Publikationen

Hier finden Sie von Know-Center MitarbeiterInnen verfasste wissenschaftliche Publikationen

2018

Kowald Dominik

Modeling Activation Processes in HumanMemory to Improve Tag Recommendation

SIGIR Newsletter, ACM, 2018

Journal
Social tagging systems enable users to collaboratively assign freely chosen keywords (i.e.,tags) to resources (e.g., Web links). In order to support users in nding descriptive tags, tagrecommendation algorithms have been proposed. One issue of current state-of-the-art tagrecommendation algorithms is that they are often designed in a purely data-driven way andthus, lack a thorough understanding of the cognitive processes that play a role when peopleassign tags to resources. A prominent example is the activation equation of the cognitivearchitecture ACT-R, which formalizes activation processes in human memory to determineif a speci c memory unit (e.g., a word or tag) will be needed in a speci c context. It is theaim of this thesis to investigate if a cognitive-inspired approach, which models activationprocesses in human memory, can improve tag recommendations.For this, the relation between activation processes in human memory and usage prac-tices of tags is studied, which reveals that (i) past usage frequency, (ii) recency, and (iii)semantic context cues are important factors when people reuse tags. Based on this, acognitive-inspired tag recommendation approach termed BLLAC+MPr is developed based onthe activation equation of ACT-R. An extensive evaluation using six real-world folksonomydatasets shows that BLLAC+MPr outperforms current state-of-the-art tag recommendationalgorithms with respect to various evaluation metrics. Finally, BLLAC+MPr is utilized forhashtag recommendations in Twitter to demonstrate its generalizability in related areas oftag-based recommender systems. The ndings of this thesis demonstrate that activationprocesses in human memory can be utilized to improve not only social tag recommendationsbut also hashtag recommendations. This opens up a number of possible research strands forfuture work, such as the design of cognitive-inspired resource recommender systems
2018

Bassa Akim, Kröll Mark, Kern Roman

GerIE - An Open InformationExtraction System for the German Language

Journal of Universal Computer Science, 2018

Journal
Open Information Extraction (OIE) is the task of extracting relations fromtext without the need of domain speci c training data. Currently, most of the researchon OIE is devoted to the English language, but little or no research has been conductedon other languages including German. We tackled this problem and present GerIE, anOIE parser for the German language. Therefore we started by surveying the availableliterature on OIE with a focus on concepts, which may also apply to the Germanlanguage. Our system is built upon the output of a dependency parser, on which anumber of hand crafted rules are executed. For the evaluation we created two dedicateddatasets, one derived from news articles and one based on texts from an encyclopedia.Our system achieves F-measures of up to 0.89 for sentences that have been correctlypreprocessed.
2018

Lovric Mario, Molero Perez Jose Manuel, Kern Roman

PySpark and RDKit: moving towards Big Data in QSAR

Journal of Chemical Information and Modelin, ACSPublication, 2018

Journal
We present an implementation of the cheminformatics toolkit RDKit in a distributed computing environment, Apache Hadoop. Together with the Apache Spark analytics engine, wrapped in PySpark, resources from commodity scalable hardware can be used for cheminformatic calculations and query operations with basic knowledge in Python coding and understanding of the RDD abstraction. A comparison of the computing acceleration in the Hadoop cluster is presented in two computation tasks of querying substructures and calculating molecular descriptors, as well as the source code for the PySpark-RDKit implementation
2018

Rexha Andi, Dragoni Mauro , Federici Marco

An Unsupervised Aspect Extraction Strategy For Monitoring Real-Time Reviews Stream

Elsevier, 2018

Journal
One of the most important opinion mining research directions falls in the extraction ofpolarities referring to specific entities (aspects) contained in the analyzed texts. Thedetection of such aspects may be very critical especially when documents come fromunknown domains. Indeed, while in some contexts it is possible to train domainspecificmodels for improving the effectiveness of aspects extraction algorithms, inothers the most suitable solution is to apply unsupervised techniques by making suchalgorithms domain-independent and more efficient in a real-time environment. Moreover,an emerging need is to exploit the results of aspect-based analysis for triggeringactions based on these data. This led to the necessity of providing solutions supportingboth an effective analysis of user-generated content and an efficient and intuitive wayof visualizing collected data. In this work, we implemented an opinion monitoringservice implementing (i) a set of unsupervised strategies for aspect-based opinion miningtogether with (ii) a monitoring tool supporting users in visualizing analyzed data.The aspect extraction strategies are based on the use of an open information extractionstrategy. The effectiveness of the platform has been tested on benchmarks provided by the SemEval campaign and have been compared with the results obtained by domainad aptedtechniques.
2018

Lassnig Markus, Stabauer Petra, Breitfuß Gert, Mauthner Katrin

Geschäftsmodellinnovationen im Zeitalter von Digitalisierung und Industrie 4.0

HMD Praxis der Wirtschaftsinformatik Wirtschaftsinformatik, Stefan Meinhard, Karl-Michael Popp, Springer Fachmedien Wiesbaden, Wiesbaden, 2018

Journal
Zahlreiche Forschungsergebnisse im Bereich Geschäftsmodellinnovationenhaben gezeigt, dass über 90% aller Geschäftsmodelle der letzten50 Jahre aus einer Rekombination von bestehenden Konzepten entstanden sind.Grundsätzlich gilt das auch für digitale Geschäftsmodellinnovationen. Angesichtsder Breite potenzieller digitaler Geschäftsmodellinnovationen wollten die Autorenwissen, welche Modellmuster in der wirtschaftlichen Praxis welche Bedeutung haben.Deshalb wurde die digitale Transformation mit neuen Geschäftsmodellen ineiner empirischen Studie basierend auf qualitativen Interviews mit 68 Unternehmenuntersucht. Dabei wurden sieben geeignete Geschäftsmodellmuster identifiziert, bezüglichihres Disruptionspotenzials von evolutionär bis revolutionär klassifiziert undder Realisierungsgrad in den Unternehmen analysiert.Die stark komprimierte Conclusio lautet, dass das Thema Geschäftsmodellinnovationendurch Industrie 4.0 und digitale Transformation bei den Unternehmenangekommen ist. Es gibt jedoch sehr unterschiedliche Geschwindigkeiten in der Umsetzungund im Neuheitsgrad der Geschäftsmodellideen. Die schrittweise Weiterentwicklungvon Geschäftsmodellen (evolutionär) wird von den meisten Unternehmenbevorzugt, da hier die grundsätzliche Art und Weise des Leistungsangebots bestehenbleibt. Im Gegensatz dazu gibt es aber auch Unternehmen, die bereits radikale Änderungenvornehmen, die die gesamte Geschäftslogik betreffen. Entsprechend wird imvorliegenden Artikel ein Clustering von Geschäftsmodellinnovatoren vorgenommen – von Hesitator über Follower über Optimizer bis zu Leader in Geschäftsmodellinnovationen
2018

Hasani-Mavriqi Ilire, Kowald Dominik, Helic Denis, Lex Elisabeth

Consensus Dynamics in Online Collaboration Systems

Journal of Computational Social Networks , Ding-Zhu Du and My T. Thai, Springer Open, 2018

Journal
In this paper, we study the process of opinion dynamics and consensus building inonline collaboration systems, in which users interact with each other followingtheir common interests and their social pro les. Speci cally, we are interested inhow users similarity and their social status in the community, as well as theinterplay of those two factors inuence the process of consensus dynamics. Forour study, we simulate the di usion of opinions in collaboration systems using thewell-known Naming Game model, which we extend by incorporating aninteraction mechanism based on user similarity and user social status. Weconduct our experiments on collaborative datasets extracted from the Web. Our ndings reveal that when users are guided by their similarity to other users, theprocess of consensus building in online collaboration systems is delayed. Asuitable increase of inuence of user social status on their actions can in turnfacilitate this process. In summary, our results suggest that achieving an optimalconsensus building process in collaboration systems requires an appropriatebalance between those two factors.
2018

Santos Tiago, Walk Simon, Kern Roman, Strohmaier M., Helic Denis

Activity in Questions & Answers Websites

ACM Transactions on Social Computing, 2018

Journal
Millions of users on the Internet discuss a variety of topics on Question and Answer (Q&A) instances. However, not all instances and topics receive the same amount of attention, as some thrive and achieve self-sustaining levels of activity while others fail to attract users and either never grow beyond being a small niche community or become inactive. Hence, it is imperative to not only better understand but also to distill deciding factors and rules that define and govern sustainable Q&A instances. We aim to empower community managers with quantitative methods for them to better understand, control and foster their communities, and thus contribute to making the Web a more efficient place to exchange information. To that end, we extract, model and cluster user activity-based time series from 50 randomly selected Q&A instances from the StackExchange network to characterize user behavior. We find four distinct types of user activity temporal patterns, which vary primarily according to the users' activity frequency. Finally, by breaking down total activity in our 50 Q&A instances by the previously identified user activity profiles, we classify those 50 Q&A instances into three different activity profiles. Our categorization of Q&A instances aligns with the stage of development and maturity of the underlying communities, which can potentially help operators of such instances not only to quantitatively assess status and progress, but also allow them to optimize community building efforts
2018

Lovric Mario

Molecular modeling of the quantitative structure activity relationship in Python – a tutorial (part I)

Journal of Chemists and Chemical Engineers, Croatian Society of Chemical Engineers, Zagreb, 2018

Journal
Today's data amount is significantly increasing. A strong buzzword in research nowadays is big data.Therefore the chemistry student has to be well prepared for the upcoming age where he does not only rule the laboratories but is a modeler and data scientist as well. This tutorial covers the very basics of molecular modeling and data handling with the use of Python and Jupyter Notebook. It is the first in a series aiming to cover the relevant topics in machine learning, QSAR and molecular modeling, as well as the basics of Python programming
2018

Hojas Sebastian, Kröll Mark, Kern Roman

GerMeter - A Corpus for Measuring Text Reuse in the Austrian JournalisticDomain

Language Resources and Evaluation, Springer, 2018

Journal
2018

Rexha Andi, Kröll Mark, Ziak Hermann, Kern Roman

Authorship Identification of Documents with High Content Similarity

Scientometrics, Wolfgang Glänzel, Springer Link, 2018

Journal
The goal of our work is inspired by the task of associating segments of text to their real authors. In this work, we focus on analyzing the way humans judge different writing styles. This analysis can help to better understand this process and to thus simulate/ mimic such behavior accordingly. Unlike the majority of the work done in this field (i.e., authorship attribution, plagiarism detection, etc.) which uses content features, we focus only on the stylometric, i.e. content-agnostic, characteristics of authors.Therefore, we conducted two pilot studies to determine, if humans can identify authorship among documents with high content similarity. The first was a quantitative experiment involving crowd-sourcing, while the second was a qualitative one executed by the authors of this paper.Both studies confirmed that this task is quite challenging.To gain a better understanding of how humans tackle such a problem, we conducted an exploratory data analysis on the results of the studies. In the first experiment, we compared the decisions against content features and stylometric features. While in the second, the evaluators described the process and the features on which their judgment was based. The findings of our detailed analysis could (i) help to improve algorithms such as automatic authorship attribution as well as plagiarism detection, (ii) assist forensic experts or linguists to create profiles of writers, (iii) support intelligence applications to analyze aggressive and threatening messages and (iv) help editor conformity by adhering to, for instance, journal specific writing style.
2018

Babić Sanja, Barišić Josip, Stipaničev Draženka, Repec Siniša, Lovric Mario, Malev Olga, Čož-Rakovac Rozalindra, Klobučar GIV

Assessment of river sediment toxicity: Combining empirical zebrafish embryotoxicity testing with in silico toxicity characterization

Science of the Total Environment, Elsevier, 2018

Journal
Quantitative chemical analyses of 428 organic contaminants (OCs) confirmed the presence of 313 OCs in the sediment extracts from river Sava, Croatia. Pharmaceuticals were present in higher concentration than pesticides thus confirming their increasing threat to freshwater ecosystems. Toxicity evaluation of the sediment extracts from four locations (Jesenice, Rugvica, Galdovo and Lukavec) using zebrafish embryotoxicity test (ZET) accompanied with semi-quantitative histopathological analyses exhibited good correlation with cumulative number and concentrations of OCs at investigated sites (10,048.6, 15,222.8, 1,247.6, and 9,130.5 ng/g respectively) and proved its role as a good indicator of toxic potential of complex contaminant mixtures. Toxicity prediction of sediment extracts and sediment was assessed using Toxic unit (TU) approach and PBT (persistence, bioaccumulation and toxicity) ranking. Also, prior-knowledge informed chemical-gene interaction models were generated and graph mining approaches used to identify OCs and genes most likely to be influential in these mixtures. Predicted toxicity of sediment extracts (TUext) for sampled locations was similar to the results obtained by ZET and associated histopathology resulting in Rugvica sediment as being the most toxic, followed by Jesenice, Lukavec and Galdovo. Sediment TU (TUsed) favoured OCs with low octanol-water partition coefficient like herbicide glyphosate and antibiotics ciprofloxacin and sulfamethazine thus indicating locations containing higher concentrations of these OCs (Galdovo and Rugvica) as most toxic. Results suggest that comprehensive in silico sediment toxicity predictions advocate providing equal attention to organic contaminants with either very low or very high log Kow
2018

Arslanovic Jasmina, Lovric Mario, Kern Roman

EATING DISORDERS IN SYNCHRONIZED SWIMMING

2018

Journal
The aim of the present study was to identify eating disorders in synchronized swimming and the level of distortion of the body image of synchronized swimming athletes. Synchronized swimming is sport in which modality is considered of risk for development of eating disorder. It is a Olympic sport where synchronized swimmers are competing in the range of age 13-15 years old and that ages are critical for every young woman (puberty). Also, the beauty of movement is associated to low body mass and judges include thinness in their final score. Eating disorders include anorexia nervosa, bulimia nervosa, binge eating symptoms, and other specified (or non-specified) feeding or eating disorders which are presenting serious issue. Twenty synchronized swimmers age 13-16 years old was studied and the group of twenty female water polo players was used for comparison with athletes. To test the presence of some symptoms of the eating disorders was used The Eating Attitudes Test: “Eat26” (Garner and Garfunkel, 1979). Comparison of results have shown that statistically significant difference exist between synchronized swimmers and female water polo players in the image of dissatisfaction, with pathological control of body weight of synchronized swimmers. Almost every sport demands certain nutrition and most of them certain weight, but that should be achieved with the help of expert team. It is possible that synchronized swimmers are skinny and strong, but only with certain nutrition which is individual for every swimmer.
2018

Lacic Emanuel, Traub Matthias, Duricic Tomislav, Haslauer Eva, Lex Elisabeth

Gone in 30 Days! Predictions for Car Import Planning

it - Information Technology, De Gruyter Oldenbourg, 2018

Journal
A challenge for importers in the automobile industry is adjusting to rapidly changing market demands. In this work, we describe a practical study of car import planning based on the monthly car registrations in Austria. We model the task as a data driven forecasting problem and we implement four different prediction approaches. One utilizes a seasonal ARIMA model, while the other is based on LSTM-RNN and both compared to a linear and seasonal baselines. In our experiments, we evaluate the 33 different brands by predicting the number of registrations for the next month and for the year to come.
2017

Seitlinger Paul, Ley Tobias, Kowald Dominik, Theiler Dieter, Hasani-Mavriqi Ilire, Dennerlein Sebastian, Lex Elisabeth, Albert D.

Balancing the Fluency-Consistency Tradeoff in Collaborative Information Search Using a Recommender Approach

International Journal of Human-Computer Interaction, Constantine Stephanidis and Gavriel Salvendy , Taylor and Francis, 2017

Journal
Creative group work can be supported by collaborative search and annotation of Web resources. In this setting, it is important to help individuals both stay fluent in generating ideas of what to search next (i.e., maintain ideational fluency) and stay consistent in annotating resources (i.e., maintain organization). Based on a model of human memory, we hypothesize that sharing search results with other users, such as through bookmarks and social tags, prompts search processes in memory, which increase ideational fluency, but decrease the consistency of annotations, e.g., the reuse of tags for topically similar resources. To balance this tradeoff, we suggest the tag recommender SoMe, which is designed to simulate search of memory from user-specific tag-topic associations. An experimental field study (N = 18) in a workplace context finds evidence of the expected tradeoff and an advantage of SoMe over a conventional recommender in the collaborative setting. We conclude that sharing search results supports group creativity by increasing the ideational fluency, and that SoMe helps balancing the evidenced fluency-consistency tradeoff.
2017

Dragoni Mauro, Federici Marco, Rexha Andi

Extracting Aspects From User-generated Content For Supporting Opinion Mining Systems

Journal of Intelligent Information Systems, Kerschberg; Z. Ras, Springer, 2017

Journal
One of the most important opinion mining research directions falls in the extraction ofpolarities referring to specific entities (aspects) contained in the analyzed texts. The detectionof such aspects may be very critical especially when documents come from unknowndomains. Indeed, while in some contexts it is possible to train domain-specificmodels for improving the effectiveness of aspects extraction algorithms, in others themost suitable solution is to apply unsupervised techniques by making such algorithmsdomain-independent. Moreover, an emerging need is to exploit the results of aspectbasedanalysis for triggering actions based on these data. This led to the necessityof providing solutions supporting both an effective analysis of user-generated contentand an efficient and intuitive way of visualizing collected data. In this work, we implementedan opinion monitoring service implementing (i) a set of unsupervised strategiesfor aspect-based opinion mining together with (ii) a monitoring tool supporting usersin visualizing analyzed data. The aspect extraction strategies are based on the use of semanticresources for performing the extraction of aspects from texts. The effectivenessof the platform has been tested on benchmarks provided by the SemEval campaign and have been compared with the results obtained by domain-adapted techniques.
2017

di Sciascio Maria Cecilia, Sabol Vedran, Veas Eduardo Enrique

Supporting Exploratory Search with a Visual User-Driven Approach

ACM Transactions on Interactive Intelligent Systems, ACM, ACM, 2017

Journal
Whenever we gather or organize knowledge, the task of search-ing inevitably takes precedence. As exploration unfolds, it be-comes cumbersome to reorganize resources along new interests,as any new search brings new results. Despite huge advances inretrieval and recommender systems from the algorithmic point ofview, many real-world interfaces have remained largely unchanged:results appear in an infinite list ordered by relevance with respect tothe current query. We introduceuRank, a user-driven visual tool forexploration and discovery of textual document recommendations.It includes a view summarizing the content of the recommenda-tion set, combined with interactive methods for understanding, re-fining and reorganizing documents on-the-fly as information needsevolve. We provide a formal experiment showing thatuRankuserscan browse the document collection and efficiently gather items rel-evant to particular topics of interest with significantly lower cogni-tive load compared to traditional list-based representations.
2017

Barreiros Carla, Veas Eduardo Enrique, Pammer-Schindler Viktoria

Can a green thumb make the difference? Using a Nature Metaphor to Communicate Sensor Information of a Coffee Machine

IEEE Consumers Electronics Magazine, 2017

Journal
This paper describes a novel visual metaphor to communicate sensor information of a connected device. The Internet of Things aims to extend every device with sensing and computing capabilities. A byproduct is that even domestic machines become increasingly complex, tedious to understand and maintain. This paper presents a prototype instrumenting a coffee machine with sensors. The machine streams the sensor data, which is picked up by an augmented reality application serving a nature metaphor. The nature metaphor, BioAR, represents the status derived from the coffee machine sensors in the features of a 3D virtual tree. The tree is meant to pass for a living proxy of the machine it represents. The metaphor, shown either with AR or a simple holographic display, reacts to the user manipulation of the machine and its workings. A first user study validates that the representation is correctly understood, and that it inspires affect for the machine. A second user study validates that the metaphor scales to a large number of machines.
2017

Kaiser René, Meixner Britta, Jäger Joscha

Reflecting on the Workshop on Interactive Content Consumption (WSICC) Series

IEEE MultiMedia Magazine, IEEE Computer Society, IEEE, 2017

Journal
Enabling interactive access to multimedia content and evaluating content-consumption behaviors and experiences involve several different research areas, which are covered at many different conferences. For four years, the Workshop on Interactive Content Consumption (WSICC) series offered a forum for combining interdisciplinary, comprehensive views, inspiring new discussions related to interactive multimedia. Here, the authors reflect on the outcome of the series.
2017

Seifert Christin, Bailer Werner, Orgel Thomas, Gantner Louis, Kern Roman, Ziak Hermann, Petit Albin, Schlötterer Jörg, Zwicklbauer Stefan, Granitzer Michael

Ubiquitous Access to Digital Cultural Heritage

Journal on Computing and Cultural Heritage (JOCCH) - Special Issue on Digital Infrastructure for Cultural Heritage, Part 1, Roberto Scopign, ACM, New York, NY, US, 2017

Journal
The digitization initiatives in the past decades have led to a tremendous increase in digitized objects in the cultural heritagedomain. Although digitally available, these objects are often not easily accessible for interested users because of the distributedallocation of the content in different repositories and the variety in data structure and standards. When users search for culturalcontent, they first need to identify the specific repository and then need to know how to search within this platform (e.g., usageof specific vocabulary). The goal of the EEXCESS project is to design and implement an infrastructure that enables ubiquitousaccess to digital cultural heritage content. Cultural content should be made available in the channels that users habituallyvisit and be tailored to their current context without the need to manually search multiple portals or content repositories. Torealize this goal, open-source software components and services have been developed that can either be used as an integratedinfrastructure or as modular components suitable to be integrated in other products and services. The EEXCESS modules andcomponents comprise (i) Web-based context detection, (ii) information retrieval-based, federated content aggregation, (iii) meta-data definition and mapping, and (iv) a component responsible for privacy preservation. Various applications have been realizedbased on these components that bring cultural content to the user in content consumption and content creation scenarios. Forexample, content consumption is realized by a browser extension generating automatic search queries from the current pagecontext and the focus paragraph and presenting related results aggregated from different data providers. A Google Docs add-onallows retrieval of relevant content aggregated from multiple data providers while collaboratively writing a document. Theserelevant resources then can be included in the current document either as citation, an image, or a link (with preview) withouthaving to leave disrupt the current writing task for an explicit search in various content providers’ portals.
2017

Thalmann Stefan, Pammer-Schindler Viktoria

Die Rolle des Mitarbeiters in der Smart Factory

Wissensmanagement, 2017

Journal
Aktuelle Untersuchungen zeigen einerseits auf, dass der Mensch weiterhin eine zentrale Rolle in der Industrie spielt. Andererseits ist aber auch klar, dass die Zahl der direkt in der Produktion beschäftigten Mitarbeter sinken wird. Die Veränderung wird dahin gehen, dass der Mensch weniger gleichförmige Prozese bearbeitet, stattdessen aber in der Lage sein muss, sich schnell ändernden Arbeitstätigkeiten azupassen und individualisierte Fertigungsprozesse zu steuern. Die Reduktion der Mitarbeiter hat jedoch auch eine Reduktion von Redunanzen zur Folge. Dies führt dazu, dass dem Einzelnen mehr Verantwortung übertragen wird. Als Folge haben Fehlentscheidungen eine görßere Tragweite und bedeuten somit auch ein höheres Risikio. Der Erfolg einer Industrie 4.0 Kampagne wird daher im Wesentlichen von den Anpassungsfähigkeiten der Mitarbeiter abhängen.
2017

Pammer-Schindler Viktoria, Fessl Angela, Weghofer Franz, Thalmann Stefan

Lernen 4.0 Herausforderungen für Menschen in der Industrie 4.0 erfolgreich meistern.

Productivity, 2017

Journal
Die Digitalisierung der Industrie wird aktuell sehr stark aus technoogischer Sicht betrachtet. Aber auch für den Menschen ergebn sich vielfältige Herausforderungen in dieser veränderten Arbeitsumgebung. Sie betreffen hautsächlich das Lernen von benötigtem Wissen.
2017

Pammer-Schindler Viktoria, Fessl Angela, Wesiak Gudrun, Feyertag Sandra, Rivera-Pelayo Verónica

In-app Reflection Guidance: Lessons Learned across Four Field Trials at the Workplace

IEEE Transactions on Learning Technologies, IEEE, 2017

Journal
This paper presents a concept for in-app reflection guidance and its evaluation in four work-related field trials. By synthesizing across four field trials, we can show that computer-based reflection guidance can function in the workplace, in the sense of being accepted as technology, being perceived as useful and leading to reflective learning. This is encouraging for all endeavours aiming to transfer existing knowledge on reflection supportive technology from educational settings to the workplace. However,reflective learning in our studies was mostly visible to limited depth in textual entries made in the applications themselves; and proactive reflection guidance technology like prompts were often found to be disruptive. We offer these two issues as highly relevant questions for future research.
2017

Pammer-Schindler Viktoria, Rivera-Pelayo Verónica, Fessl Angela, Müller Lars

Introducing Mood Self-Tracking at Work: Empirical Insights from Call Centers

ACM Transactions on Computer-Human Interaction (TOCHI), ACM New York, NY, USA , 2017

Journal
The benefits of self-tracking have been thoroughly investigated in private areas of life, like health or sustainable living, but less attention has been given to the impact and benefits of self-tracking in work-related settings. Through two field studies, we introduced and evaluated a mood self-tracking application in two call centers to investigate the role of mood self-tracking at work, as well as its impact on individuals and teams. Our studies indicate that mood self-tracking is accepted and can improve performance if the application is well integrated into the work processes and matches the management style. The results show that (i) capturing moods and explicitly relating them to work tasks facilitated reflection, (ii) mood self-tracking increased emotional awareness and this improved cohesion within teams, and (iii) proactive reactions by managers to trends and changes in team members’ mood were key for acceptance of reflection and correlated with measured improvements in work performance. These findings help to better understand the role and potential of self-tracking in work settings and further provide insights that guide future researchers and practitioners to design and introduce these tools in a workplace setting.
2017

Topps David, Dennerlein Sebastian, Treasure-Jones Tamsin

Raising the BarCamp: international reflections

MedEdPublish, 2017

Journal
There is increasing interest in Barcamps and Unconferences as an educational approach during traditional medical education conferences. Ourgroup has now accumulated extensive experience in these formats over a number of years in different educational venues. We present asummary of observations and lessons learned about what works and what doesn’t.
2017

Wilsdon James , Bar-Ilan Judit, Frodemann Robert, Lex Elisabeth, Peters Isabella , Wouters Paul

Next-generation altmetrics: responsible metrics and evaluation for open science

European Union, 2017

Journal
2017

Ross-Hellauer Anthony, Deppe A., Schmidt B.

Survey on open peer review: Attitudes and experience amongst editors, authors and reviewers

Journal, PLOS One, 2017

Journal
Open peer review (OPR) is a cornerstone of the emergent Open Science agenda. Yet to date no large-scale survey of attitudes towards OPR amongst academic editors, authors, reviewers and publishers has been undertaken. This paper presents the findings of an online survey, conducted for the OpenAIRE2020 project during September and October 2016, that sought to bridge this information gap in order to aid the development of appropriate OPR approaches by providing evidence about attitudes towards and levels of experience with OPR. The results of this cross-disciplinary survey, which received 3,062 full responses, show the majority (60.3%) of respondents to be believe that OPR as a general concept should be mainstream scholarly practice (although attitudes to individual traits varied, and open identities peer review was not generally favoured). Respondents were also in favour of other areas of Open Science, like Open Access (88.2%) and Open Data (80.3%). Among respondents we observed high levels of experience with OPR, with three out of four (76.2%) reporting having taken part in an OPR process as author, reviewer or editor. There were also high levels of support for most of the traits of OPR, particularly open interaction, open reports and final-version commenting. Respondents were against opening reviewer identities to authors, however, with more than half believing it would make peer review worse. Overall satisfaction with the peer review system used by scholarly journals seems to strongly vary across disciplines. Taken together, these findings are very encouraging for OPR’s prospects for moving mainstream but indicate that due care must be taken to avoid a “one-size fits all” solution and to tailor such systems to differing (especially disciplinary) contexts. OPR is an evolving phenomenon and hence future studies are to be encouraged, especially to further explore differences between disciplines and monitor the evolution of attitudes.
2017

di Sciascio Maria Cecilia, Sabol Vedran, Veas Eduardo Enrique

Supporting Exploratory Search with a Visual User-Driven Approach

Transactions on Interactive Intelligent Systems, ACM, 2017

Journal
Whenever users engage in gathering and organizing new information, searching and browsing activities emerge at the core of the exploration process. As the process unfolds and new knowledge is acquired, interest drifts occur inevitably and need to be accounted for. Despite the advances in retrieval and recommender algorithms, real-world interfaces have remained largely unchanged: results are delivered in a relevance-ranked list. However, it quickly becomes cumbersome to reorganize resources along new interests, as any new search brings new results. We introduce an interactive user-driven tool that aims at supporting users in understanding, refining, and reorganizing documents on the fly as information needs evolve. Decisions regarding visual and interactive design aspects are tightly grounded on a conceptual model for exploratory search. In other words, the different views in the user interface address stages of awareness, exploration, and explanation unfolding along the discovery process, supported by a set of text-mining methods. A formal evaluation showed that gathering items relevant to a particular topic of interest with our tool incurs in a lower cognitive load compared to a traditional ranked list. A second study reports on usage patterns and usability of the various interaction techniques within a free, unsupervised setting.
2017

Ross-Hellauer Anthony

What is open peer review? A systematic review [version 2; referees: 4 approved]

F1000Research, F1000, 2017

Journal
Background: “Open peer review” (OPR), despite being a major pillar of Open Science, has neither a standardized definition nor an agreed schema of its features and implementations. The literature reflects this, with numerous overlapping and contradictory definitions. While for some the term refers to peer review where the identities of both author and reviewer are disclosed to each other, for others it signifies systems where reviewer reports are published alongside articles. For others it signifies both of these conditions, and for yet others it describes systems where not only “invited experts” are able to comment. For still others, it includes a variety of combinations of these and other novel methods.Methods: Recognising the absence of a consensus view on what open peer review is, this article undertakes a systematic review of definitions of “open peer review” or “open review”, to create a corpus of 122 definitions. These definitions are systematically analysed to build a coherent typology of the various innovations in peer review signified by the term, and hence provide the precise technical definition currently lacking.Results: This quantifiable data yields rich information on the range and extent of differing definitions over time and by broad subject area. Quantifying definitions in this way allows us to accurately portray exactly how ambiguously the phrase “open peer review” has been used thus far, for the literature offers 22 distinct configurations of seven traits, effectively meaning that there are 22 different definitions of OPR in the literature reviewed.Conclusions: I propose a pragmatic definition of open peer review as an umbrella term for a number of overlapping ways that peer review models can be adapted in line with the aims of Open Science, including making reviewer and author identities open, publishing review reports and enabling greater participation in the peer review process.
2016

Dennerlein Sebastian, Treasure-Jones Tamsin, Lex Elisabeth, Ley Tobias

The role of collaboration and shared understanding in interprofessional teamwork

AMEE - International Conference of Medical Education 2016, AMEE 2016, 2016

Journal
Background: Teamworking, within and acrosshealthcare organisations, is essential to deliverexcellent integrated care. Drawing upon an alternationof collaborative and cooperative phases, we exploredthis teamworking and respective technologicalsupport within UK Primary Care. Participants usedBits&Pieces (B&P), a sensemaking tool for tracedexperiences that allows sharing results and mutuallyelaborating them: i.e. cooperating and/orcollaborating.Summary of Work: We conducted a two month-longcase study involving six healthcare professionals. InB&P, they reviewed organizational processes, whichrequired the involvement of different professions ineither collaborative and/or cooperative manner. Weused system-usage data, interviews and qualitativeanalysis to understand the interplay of teamworkingpracticeand technology.Summary of Results: Within our analysis we mainlyidentified cooperation phases. In a f2f-meeting,professionals collaboratively identified subtasks andassigned individuals leading collaboration on them.However, these subtasks were undertaken asindividual sensemaking efforts and finally combined(i.e. cooperation). We found few examples ofreciprocal interpretation processes (i.e. collaboration):e.g. discussing problems during sensemaking ormonitoring other’s sensemaking-outcomes to makesuggestions.Discussion: These patterns suggest that collaborationin healthcare often helps to construct a minimalshared understanding (SU) of subtasks to engage incooperation, where individuals trust in other’scompetencies and autonomous completion. However,we also found that professionals with positivecollaboration history and deepened SU were willing toundertake subtasks collaboratively. It seems thatacquiring such deepened SU of concepts andmethods, leads to benefits that motivate professionalsto collaborate more.Conclusion: Healthcare is a challenging environmentrequiring interprofessional work across organisations.For effective teamwork, a deepened SU is crucial andboth cooperation and collaboration are required.However, we found a tendency of staff to rely mainlyon cooperation when working in teams and not fullyexplore benefits of collaboration.Take Home Messages: To maximise benefits ofinterprofessional working, tools for teamworkingshould support both cooperation and collaborationprocesses and scaffold the move between them
2016

Yi-ling Lin, Parra Denis, Trattner Christoph, Brusilovsky Peter

Tag-Based Information Access in Image Collections: Insights from Log Analysis, Eye-Gaze Analysis, and User Feedback

IEEE Transactions on Systems, Man and Cybernetics: Systems (SMCA) , 2016

Journal
2016

Kraker Peter, Peters Isabella, Lex Elisabeth, Gumpenberger Christian , Gorraiz Juan

Research data explored: an extended analysis of citations and alt metrics

Journal of Scientometrics, Springer Link, Springer-Verlag, Cham, 2016

Journal
In this study, we explore the citedness of research data, its distribution overtime and its relation to the availability of a digital object identifier (DOI) in the ThomsonReuters database Data Citation Index (DCI). We investigate if cited research data ‘‘im-pacts’’ the (social) web, reflected by altmetrics scores, and if there is any relationshipbetween the number of citations and the sum of altmetrics scores from various social mediaplatforms. Three tools are used to collect altmetrics scores, namely PlumX, ImpactStory,and Altmetric.com, and the corresponding results are compared. We found that out of thethree altmetrics tools, PlumX has the best coverage. Our experiments revealed thatresearch data remain mostly uncited (about 85 %), although there has been an increase inciting data sets published since 2008. The percentage of the number of cited research datawith a DOI in DCI has decreased in the last years. Only nine repositories are responsible for research data with DOIs and two or more citations. The number of cited research datawith altmetrics ‘‘foot-prints’’ is even lower (4–9 %) but shows a higher coverage ofresearch data from the last decade. In our study, we also found no correlation between thenumber of citations and the total number of altmetrics scores. Yet, certain data types (i.e.survey, aggregate data, and sequence data) are more often cited and also receive higheraltmetrics scores. Additionally, we performed citation and altmetric analyses of allresearch data published between 2011 and 2013 in four different disciplines covered by theDCI. In general, these results correspond very well with the ones obtained for research datacited at least twice and also show low numbers in citations and in altmetrics. Finally, weobserved that there are disciplinary differences in the availability and extent of altmetricsscores.
2016

Kraker Peter, Dennerlein Sebastian, Dörler, D, Ferus, A, Gutounig Robert, Heigl, F., Kaier, C., Rieck Katharina, Šimukovic, E., Vignoli Michela

The Vienna Principles: A Vision for Scholarly Communication in the 21st Century.

15th Annual STS Conference Graz 2016 Track: The Politics of Open Science, OANA, Zenodo, 2016

Journal
Between April 2015 and June 2016, members of the Open Access Network Aus- tria (OANA) working group “Open Access and Scholarly Communication” met in Vienna to discuss a fundamental reform of the scholarly communication system.By scholarly communication we mean the processes of producing, reviewing, organising, disseminating and preserving scholarly knowledge1. Scholarly communication does not only concern researchers, but also society at large, especially students, educators, policy makers, public administrators, funders, librarians, journalists, practitioners, publishers, public and private organisations, and interested citizens.
2016

Santos Patricia, Dennerlein Sebastian, Theiler Dieter, Cook John, Treasure-Jones Tamsin, Holley Debbie, Kerr Micky , Atwell Graham, Kowald Dominik, Lex Elisabeth

Going beyond your Personal Learning Network, using Recommendations and Trust through a Multimedia Question-Answering Service for Decision-support: a Case Study in the Healthcare

Journal of Universal Computer Science, J.UCS, J. UCS Consortium, 2016

Journal
Social learning networks enable the sharing, transfer and enhancement of knowledge in the workplace that builds the ground to exchange informal learning practices. In this work, three healthcare networks are studied in order to understand how to enable the building, maintaining and activation of new contacts at work and the exchange of knowledge between them. By paying close attention to the needs of the practitioners, we aimed to understand how personal and social learning could be supported by technological services exploiting social networks and the respective traces reflected in the semantics. This paper presents a case study reporting on the results of two co-design sessions and elicits requirements showing the importance of scaffolding strategies in personal and shared learning networks. Besides, the significance of these strategies to aggregate trust among peers when sharing resources and decision-support when exchanging questions and answers. The outcome is a set of design criteria to be used for further technical development for a social tool. We conclude with the lessons learned and future work.
2016

Yusuke Fukazawa, Kröll Mark, Strohmaier M., Ota Jun

IR based Task-Model Learning: Automating the hierarchical structuring of tasks

Web Intelligence, IOS Press, IOS Press, 2016

Journal
Task-models concretize general requests to support users in real-world scenarios. In this paper, we present an IR based algorithm (IRTML) to automate the construction of hierarchically structured task-models. In contrast to other approaches, our algorithm is capable of assigning general tasks closer to the top and specific tasks closer to the bottom. Connections between tasks are established by extending Turney’s PMI-IR measure. To evaluate our algorithm, we manually created a ground truth in the health-care domain consisting of 14 domains. We compared the IRTML algorithm to three state-of-the-art algorithms to generate hierarchical structures, i.e. BiSection K-means, Formal Concept Analysis and Bottom-Up Clustering. Our results show that IRTML achieves a 25.9% taxonomic overlap with the ground truth, a 32.0% improvement over the compared algorithms.
2016

Trattner Christoph, Kowald Dominik, Ley Tobias, Seitlinger Paul

Modeling Activation Processes in Human Memory to Predict the Reuse of Tags

The Journal of Web Science, James Finlay, NOW publishing, 2016

Journal
Several successful tag recommendation mechanisms have been developed, including algorithms built upon Collaborative Filtering, Tensor Factorization, graph-based and simple "most popular tags" approaches. From an economic perspective, the latter approach has been convincing since calculating frequencies is computationally efficient and effective with respect to different recommender evaluation metrics. In this paper, we introduce a tag recommendation algorithm that mimics the way humans draw on items in their long-term memory in order to extend these conventional "most popular tags" approaches. Based on a theory of human memory, the approach estimates a tag's reuse probability as a function of usage frequency and recency in the user's past (base-level activation) as well as of the current semantic context (associative component).Using four real-world folksonomies gathered from bookmarks in BibSonomy, CiteULike, Delicious and Flickr, we show how refining frequency-based estimates by considering recency and semantic context outperforms conventional "most popular tags" approaches and another existing and very effective but less theory-driven, time-dependent recommendation mechanism. By combining our approach with a simple resource-specific frequency analysis, our algorithm outperforms other well-established algorithms, such as Collaborative Filtering, FolkRank and Pairwise Interaction Tensor Factorization with respect to recommender accuracy and runtime. We conclude that our approach provides an accurate and computationally efficient model of a user's temporal tagging behavior. Moreover, we demonstrate how effective principles of recommender systems can be designed and implemented if human memory processes are taken into account.
2016

Silva Nelson, Caldera Christian, Krispel Ulrich, Eggeling Eva, Sunk Alexander, Reisinger Gerhard, Sihn Wilfried, Fellner Dieter W.

VASCO - Digging the Dead Man's Chest of Value Streams

International Journal on Advances in Intelligent Systems, IARIA, 2016

Journal
Value stream mapping is a lean management method for analyzing and optimizing a series of events for production or services. Even today the first step in value stream analysis – the acquisition of the current state map – is still created using pen & paper by physically visiting the production line. We capture a digital representation of how manufacturing processes look like in reality. The manufacturing processes can be represented and efficiently analyzed for future production planning as a future state map by using a meta description together with a dependency graph. With VASCO we present a tool, which contributes to all parts of value stream analysis - from data acquisition, over analyzing, planning, comparison up to simulation of alternative future state maps.We call this a holistic approach for Value stream mapping including detailed analysis of lead time, productivity, space, distance, material disposal, energy and carbon dioxide equivalents – depending in a change of calculated direct product costs.
2016

Hasani-Mavriqi Ilire, Geigl Florian, Pujari Suhbash Chandra, Lex Elisabeth, Helic Denis

The Influence of Social Status and Network Structure on Consensus Building in Collaboration Networks

Social Network Analysis and Mining, Reda Alhajj, Springer Vienna, 2016

Journal
In this paper, we study the process of opinion dynamics and consensus building in online collaboration systems, in which users interact with each other following their common interests and their social profiles. Specifically, we are interested in how users similarity and their social status in the community, as well as the interplay of those two factors influence the process of consensus dynamics. For our study, we simulate the diffusion of opinions in collaboration systems using the well-known Naming Game model, which we extend by incorporating an interaction mechanism based on user similarity and user social status. We conduct our experiments on collaborative datasets extracted from the Web. Our findings reveal that when users are guided by their similarity to other users, the process of consensus building in online collaboration systems is delayed. A suitable increase of influence of user social status on their actions can in turn facilitate this process. In summary, our results suggest that achieving an optimal consensus building process in collaboration systems requires an appropriate balance between those two factors.
2016

Fessl Angela, Pammer-Schindler Viktoria, Blunk Oliver, Prilla Michael

The known universe of reflection guidance: a literature review

International Journal of Technology Enhanced Learning, Inderscience Enterprises Ltd., 2016

Journal
Reflective learning has been established as a process that deepenslearning in both educational and work-related settings. We present a literaturereview on various approaches and tools (e.g., prompts, journals, visuals)providing guidance for facilitating reflective learning. Research consideredin this review coincides common understanding of reflective learning, hasapplied and evaluated a tool supporting reflection and presents correspondingresults. Literature was analysed with respect to timing of reflection, reflectionparticipants, type of reflection guidance, and results achieved regardingreflection. From this analysis, we were able to derive insights, guidelinesand recommendations for the design of reflection guidance functionality incomputing systems: (i) ensure that learners understand the purpose of reflectivelearning, (ii) combine reflective learning tools with reflective questions either inform of prompts or with peer-to-peer or group discussions, (iii) for work-relatedsettings consider the time with regard to when and how to motivate to reflect.
2016

Trattner Christoph, Kuśmierczyk Tomasz, Nørvåg Kjetil

FOODWEB - Studying Online Food Consumption and Production Patterns on the Web

ERCIM NEWS, ERCIM EEIG, 2016

Journal
2016

Kopeinik Simone, Kowald Dominik, Hasani-Mavriqi Ilire, Lex Elisabeth

Improving Collaborative Filtering Using a Cognitive Model of Human Category Learning

Journal of WebScience, James Finlay, Now publishing, 2016

Journal
Classic resource recommenders like Collaborative Filteringtreat users as just another entity, thereby neglecting non-linear user-resource dynamics that shape attention and in-terpretation. SUSTAIN, as an unsupervised human cate-gory learning model, captures these dynamics. It aims tomimic a learner’s categorization behavior. In this paper, weuse three social bookmarking datasets gathered from Bib-Sonomy, CiteULike and Delicious to investigate SUSTAINas a user modeling approach to re-rank and enrich Collab-orative Filtering following a hybrid recommender strategy.Evaluations against baseline algorithms in terms of recom-mender accuracy and computational complexity reveal en-couraging results. Our approach substantially improves Col-laborative Filtering and, depending on the dataset, success-fully competes with a computationally much more expen-sive Matrix Factorization variant. In a further step, we ex-plore SUSTAIN’s dynamics in our specific learning task andshow that both memorization of a user’s history and clus-tering, contribute to the algorithm’s performance. Finally,we observe that the users’ attentional foci determined bySUSTAIN correlate with the users’ level of curiosity, iden-tified by the SPEAR algorithm. Overall, the results ofour study show that SUSTAIN can be used to efficientlymodel attention-interpretation dynamics of users and canhelp improve Collaborative Filtering for resource recommen-dations.
2016

Kraker Peter, Kittel Christopher, Enkhbayar Asuraa

Open Knowledge Maps: Creating a Visual Interface to the World’s Scientific Knowledge Based on Natural Language Processing

027.7 Journal for Library Culture, 2016

Journal
The goal of Open Knowledge Maps is to create a visual interface to the world’s scientific knowledge. The base for this visual interface consists of so-called knowledge maps, which enable the exploration of existing knowledge and the discovery of new knowledge. Our open source knowledge mapping software applies a mixture of summarization techniques and similarity measures on article metadata, which are iteratively chained together. After processing, the representation is saved in a database for use in a web visualization. In the future, we want to create a space for collective knowledge mapping that brings together individuals and communities involved in exploration and discovery. We want to enable people to guide each other in their discovery by collaboratively annotating and modifying the automatically created maps.
2016

Simon Jörg Peter, Schmidt Peter, Pammer-Schindler Viktoria

Analysis of Differential Synchronisation's Energy Consumption on Mobile Devices

EAI Collaborative Computing, CoRR (2016), EAI, 2016

Journal
Synchronisation algorithms are central to collaborative editing software. As collaboration is increasingly mediated by mobile devices, the energy efficiency for such algorithms is interest to a wide community of application developers. In this paper we explore the differential synchronisation (diffsync) algorithm with respect to energy consumption on mobile devices. Discussions within this paper are based on real usage data of PDF annotations via the Mendeley iOS app, which requires realtime synchronisation. We identify three areas for optimising diffsync: a.) Empty cycles in which no changes need to be processed b.) tail energy by adapting cycle intervals and c.) computational complexity. Following these considerations, we propose a push-based diffsync strategy in which synchronisation cycles are triggered when a device connects to the network or when a device is notified of changes.
2015

Forgetting the Words but Remembering the Meaning: Modeling Forgetting in a Verbal and Semantic Tag Recommender

MSM-MUSE PostProceedings, Springer, 2015

Journal
We assume that recommender systems are more successful, when they are based on a thorough understanding of how people process information. In the current paper we test this assumption in the context of social tagging systems. Cognitive research on how people assign tags has shown that they draw on two interconnected levels of knowledge in their memory: on a conceptual level of semantic fields or LDA topics, and on a lexical level that turns patterns on the semantic level into words. Another strand of tagging research reveals a strong impact of time-dependent forgetting on users' tag choices, such that recently used tags have a higher probability being reused than "older" tags. In this paper, we align both strands by implementing a computational theory of human memory that integrates the two-level conception and the process of forgetting in form of a tag recommender. Furthermore, we test the approach in three large-scale social tagging datasets that are drawn from BibSonomy, CiteULike and Flickr. As expected, our results reveal a selective effect of time: forgetting is much more pronounced on the lexical level of tags. Second, an extensive evaluation based on this observation shows that a tag recommender interconnecting the semantic and lexical level based on a theory of human categorization and integrating time-dependent forgetting on the lexical level results in high accuracy predictions and outperforms other wellestablished algorithms, such as Collaborative Filtering, Pairwise Interaction Tensor Factorization, FolkRank and two alternative time-dependent approaches. We conclude that tag recommenders will benefit from going beyond the manifest level of word co-occurrences, and from including forgetting processes on the lexical level.
2015

Refining Frequency-Based Tag Reuse Predictions by Means of Time and Semantic Context

MSM-MUSE PostProceedings, Springer, 2015

Journal
In this paper, we introduce a tag recommendation algorithm that mimics the way humans draw on items in their long-term memory. Based on a theory of human memory, the approach estimates a tag's probability being applied by a particular user as a function of usage frequency and recency of the tag in the user's past. This probability is further refined by considering the in uence of the current semantic context of the user's tagging situation. Using three real-world folksonomies gathered from bookmarks in BibSonomy, CiteULike and Flickr, we show how refining frequency-based estimates by considering usage recency and contextual in uence outperforms conventional "most popular tags" approaches and another existing and very effective but less theory-driven, time-dependent recommendation mechanism. By combining our approach with a simple resource-specific frequency analysis, our algorithm outperforms other well-established algorithms, such as FolkRank, Pairwise Interaction Tensor Factorization and Collaborative Filtering. We conclude that our approach provides an accurate and computationally efficient model of a user's temporal tagging behavior. We demonstrate how effective principles of recommender systems can be designed and implemented if human memory processes are taken into account.
2015

Utilizing Online Social Network and Location-Based Data to Recommend Products and Categories in Online Marketplaces

MSM-MUSE PostProceedings, Springer, 2015

Journal
Recent research has unveiled the importance of online social networks for improving the quality of recommender systems and encouraged the research community to investigate better ways of exploiting the social information for recommendations. To contribute to this sparse field of research, in this paper we exploit users’ interactions along three data sources (marketplace, social network and location-based) to assess their performance in a barely studied domain: recommending products and domains of interests (i.e., product categories) to people in an online marketplace environment. To that end we defined sets of content- and network-based user similarity features for each data source and studied them isolated using an user-based Collaborative Filtering (CF) approach and in combination via a hybrid recommender algorithm, to assess which one provides the best recommendation performance. Interestingly, in our experiments conducted on a rich dataset collected from SecondLife, a popular online virtual world, we found that recommenders relying on user similarity features obtained from the social network data clearly yielded the best results in terms of accuracy in case of predicting products, whereas the features obtained from the marketplace and location-based data sources also obtained very good results in case of predicting categories. This finding indicates that all three types of data sources are important and should be taken into account depending on the level of specialization of the recommendation task.
2015

Parra Denis, Gomez M., Hutardo D., Wen X., Lin Yu-Ru, Trattner Christoph

Twitter in academic events: {A} study of temporal usage, communication, and topical patterns in 16 Computer Science conferences

Computer Communications, Elsevier, 2015

Journal
Twitter is often referred to as a backchannel for conferences. While the main conference takes place in a physicalsetting, on-site and off-site attendees socialize, introduce new ideas or broadcast information by microblogging on Twitter.In this paper we analyze scholars’ Twitter usage in 16 Computer Science conferences over a timespan of five years. Ourprimary finding is that over the years there are differences with respect to the uses of Twitter, with an increase ofinformational activity (retweets and URLs), and a decrease of conversational usage (replies and mentions), which alsoimpacts the network structure – meaning the amount of connected components – of the informational and conversationalnetworks. We also applied topic modeling over the tweets’ content and found that when clustering conferences accordingto their topics the resulting dendrogram clearly reveals the similarities and differences of the actual research interests ofthose events. Furthermore, we also analyzed the sentiment of tweets and found persistent differences among conferences.It also shows that some communities consistently express messages with higher levels of emotions while others do it in amore neutral manner. Finally, we investigated some features that can help predict future user participation in the onlineTwitter conference activity. By casting the problem as a classification task, we created a model that identifies factors thatcontribute to the continuing user participation. Our results have implications for research communities to implementstrategies for continuous and active participation among members. Moreover, our work reveals the potential for the useof information shared on Twitter in order to facilitate communication and cooperation among research communities, byproviding visibility to new resources or researchers from relevant but often little known research communities.
2015

Offener Datensatz für Fallerkennung basierend auf Sensordaten mobiler Endgeräte

12th International Conference on Mobile and Ubiquitous Systems: Computing, Networking and Services, 2015

Journal
Fall detection is a classical use case for mobile phone sensing. Nonetheless, no open dataset exists that could be used to train, test and compare fall detection algorithms. We present a dataset for mobile phone sensing-based fall detection. The dataset contains both accelerometer and gyroscope data. Data were labelled with four types of falls (e.g., “stumbling”) and ten types of non-fall activities (e.g., “sit down”). The dataset was collected with martial artists who simulated falls. We used five different state-of-the-art Android smartphone models worn on the hip in a small bag. Due to the datasets properties of using multiple devices and being labelled with multiple fall- and non-fall categories, we argue that it is suitable to serve as benchmark dataset.
2015

Kraker Peter

Educational Technology as Seen Through the Eyes of the Readers

International Journal of Technology Enhanced Learning, Inderscience Publishers, 2015

Journal
In this paper, I present the evaluation of a novel knowledge domain visualization of educational technology. The interactive visualization is based on readership patterns in the online reference management system Mendeley. It comprises of 13 topic areas, spanning psychological, pedagogical, and methodological foundations, learning methods and technologies, and social and technological developments. The visualization was evaluated with (1) a qualitative comparison to knowledge domain visualizations based on citations, and (2) expert interviews. The results show that the co-readership visualization is a recent representation of pedagogical and psychological research in educational technology. Furthermore, the co-readership analysis covers more areas than comparable visualizations based on co-citation patterns. Areas related to computer science, however, are missing from the co-readership visualization and more research is needed to explore the interpretations of size and placement of research areas on the map.
2015

Mutlu Belgin, Veas Eduardo Enrique, Trattner Christoph

VizRec: Recommending Personalized Visualizations

ACM Transactions on Interactive Intelligent Systems (TiiS) - Special Issue on Human Interaction with Artificial Advice Givers, ACM, 2015

Journal
Visualizations have a distinctive advantage when dealing with the information overload problem: since theyare grounded in basic visual cognition, many people understand them. However, creating the appropriaterepresentation requires specific expertise of the domain and underlying data. Our quest in this paper is tostudy methods to suggest appropriate visualizations autonomously. To be appropriate, a visualization hasto follow studied guidelines to find and distinguish patterns visually, and encode data therein. Thus, a visu-alization tells a story of the underlying data; yet, to be appropriate, it has to clearly represent those aspectsof the data the viewer is interested in. Which aspects of a visualization are important to the viewer? Canwe capture and use those aspects to recommend visualizations? This paper investigates strategies to recom-mend visualizations considering different aspects of user preferences. A multi-dimensional scale is used toestimate aspects of quality for charts for collaborative filtering. Alternatively, tag vectors describing chartsare used to recommend potentially interesting charts based on content. Finally, a hybrid approach combinesinformation on what a chart is about (tags) and how good it is (ratings). We present the design principlesbehindVizRec, our visual recommender. We describe its architecture, the data acquisition approach with acrowd sourced study, and the analysis of strategies for visualization recommendation
2015

Tatzgern Markus, Grasset Raphael, Veas Eduardo Enrique, Schmalstieg Dieter

Exploring real world points of interest: Design and evaluation of object-centric exploration techniques for augmented reality

Pervasive and Mobile Computing, Elsevier, 2015

Journal
Augmented reality (AR) enables users to retrieve additional information about real world objects and locations. Exploring such location-based information in AR requires physical movement to different viewpoints, which may be tiring and even infeasible when viewpoints are out of reach. In this paper, we present object-centric exploration techniques for handheld AR that allow users to access information freely using a virtual copy metaphor. We focus on the design of techniques that allow the exploration of large real world objects. We evaluated our interfaces in a series of studies in controlled conditions and compared them to a 3D map interface, which is a more common method for accessing location-based information. Based on our findings, we put forward design recommendations that should be considered by future generations of location-based AR browsers, 3D tourist guides or situated urban planning.
2015

Buschmann Katrin, Kasberger Stefan, Mayer Katja, Reckling Falk, Rieck Katharina, Vignoli Michela, Kraker Peter

Open Science in Austria: Approaches and Status

Information. Wissenschaft und Praxis, DeGruyter, 2015

Journal
Insbesondere in den letzten zwei Jahren hat Österreichim Bereich Open Science, vor allem was Open Accessund Open Data betrifft, nennenswerte Fortschritte gemacht.Die Gründung des Open Access Networks Austria(OANA) und das Anfang 2014 gestartete Projekt e-InfrastructuresAustria können als wichtige Grundsteine fürden Ausbau einer österreichischen Open-Science-Landschaftgesehen werden. Auch das österreichische Kapitelder Open Knowledge Foundation leistet in den BereichenOpen Science Praxis- und Bewusstseinsbildung grundlegendeArbeit. Unter anderem bilden diese Initiativendie Grundlage für den Aufbau einer nationalen Open-Access-Strategie sowie einer ganz Österreich abdeckendenInfrastruktur für Open Access und Open (Research) Data.Dieser Beitrag gibt einen Überblick über diese und ähnlichenationale sowie lokale Open-Science-Projekte und-Initiativen und einen Ausblick in die mögliche Zukunftvon Open Science in Österreich.
2015

Kraker Peter, Lindstaedt Stefanie , Schlögl C., Jack K.

Visualization of co-readership patterns from an online reference management system

Journal of Informetrics, Elsevier, NULL, 2015

Journal
In this paper, we analyze the adequacy and applicability of readership statistics recorded in social reference management systems for creating knowledge domain visualizations. First, we investigate the distribution of subject areas in user libraries of educational technology researchers on Mendeley. The results show that around 69% of the publications in an average user library can be attributed to a single subject area. Then, we use co-readership patterns to map the field of educational technology. The resulting visualization prototype, based on the most read publications in this field on Mendeley, reveals 13 topic areas of educational technology research. The visualization is a recent representation of the field: 80% of the publications included were published within ten years of data collection. The characteristics of the readers, however, introduce certain biases to the visualization. Knowledge domain visualizations based on readership statistics are therefore multifaceted and timely, but it is important that the characteristics of the underlying sample are made transparent.
2015

Trattner Christoph, Steurer Michael

Detecting partnership in location-based and online social networks

Social Netw. Analys. Mining, Springer, 2015

Journal
Existing approaches to identify the tie strength between users involve typically only one type of network. To date, no studies exist that investigate the intensity of social relations and in particular partnership between users across social networks. To fill this gap in the literature, we studied over 50 social proximity features to detect the tie strength of users defined as partnership in two different types of networks: location-based and online social networks. We compared user pairs in terms of partners and non-partners and found significant differences between those users. Following these observations, we evaluated the social proximity of users via supervised and unsupervised learning approaches and establish that location-based social networks have a great potential for the identification of a partner relationship. In particular, we established that location-based social networks and correspondingly induced features based on events attended by users could identify partnership with 0.922 AUC, while online social network data had a classification power of 0.892 AUC. When utilizing data from both types of networks, a partnership could be identified to a great extent with 0.946 AUC. This article is relevant for engineers, researchers and teachers who are interested in social network analysis and mining.
2015

Lin Yi-ling, Trattner Christoph, Brusilovsky Peter , He Daqing

The impact of image descriptions on user tagging behavior: A study of the nature and functionality of crowdsourced tags

JASIST, Wiley, 2015

Journal
Crowdsourcing has been emerging to harvest social wisdom from thousands of volunteers to perform series of tasks online. However, little research has been devoted to exploring the impact of various factors such as the content of a resource or crowdsourcing interface design to user tagging behavior. While images’ titles and descriptions are frequently available in image digital libraries, it is not clear whether they should be displayed to crowdworkers engaged in tagging. This paper focuses on offering an insight to the curators of digital image libraries who face this dilemma by examining (i) how descriptions influence the user in his/her tagging behavior and (ii) how this relates to the (a) nature of the tags, (b) the emergent folksonomy, and (c) the findability of the images in the tagging system. We compared two different methods for collecting image tags from Amazon’s Mechanical Turk’s crowdworkers – with and without image descriptions. Several properties of generated tags were examined from different perspectives: diversity, specificity, reusability, quality, similarity, descriptiveness, etc. In addition, the study was carried out to examine the impact of image description on supporting users’ information seeking with a tag cloud interface. The results showed that the properties of tags are affected by the crowdsourcing approach. Tags from the “with description” condition are more diverse and more specific than tags from the “without description” condition, while the latter has a higher tag reuse rate. A user study also revealed that different tag sets provided different support for search. Tags produced “with description” shortened the path to the target results, while tags produced without description increased user success in the search task
2015

Kraker Peter, Schlögl C. , Jack K., Lindstaedt Stefanie

The Quest for Keeping an Overview: Knowledge Domain Visualizations based on Co-Readership Patterns

In: Science 2.0, IEEE Computer Society Special Technical Community on Social Networking E-Letter, vol. 3, no. 1, 2015

Journal
Given the enormous amount of scientific knowledgethat is produced each and every day, the need for better waysof gaining – and keeping – an overview of research fields isbecoming more and more apparent. In a recent paper publishedin the Journal of Informetrics [1], we analyze the adequacy andapplicability of readership statistics recorded in social referencemanagement systems for creating such overviews. First, weinvestigated the distribution of subject areas in user librariesof educational technology researchers on Mendeley. The resultsshow that around 69% of the publications in an average userlibrary can be attributed to a single subject area. Then, we usedco-readership patterns to map the field of educational technology.The resulting knowledge domain visualization, based on the mostread publications in this field on Mendeley, reveals 13 topicareas of educational technology research. The visualization isa recent representation of the field: 80% of the publicationsincluded were published within ten years of data collection. Thecharacteristics of the readers, however, introduce certain biasesto the visualization. Knowledge domain visualizations based onreadership statistics are therefore multifaceted and timely, but itis important that the characteristics of the underlying sample aremade transparent.
2015

Lex Elisabeth, Dennerlein Sebastian

HowTo: Scientific Work in Interdisciplinary and Distributed Teams

In: Science 2.0, IEEE Computer Society Special Technical Community on Social Networking E-Letter, vol. 3, no. 1, IEEE, 2015

Journal
Today's complex scientific problems often require interdisciplinary, team-oriented approaches: the expertise of researchers from different disciplines is needed to collaboratively reach a solution. Interdisciplinary teams yet face many challenges such as differences in research practice, terminology, communication , and in the usage of tools. In this paper, we therefore study concrete mechanisms and tools of two real-world scientific projects with the aim to examine their efficacy and influence on interdisciplinary teamwork. For our study, we draw upon Bronstein's model of interdisciplinary collaboration. We found that it is key to use suitable environments for communication and collaboration, especially when teams are geographically distributed. Plus, the willingness to share (domain) knowledge is not a given and requires strong common goals and incentives. Besides, structural barriers such as financial aspects can hinder interdisciplinary work, especially in applied, industry funded research. Furthermore, we observed a kind of cold-start problem in interdisciplinary collaboration, when there is no work history and when the disciplines are rather different, e.g. in terms of wording. HowTo: Scientific Work in Interdisciplinary and Distributed Teams (PDF Download Available). Available from: https://www.researchgate.net/publication/282813815_HowTo_Scientific_Work_in_Interdisciplinary_and_Distributed_Teams [accessed Jul 13, 2017].
2011

Pammer-Schindler Viktoria, Kump Barbara, Lindstaedt Stefanie

Tag-based algorithms can predict human ratings of which objects a picture shows

Multimedia Tools and Applications, Springer, 2011

Journal
2010

Ley Tobias, Kump Barbara, Albert D.

A Methodology for Eliciting, Modelling, and Evaluating Expert Knowledge for an Adaptive Work-integrated Learning System

International Journal of Human-Computer Studies, 2010

Journal
2010

Stocker A., Mueller J.

Enterprise Microblogging bei Siemens, Building Technologies Division

erscheint in: DOK Magazin, 2010

Journal
2010

Granitzer Michael, Sabol Vedran, Onn K., Lukose D.

Ontology Alignment - A Survey with Focus on Visually Supported Semi-Automatic Techniques

Future Internet, MDPI AG, 2010

Journal
2009

Thurner-Scheuerer Claudia

Thema des Monats: Die Plattform Wissensmanagement – ein Stern im Wissensmanagement-Orbit

Community of knowledge, Rollen - Koordinator WM, 2009

Journal
2009

Neidhart T., Granitzer Michael, Kern Roman, Weichselbraun A., Wohlgenannt G., Scharl A., Juffinger A.

Distributed Web2.0 Crawling for Ontology Evolution

Journal of Digital Information Management, 2009

Journal
2009

Lindstaedt Stefanie , Hambach S., Müsebeck P., de Hoog R., Kooken J., Musielak M.

Context and Scripts: Supporting Interactive Work-Integrated Learning

Computer Supported Collaboration Learning Practices, CSCL09, 8-13 June 2009, Rhodes, Greece, Dimitracopoulou A., O’Malley, C., Suthers D., Reimann P. , 2009

Journal
2009

Schachner W., Koubek A.

Bessere Unternehmen mit Wissensmanagement?

QZ Qualität und Zuverlässigkeit, 03/2009, Carl Hanser Verlag, München, 2009

Journal
2009

Gras R., Devaurs Didier, Wozniak A., Aspinall A.

An Individual-Based Evolving Predator-Prey Ecosystem Simulation Using a Fuzzy Cognitive Map as the Behavior Model

Artificial Life, Massachusetts Institute of Technology, 2009

Journal
We present an individual-based predator-prey model with, for the first time, each agent behavior being modeled by a fuzzy cognitive map (FCM), allowing the evolution of the agent behavior through the epochs of the simulation. The FCM enables the agent to evaluate its environment (e.g., distance to predator or prey, distance to potential breeding partner, distance to food, energy level) and its internal states (e.g., fear, hunger, curiosity), and to choose several possible actions such as evasion, eating, or breeding. The FCM of each individual is unique and is the result of the evolutionary process. The notion of species is also implemented in such a way that species emerge from the evolving population of agents. To our knowledge, our system is the only one that allows the modeling of links between behavior patterns and speciation. The simulation produces a lot of data, including number of individuals, level of energy by individual, choice of action, age of the individuals, and average FCM associated with each species. This study investigates patterns of macroevolutionary processes, such as the emergence of species in a simulated ecosystem, and proposes a general framework for the study of specific ecological problems such as invasive species and species diversity patterns. We present promising results showing coherent behaviors of the whole simulation with the emergence of strong correlation patterns also observed in existing ecosystems.
2008

Granitzer Gisela, Höfler Patrick

Learning With Social Semantic Technologies - Exploiting Latest Tools

International Journal of Emerging Technologies in Learning (iJET), Vol 3, 2008

Journal
Even though it was only about three years ago that Social Software became a trend, it has become a common practice to utilize Social Software in learning institutions. It brought about a lot of advantages, but also challenges. Amounts of distributed and often unstructured user generated content make it difficult to meaningfully process and find relevant information. According to the estimate of the authors, the solution lies in underpinning Social Software with structure resulting in Social Semantic Software. In this contribution we introduce the central concepts Social Software, Semantic Web and Social Semantic Web and show how Social Semantic Technologies might be utilized in the higher education context.
2008

Lex Elisabeth, Kienreich Wolfgang, Granitzer Michael, Seifert C.

A generic framework for visualizing the news article domain and its application to real-world data

Journal of Digital Information Management, 2008

Journal
2007

Lokaiczyk R., Godehardt E., Faatz A., Goertz M., Kienle A., Wessner M., Ulbrich Armin

Exploiting Context Information for Identification of Relevant Experts in Collaborative Workplace-Embedded E-Learning Environments

Creating New Learning Experiences on a Global Scale (LNCS, Volume 4753), Duval, E., Klamma, R., Wolpers, M., Springer, Heidelberg, 2007

Journal
2007

Rollett H., Lux M., Strohmaier M., Dösinger G.

The Web 2.0 Way of Learning with Technologies

International Journal of Learning Technology, Vol. 3, Issue 1, 2007, Inderscience Publishers, 2007

Journal
While there is a lot of hype around various concepts associated with the term Web 2.0 in industry, little academic research has so far been conducted on the implications of this new approach for the domain of education. Much of what goes by the name of Web 2.0 can, in fact, be regarded as new kinds of learning technologies, and can be utilised as such. This paper explains the background of Web 2.0, investigates the implications for knowledge transfer in general, and then discusses its particular use in eLearning contexts with the help of short scenarios. The main challenge in the future will be to maintain essential Web 2.0 attributes, such as trust, openness, voluntariness and self-organisation, when applying Web 2.0 tools in institutional contexts.
2007

Lux M.

From Folksonomies to Ontologies: Employing Wisdom of the Crowds to Serve Learning Purposes

International Journal for Knowledge & Learning IJKL, 3(4), 2007, 2007

Journal
Is Web 2.0 just hype or just a buzzword, which might disappear in the near future? One way to find answers to these questions is to investigate the actual benefit of the Web 2.0 for real use cases. Within this contribution we study a very special aspect of the Web 2.0 ? the folksonomy ? and its use within self-directed learning. Guided by conceptual principles of emergent computing we point out methods, which might be able to let semantics emerge from folksonomies and discuss the effect of the results in self-directed learning.
2007

Kooken J., Ley Tobias, de Hoog R.

How Do People Learn at the Workplace? Investigating Four Workplace Learning Assumptions

in: Duval, E., Klamma, R., Wolpers, M. (Eds.), Creating New Learning Experiences on a Global Scale (LNCS, Volume 4753), Springer, Heidelberg, 2007

Journal
Any software development project is based on assumptions about the state of the world that probably will hold when it is fielded. Investigating whether they are true can be seen as an important task. This paper describes how an empirical investigation was designed and conducted for the EU funded APOSDLE project. This project aims at supporting informal learning during work. Four basic assumptions are derived from the project plan and subsequently investigated in a two-phase study using several methods, including workplace observations and a survey. The results show that most of the assumptions are valid in the current work context of knowledge workers. In addition more specific suggestions for the design of the prospective APOSDLE application could be derived. Though requiring a substantial effort, carrying out studies like this can be seen as important for longer term software development projects.
2006

Burgsteiner H., Kröll Mark, Leopold A., Steinbauer G.

Movement Prediction From Real-World Images Using A Liquid State Machine

Journal of Applied Intelligence, Springer, 2006

Journal
2005

Strohmaier M.

The B-KIDE Framework and Tool for Business Process Oriented Knowledge Infrastructure Development

Journal of Knowledge and Process Management, John Wiley & Sons, 2005

Journal
2005

Timbrell G., Koller S., Schefe N., Lindstaedt Stefanie

A Knowledge Infrastructure Hierarchy Model for Call-Centre Processes

Journal of Universal Computer Science, 2005

Journal
2004

Dösinger G., Gissing B.

Know how to share and transfer Know-how

Proceedings des 18. Symposiums Environmental Informatics – Knowledge Sharing, Genf, Schweiz, 2004

Journal
2004

Lindstaedt Stefanie , Farmer J.

'Kooperatives Lernen in Organisationen' in 'CSCL-Kompendium - Lehr- und Handbuch für das computerunterstützte kooperative Lernen'

Oldenbourg Wissenschaftsverlag, Haake, J., Schwabe, G., Wessner, M., München,Germany, 2004

Journal
2004

Dösinger G.

Trendanalyse Wissensmanagement: Orientierungshilfen für Praxisprojekte von morgen

wissensmanagement - Das Magazin für Führungskräfte, 2004

Journal
2004

Maurer H.

Das Know-Center und die neue Fakultät für Informatik an der TU Graz

Zeitschrift TELEMATIK 04/2004, Schwerpunktheft, Graz, Austria, 2004

Journal
2004

Maurer H.

Wie Wissen wirklich wirkt

Austria Innovativ, Ausgabe 1/2004, 2004

Journal
2003

Kienreich Wolfgang, Sabol Vedran, Granitzer Michael, Becker J.

Themenkarten als Ergänzung zu hierarchiebasierter Navigation und Suche in Wissensmanagementsystemen

4. Oldenburger Forum Wissensmanagement, Oldenburg, Germany, 2003

Journal
2003

Ley Tobias, Albert D.

JUCS Special Issue: Skills Management - Managing Competencies in the Knowledg-based Economy

Journal of Universal Computer Science, Special Issue, Springer, 2003

Journal
2003

Clancy J.M. , Elliott G., Ley Tobias, Odomei M.M., Wearing A.J., McLennan J., Thorsteinsson E.B.

Command Style and Team Performance in Dynamic Decision-Making Tasks

In: S. L. Schneider and J. Shanteau (Eds.). Emerging Perspectives on Judgment and Decision Research, S. L. Schneider & J. Shanteau, Cambridge University Press, 2003

Journal
2003

Ley Tobias, Albert D.

Identifying Employee Competencies in Dynamic Work Domains: Methodological Considerations and a Case Study

Journal of Universal Computer Science, Special Issue, Springer Verlag, 2003

Journal
We present a formalisation for employee competencies which is based on a psychological framework separating the overt behavioural level from the underlying competence level. On the competence level, employees draw on action potentials (knowledge, skills and abilities) which in a given situation produce performance outcomes on the behavioural level. Our conception is based on the competence performance approach by [Korossy 1997] and [Korossy 1999] which uses mathematical structures to establish prerequisite relations on the competence and the performance level. From this framework, a methodology for assessing competencies in dynamic work domains is developed which utilises documents employees have created to assess the competencies they have been acquiring. By means of a case study, we show how the methodology and the resulting structures can be validated in an organisational setting. From the resulting structures, employee competency profiles can be derived and development planning can be supported. The structures also provide the means for making inferences within the competency assessment process which in turn facilitates continuous updating of competency profiles and maintenance of the structures.
2003

Ley Tobias, Albert D.

Kompetenzmanagement als formalisierbare Abbildung von Wissen und Handeln für das Personalwesen

Wissensmanagement – psychologische Perspektiven und Redefinitionen. Wirtschaftspsychologie Themenheft, 5, 3, Wehner, T., Dick, M., Pabst Science Publishers, 2003

Journal
2002

Lux M., Klieber Hans-Werner, Becker J., Mayer H., Neuschmied H., Haas W.

XML and MPEG-7 for Interactive Annotation and Retrieval Using Semantic Meta-data

IICM, JUCS online, Graz, Austria, 2002

Journal
The evolution of the Web is not only accompanied by an increasing diversity of multimedia but by new requirements towards intelligent research capabilities, user specific assistance, intuitive user interfaces and platform independent information presentation. To reach these and further upcoming requirements new standardized Web technologies and XML based description languages are used. The Web Information Space has transformed into a Knowledge marketplace where worldwide located participants take part into the creation, annotation and consumption of knowledge. This paper points out the design of semantic retrieval frameworks and a prototype implementation for audio and video annotation, storage and retrieval using the MPEG-7 standard and semantic web reference implementations. MPEG-7 plays an important role towards the standardized enrichment of multimedia with semantics on higher abstraction levels and a related improvement of query results.
2002

AeI - A Smooth Integration of eLearning into Traditional Teaching Concepts

Poster/Demo at ED-Media, Association for the Advancement of Computing in Education (AACE), Denver,USA, 2002

Journal
2002

Environmental Information Systems

Encyclopedia of Environmetrics, El-Shaarawi, A., Piegorsch, W., John Wiley & Sons, 2002

Journal
2002

Lindstaedt Stefanie , Scheir Peter, Sarka W.

Generic Knowledge Management System (GKMS)

TELEMATIK 03/2002, Telematik Ingenieur Verband, Graz, Austria, 2002

Journal
2002

Lindstaedt Stefanie

Integration von Arbeits- und Lernprozessen

Fachtagung der Senatsverwaltung für Wirtschaft, Arbeit und Frauen, Berlin, am 21./22. November 2002, BBJ-Verlag, Berlin, Germany, 2002

Journal
2002

Becker J., Lux M., Klieber Hans-Werner

Intelligente Multimedia Bibliothek

to be Published in TELEMATIK 03/2002, Telematik Ingenieur Verband, Graz, Austria, 2002

Journal
2002

Becker J., Lux M., Klieber Hans-Werner, Sabol Vedran, Kienreich Wolfgang

Knowledge Discovery Space

to be Published in TELEMATIK 03/2002, Telematik Ingenieur Verband, Graz, Austria, 2002

Journal
2002

Lux M., Klieber Hans-Werner, Becker J., Mayer H., Neuschmied H., Haas W.

XML and MPEG-7 for Interactive Annotation and Retrieval Using Semantic Metadata

Journal of Computer Science (www.jucs.org), Springer-Verlag, 2002

Journal
2002

Maurer H.

People-Oriented Knowledge Management

Special Issue Journal of Universal Computer Science, Springer Verlag, Vol. 8 , No. 5, 2002, 2002

Journal
2002

Maurer H.

Technology-Oriented Knowledge Management

Special Issue Journal of Universal Computer Science, Springer Verlag 2002, 2002

Journal
2002

Andrews K., Kienreich Wolfgang, Sabol Vedran, Becker J., Kappe F., Droschl G., Granitzer Michael, Auer P.

The InfoSky Visual Explorer: Exploiting Hierarchical Structure and Document Similarities

Information Visulization, Palgrave Journals, London, England, 2002

Journal
2002

Becker J., Granitzer Michael, Kienreich Wolfgang, Sabol Vedran

WebRat

to be Published in TELEMATIK 03/2002, Telematik Ingenieur Verband, Graz, Austria, 2002

Journal
2002

Dösinger G., Ley Tobias

Wissensbilanzen als ein Instrument zum Management Intellektuellen Kapitals

TELEMATIK 03/2002, Telematik Ingenieur Verband, Graz, Austria, 2002

Journal
2002

Environmental Informatics

Encyclopedia of Environmetrics, El-Shaarawi, A., Piegorsch, W., John Wiley & Sons, 2002

Journal
2001

Ulbrich Armin, Ausserhofer A., Dietinger T., Raback W., Hoitsch P.

Requirements Analysis and Evaluation of Streaming Technologies with Respect to Interaction in Multimedia E-Learning Courses

WebNet 2001, 2001

Journal
2001

Lindstaedt Stefanie

Web Globalization: Vision, Strategie

www.ContentManager.de, 2001

Journal

Clemens Bloechl, Rana Ali Amjad, Geiger Bernhard

Co-Clustering via Information-Theoretic Markov Aggregation

IEEE TRANSACTIONS ON KNOWLEDGE AND DATA ENGINEERING, IEEE

Journal
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