Publikationen

Hier finden Sie von Know-Center MitarbeiterInnen verfasste wissenschaftliche Publikationen

2014

Dennerlein Sebastian, Cook John, Kravcik Milos, Kunzmann Christine, Pata Kai, Purma Jukka, Sandars John, Santos Patricia , Schmidt Andreas, Al-Smadi Mohammad, Trattner Christoph, Ley Tobias

Scaling informal learning at the workplace: A model and four designs from a large‐scale design‐based research effort

British Journal of Educational Technology, 2014

Workplace learning happens in the process and context of work, is multi-episodic, often informal, problem based and takes place on a just-in-time basis. While this is a very effective means of delivery, it also does not scale very well beyond the immediate context. We review three types of technologies that have been suggested to scale learning and three connected theoretical discourses around learning and its support. Based on these three strands and an in-depth contextual inquiry into two workplace learning domains, health care and building and construction, four design-based research projects were conducted that have given rise to designs for scaling informal learning with technology. The insights gained from the design and contextual inquiry contributed to a model that provides an integrative view on three informal learning processes at work and how they can be supported with technology: (1) task performance, reflection and sensemaking; (2) help seeking, guidance and support; and (3) emergence and maturing of collective knowledge. The model fosters our understanding of how informal learning can be scaled and how an orchestrated set of technologies can support this process.
2014

Discovery and Visual Analysis of Linked Data for Humans

The Semantic Web – ISWC 2014, Lecture Notes in Computer Science Volume 8796, Springer International Publishing, 2014

2014

5th International Workshop on Modeling Social Media: Mining Big Data in Social Media and the Web (MSM 2014)

In Proceedings of the ACM World Wide Web Conference, ACM, 2014

Konferenz
2014

What Really Works: Reflections on Applied Methods in a Real World Interdisciplinary Project

Proceedings of the Interdisciplinary Coups to Calamities Workshop at ACM Web Science 2014, 2014

Today's data driven world requires interdisciplinary, team-oriented approaches: experts from di fferent disciplines are needed to collaboratively solve complex real-world problems. Interdisciplinary teams face a set of challenges that are not necessarily encountered by unidisciplinary teams, such as organisational culture, mental and nancial barriers. We share our experiences with interdisciplinary teamwork based on a real-world example. We found that models of interdisciplinary teamwork from Social Sciences and Web Science can guide interdisciplinary teamwork in the domain of pharmaceutical knowledge management. Additionally, we identified potential extensions of the models' components as well as novel influencing factors such the willingness to explicate and share domain knowledge.
2014

ProS 2014: Workshop on UMAP Projects Synergy

Workshop Proceedings of the 22nd Conference on User Modeling, Adaptation, and Personalization, CEUR.WS, 2014

Konferenz
2014

Sinn aus "Bits & Pieces" gewinnen: Ein Sensemaking-Tool für informelles Lernen am Arbeitsplatz

in press, 2014

Sensemaking at the workplace and in educational contexts has been extensively studied for decades. Interestingly, making sense out of the own wealth of learning experiences at the workplace has been widely ignored. To tackle this issue, we have implemented a novel sensemaking interface for healthcare professionals to support learning at the workplace. The proposed prototype supports remembering of informal experiences from episodic memory followed by sensemaking in semantic memory. Results from an initial study conducted as part of an iterative co-design process reveal the prototype is being perceived as useful and supportive for informal sensemaking by study participants from the healthcare domain. Furthermore, we find first evidence that re-evaluation of collected information is a potentially necessary process that needs further exploration to fully understand and support sensemaking of informal learning experiences.
2014

A Study of Scientific Writing: Comparing Theoretical Guidelines with Practical Implementation

COLING Workshop on Synchronic and Diachronic Approaches to Analyzing Technical Language, 2014

Good scientific writing is a skill researchers seek to acquire. Textbook literature provides guidelines to improve scientific writing, for instance, "use active voice when describing your own work". In this paper we investigate to what extent researchers adhere to textbook principles in their articles. In our analyses we examine a set of selected principles which (i) are general and (ii) verifiable by applying text mining and natural language processing. We develop a framework to automatically analyse a large data set containing ~14.000 scientific articles received from Mendeley and PubMed. We are interested in whether adhering to writing principles is related to scientific quality, scientific domain or gender and whether these relations change over time. Our results show (i) a clear relation between journal quality and scientific imprecision, i.e. journals with low impact factors exhibit higher numbers of imprecision indicators such as #citation bunches and #relativating words and (ii) that writing style partly depends on domain characteristics and preferences.
2014

Altmetrics-based Visualizations Depicting the Evolution of a Knowledge Domain

19th International Conference on Science and Technology Inidicators (STI 2014), 2014

2014

Recommending Items in Social Tagging Systems Using Tag and Time Information

In Proceedings of the 1st Social Personalization Workshop co-located with the 25th ACM Conference on Hypertext and Social Media (HT 2014), ACM, 2014

In this work we present a novel item recommendation approach that aims at improving Collaborative Filtering (CF) in social tagging systems using the information about tags and time. Our algorithm follows a two-step approach, where in the first step a potentially interesting candidate item-set is found using user-based CF and in the second step this candidate item-set is ranked using item-based CF. Within this ranking step we integrate the information of tag usage and time using the Base-Level Learning (BLL) equation coming from human memory theory that is used to determine the reuse-probability of words and tags using a power-law forgetting function. As the results of our extensive evaluation conducted on datasets gathered from three social tagging systems (BibSonomy, CiteULike and MovieLens) show, the usage of tag-based and time information via the BLL equation also helps to improve the ranking and recommendation process of items and thus, can be used to realize an effective item recommender that outperforms two alternative algorithms which also exploit time and tag-based information.
2014

Comparison of downloads, citations and readership data for two information systems journals

Scientometrics, 2014

Konferenz
In our article we compare downloads from ScienceDirect, citations from Scopus and readership data from the social reference management system Mendeley for articles from two information systems journals ("Journal of Strategic Information Systems" and "Information and Management") Published between 2002 and 2011. Our study shows a medium to high correlation between downloads and citations (Spearman r = 0.77/ 0.76) and between downloads and readership data (Spearman r = 0.73/0.66). The correlation between readership data and citations, however, was only medium-sized (Spearman r = 0.51/0.59). These results suggest that there is at least "some" difference between the two usage measures and the citation impact of the analysed information systems articles. As expected, downloads and citations have different obsolescence characteristics. While the highest number of downloads are usually made in the publication year and immediately afterwards, it takes several years until the citation maximum is reached. Furthermore, there was a re-increase in the downloads in later years which might be an indication that citations also have an effect on downloads to some degree.
2014

Towards a Marketplace for the Scientific Community: Accessing Knowledge from the Computer Science Domain

International Workshop on Mining Scientific Publications @ Digital Libraries, 2014

As scientific output is constantly growing, it is getting more and more important to keep track not only for researchers but also for other scientific stakeholders such as funding agencies or research companies. Each stakeholder values different types of information. A funding agency, for instance, might be rather interested in the number of publications funded by their grants. However, information extraction approaches tend to be rather researcher-centric indicated, for example, by the type of named entities to be recognized. In this paper we account for different perspectives and propose an ontological description of one scientific domain – the computer science domain. We accordingly annotated a set of 22 computer science papers by hand and make this data set publicly available. In addition, we started to apply methods to automatically extract instances and report preliminary results. Automating the population process represents a prerequisite for our vision of a “Marketplace for the Scientific Community” where stakeholders can exchange not only information but also search concepts or annotated data.
2014

Applikations übergreifende User Profile um reflektives Lernen während der Arbeit zu unterstützen

Proceedings of the 4th Workshop on Awareness and Reflection in Technology-Enhanced Learning (ARTEL 2014 ), EC-TEL 2014, Graz, Austria, M. Kravcik, A. Mikroyannidis, V. Pammer, M. Prilla, T. Ullman, F. Wild, 2014

Reflective learning is an important activity of knowledge workers in order to improve future working-behaviours. The insights gained by reflective learning are based on re-experiencing and re-evaluating past working situations. One time- and cost-eff ective way to support reflective learning is the employment of applications that collect data about working processes, store the data in user profi les, and visualise it in order to provide timely feedback to the employees. However, a single application can only capture part of the data that might be relevant for reflection and the parallel use of several applications leads to high demands on the user regarding the interpretation of relationships between several single visualizations. A combined visualisation of data captured by diff erent apps should enhance the support for reflection about the working behaviour and experiences. This paper introduces an overlapping user profi le application, which combines and aggregates data captured by various applications. The goal of this overlapping application is to provide higher-level reflection possibilities by combining visualisations of di fferent application data in order to better induce and upport reflective learning at work. A first proof-of-concept of such an approach indicates that a combined user profi le application and especially it's visualisations can be bene ficial with regard to reflective learning and can enhance the awareness about the multiple aspects of a user's work life.
2014

Proceedings of the 4th Workshop on Awareness and Reflection in Technology-Enhanced Learning In conjunction with the 9th European Conference on Technology Enhanced Learning: Open Learning and Teaching in Educational Communities, ARTEL@EC-TEL 2014, Graz,

CEUR Workshop Proceedings, 2014

Konferenz
2014

Awareness and reflection in technology enhanced learning (Editorial)

Proceedings of the 4th Workshop on Awareness and Reflection in Technology Enhanced Learning. In conjunction with the 9th European Conference on Technology Enhanced Learning: Open Learning and Teaching in Educational Communities. Graz, Austria, September 1, CEUR Workshop Proceedings, 2014

2014

Using Semantics for Interactive Visual Analysis of Linked Open Data

CEUR Workshop Proceedings (CEUR-WS.org) Vol-1272, 2014

Providing easy to use methods for visual analysis of Linked Data is often hindered by the complexity of semantic technologies. On the other hand, semantic information inherent to Linked Data provides opportunities to support the user in interactively analysing the data. This paper provides a demonstration of an interactive, Web-based visualisation tool, the "Vis Wizard", which makes use of semantics to simplify the process of setting up visualisations, transforming the data and, most importantly, interactively analysing multiple datasets using brushing and linking methods.
2014

Tag Clouds

In Encyclopedia of Social Network Analysis and Mining, Springer, 2014

Journal
2014

A Comparison of Two Unsupervised Table Recognition Methods from Digital Scientific Articles

3rd International Workshop on Mining Scientific Publications, 2014

In digital scientific articles tables are a common form of presenting information in a structured way. However, the large variability of table layouts and the lack of structural information in digital document formats pose significant challenges for information retrieval and related tasks. In this paper we present two table recognition methods based on unsupervised learning techniques and heuristics which automatically detect both the location and the structure of tables within a article stored as PDF. For both algorithms the table region detection first identifies the bounding boxes of individual tables from a set of labelled text blocks. In the second step, two different tabular structure detection methods extract a rectangular grid of table cells from the set of words contained in these table regions. We evaluate each stage of the algorithms separately and compare performance values on two data sets from different domains. We find that the table recognition performance is in line with state-of-the-art commercial systems and generalises to the non-scientific domain.
2014

A comparison of citations, downloads and readership data for an information systems journal

Research Trends, 2014

Konferenz
2014

Download vs. Citation vs. Readership Data: The Case of an Information Systems Journal

14th International Society of Scientometrics and Informetrics Conference, 2014

2014

Scaling the support for informal learning at the workplace: a model and four designs from a large-scale design-based research effort

British Journal of Educational Technology, Wiley - Oxford, 2014

Konferenz
Workplace learning happens in the process and context of work, is multi-episodic, often informal, problem based and takes place on a just-in-time basis. While this is a very effective means of delivery, it also does not scale very well beyond the immediate context. We review three types of technologies that have been suggested to scale learning and three connected theoretical discourses around learning and its support. Based on these three strands and an in-depth contextual inquiry into two workplace learning domains, health care and building and construction, four design-based research projects were conducted that have given rise to designs for scaling informal learning with technology. The insights gained from the design and contextual inquiry contributed to a model that provides an integrative view on three informal learning processes at work and how they can be supported with technology: (1) task performance, reflection and sensemaking; (2) help seeking, guidance and support; and (3) emergence and maturing of collective knowledge. The model fosters our understanding of how informal learning can be scaled and how an orchestrated set of technologies can support this process.
2014

Graph Visualization using Hierarchical Aggregation and Edge Bundling

WebSci'14 Poster Session, 2014

Journal
2014

Future Directions for Visualisation

Envisioning Visualisation Without Desktop Computing Workshop (co-located with IEEE VIS 2014), 2014

2014

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

Pervasive and Mobile Computing, Elsevier, 2014

Konferenz
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 allows 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.
2014

Automatic Summarization for Terminology Recommendation: the case of the NCBO Ontology Recommender

International SWAT4LS Workshop, 2014

2014

Is enterprise search useful at all?: lessons learned from studying user behavior

i-KNOW '14 Proceedings of the 14th International Conference on Knowledge Technologies and Data-driven Business , 2014

2014

My Places Diary – Automatic Place and Transportation- Mode Detection

Proceedings of the 11th International Conference on Mobile and Ubiquitous Systems: Computing, Networking and Services , ICST (Institute for Computer Sciences, Social-Informatics and Telecommunications Engineering) , 2014

Play, that tracks places and movements of users throughout the day. It includes two innovative features: Firstly users’ home and workplaces are detected automatically, based on heuristics derived from earlier work on automatic semantic place detection. Additional place labels are provided via open geo data sources. The position is determined by using a low power positioning method while preserving sufficient accuracy for place detection. Secondly modes of transportation between places (walking, driving, biking) are derived based on Google’s activity recognition module. Combining these two features makes My Places Diary an automatically created diary of places and transitions between them. All computations are executed directly on the mobile phone.
2014

{{citation needed}}: Filling in Wikipedia’s Citation Shaped Holes

Bibliometric-enhanced Information Retrieval @ ECIR European conference on Information Retireval, 2014

Wikipedia authors cite external references to support claims made in their articles in order to increase their validity. A large number of claims, however, do not have supporting citations, putting them in question. In this paper, we describe a study in which we attempt to retrieve relevant citations for claims using a variety of information retrieval algorithms. These algorithms are inspired by bibliometric and altmetric insights that exploit readership data from Mendeley’s community and rerank results using a Bradfordising approach. The results of the small scale study indicate that both of these approaches can improve upon basic keyword-based search, typically used in digital libraries, in order to return relevant documents for unsupported claims.
2014

Towards a mobile sensor framework including EEG sensors

Sixth International BCI Conference 2014, 2014

Journal
Ubiquitous sensing is gaining increased attention, mostly in the form of mobile phone sensing, as the number of smartphone users is rapidly growing all over the world. Current smartphones are equipped with several powerful sensors (such as accelerometers, GPS sensors, and microphones), which allow for tracking user activities in a wide range of situations [1]. In addition, external sensors such as heart rate monitors or smartwatches (which are typically used in healthcare and fitness settings) can be integrated to augment the available information about the smartphone users throughout their daily lives. So far, EEG sensors have not been widely used in ubiquitous personal sensing frameworks. One of the reasons is that comfortable and reliable EEG sensors are not yet readily available as consumer devices. However, analyzing biosignals (in particular EEG signals) in combination with other mobile sensors opens up new application scenarios in healthcare, education, gaming, and workplace environments. For instance, estimating the mental state of a person with EEG sensors (e.g. cognitive load [2]) might be used to adapt the current computer environment accordingly, such as by minimizing distractions or adapting the complexity of a user interface. However, there are challenges in combining biosensors with existing mobile phone sensors, which include data processing issues (EEG signals are continuous and the timing is critical), portability of EEG devices, data fusion, power consumption, privacy, and security. We review scenarios in which EEG sensors as part of ubiquitous personal sensing frameworks create an added benefit for users. We also discuss technological challenges that need to be addressed to implement such scenarios. Some of those challenges are already addressed by existing ubiquitous sensing frameworks, though rarely all in one. It is important that architectures are tuned to the intended usage scenario. Therefore, we review specific requirements and propose an adequate architectural solution.
2014

Continuous learning with a quiz for stroke nurses

Int. J. Technology Enhanced Learning, Dr. Ambjörn Naeve, Interscience Publishers, 2014

Konferenz
A continuous learning solution was sought which allows stroke nurses to keep the vast body of theoretical knowledge fresh, stay up-to-date with new knowledge, and relate theoretical knowledge to practical experience. Based on the theoretical background of learning in the medical domain, reflective and game-based learning, we carried out a user-oriented design process that involved a focus group and a design workshop. In this process, a quiz that includes both content-based and reflection questions was identified as a viable means of transportation for theoretical knowledge. In this paper we present the result of trialling a quiz with both content-based and metacognitive (reflective) questions in two settings: In one trial the quiz was used by nurses as part of a qualification programme for stroke nurses, in the second trial by nurses outside such a formal continuous learning setting. Both trials were successful in terms of user acceptance, user satisfaction and learning. Beyond this success report, we discuss barriers to integrating a quiz into work processes within an emergency ward such as a stroke unit.
2014

The Impact of Image Descriptions on User Tagging Behavior: A Study of the Nature and Functionality of Crowdsourced Tags

Journal of the Association for Information Science and Technology, Wiley, 2014

Konferenz
2014

Twitter in Academic Conferences: Usage, Networking and Participation over Time

In Proceedings of the 25th ACM Conference on Hypertext and Social Media, ACM, 2014

2014

Lex Elisabeth, Kraker Peter, Dennerlein Sebastian

What Really Works: Reflections on Applied Methods in a Real World Interdisciplinary Project

Interdisciplinary Coups to Calamities Workshop at ACM Web Science, 2014

Today’s data driven world requires interdisciplinary, teamoriented approaches: experts from different disciplines are needed to collaboratively solve complex real-world problems. Interdisciplinary teams face a set of challenges that are not necessarily encountered by unidisciplinary teams, such as organisational culture, mental and financial barriers. We share our experiences with interdisciplinary teamwork based on a real-world example. We found that models of interdisciplinary teamwork from Social Sciences and Web Science can guide interdisciplinary teamwork in the domain of pharmaceutical knowledge management. Additionally, we identified potential extensions of the models’ components as well as novel influencing factors such the willingness to explicate and share domain knowledge.
2014

CODE Query Wizard and Vis Wizard: Supporting Exploration and Analysis of Linked Data

ERCIM News, 2014

Konferenz
Although the concept of Linked Data has been increasing in popularity, easy-to-use interfaces to access and make sense of the actual data are still few and far between. The CODE project's Query Wizard and Vis Wizard aim to fill this gap.
2014

Ullrich Torsten, Silva Nelson, Eggeling Eva, Fellner Dieter W.

Generative Modeling and Numerical Optimization for Energy Efficient Buildings (3)

Selected Readings in Computer Graphics , 2014

Buch
2014

Silva Nelson, Settgast Volker, Eggeling Eva, Grill Florian, Zeh Theodor, Fellner Dieter W.

Sixth Sense - Air Traffic Control Prediction Scenario Augmented by Sensors

I-Know 2014, 2014

Konferenz
2014

Silva Nelson

The Sixth Sense in Air Traffic Control - Automated error detection through sensor augmentation, while keeping the humans in the main decision loop of ATC

I-Know 2014, 2014

Konferenz
2014

Silva Nelson

The Sixth Sense of an Air Traffic Controller - Increasing Fault Tolerance of Human Machine Interfaces

SID 2014, 2014

Konferenz
2014

Mutlu Belgin, Tschinkel Gerwald, Veas Eduardo Enrique, Sabol Vedran, Stegmaier Florian, Granitzer Michael

Suggesting visualisations for published data

Information Visualization Theory and Applications (IVAPP), 2014 International Conference on, IEEE, 2014

Konferenz
Research papers are published in various digital libraries, which deploy their own meta-models and tech-nologies to manage, query, and analyze scientific facts therein. Commonly they only consider the meta-dataprovided with each article, but not the contents. Hence, reaching into the contents of publications is inherentlya tedious task. On top of that, scientific data within publications are hardcoded in a fixed format (e.g. tables).So, even if one manages to get a glimpse of the data published in digital libraries, it is close to impossibleto carry out any analysis on them other than what was intended by the authors. More effective querying andanalysis methods are required to better understand scientific facts. In this paper, we present the web-basedCODE Visualisation Wizard, which provides visual analysis of scientific facts with emphasis on automatingthe visualisation process, and present an experiment of its application. We also present the entire analyticalprocess and the corresponding tool chain, including components for extraction of scientific data from publica-tions, an easy to use user interface for querying RDF knowledge bases, and a tool for semantic annotation ofscientific data set
2014

Granitzer MIchael, Veas Eduardo Enrique, Seifert C.

Linked Data Query Wizard: A Novel Interface for Accessing SPARQL Endpoints.

LDOW, 2014

Konferenz
In an interconnected world, Linked Data is more importantthan ever before. However, it is still quite di cult to accessthis new wealth of semantic data directly without havingin-depth knowledge about SPARQL and related semantictechnologies. Also, most people are currently used to consumingdata as 2-dimensional tables. Linked Data is by de -nition always a graph, and not that many people are used tohandle data in graph structures. Therefore we present theLinked Data Query Wizard, a web-based tool for displaying,accessing, ltering, exploring, and navigating Linked Datastored in SPARQL endpoints. The main innovation of theinterface is that it turns the graph structure of Linked Datainto a tabular interface and provides easy-to-use interactionpossibilities by using metaphors and techniques from currentsearch engines and spreadsheet applications that regular webusers are already familiar with.
2014

Sabol Vedran, Tschinkel, Veas Eduardo Enrique, Mutlu Belgin, Granitzer Michael

Discovery and visual analysis of linked data for humans

International Semantic Web Conference, Springer, Cham, 2014

Konferenz
Linked Data has grown to become one of the largest availableknowledge bases. Unfortunately, this wealth of data remains inaccessi-ble to those without in-depth knowledge of semantic technologies. Wedescribe a toolchain enabling users without semantic technology back-ground to explore and visually analyse Linked Data. We demonstrateits applicability in scenarios involving data from the Linked Open DataCloud, and research data extracted from scientific publications. Our fo-cus is on the Web-based front-end consisting of querying and visuali-sation tools. The performed usability evaluations unveil mainly positiveresults confirming that the Query Wizard simplifies searching, refiningand transforming Linked Data and, in particular, that people using theVisualisation Wizard quickly learn to perform interactive analysis taskson the resulting Linked Data sets. In making Linked Data analysis ef-fectively accessible to the general public, our tool has been integratedin a number of live services where people use it to analyse, discover anddiscuss facts with Linked Data.
2014

Tschinkel Gerwald, Veas Eduardo Enrique, Mutlu Belgin, Sabol Vedran

Using semantics for interactive visual analysis of linked open data

Proceedings of the 2014 International Conference on Posters & Demonstrations Track-Volume 1272, CEUR-WS. org, 2014

Konferenz
Providing easy to use methods for visual analysis of LinkedData is often hindered by the complexity of semantic technologies. Onthe other hand, semantic information inherent to Linked Data providesopportunities to support the user in interactively analysing the data. Thispaper provides a demonstration of an interactive, Web-based visualisa-tion tool, the “Vis Wizard”, which makes use of semantics to simplify theprocess of setting up visualisations, transforming the data and, most im-portantly, interactively analysing multiple datasets using brushing andlinking method
2014

Rauch Manuela, Wozelka Ralph, Veas Eduardo Enrique, Sabol Vedran

Semantic Blossom Graph: A new Approach for Visual Graph Exploration

18th International Conference on Information Visualisation, IEEE Computer Society CPS, 2014

Konferenz
Graphs are widely used to represent relationshipsbetween entities. Indeed, their simplicity in depicting connect-edness backed by a mathematical formalism, make graphs anideal metaphor to convey relatedness between entities irrespec-tive of the domain. However, graphs pose several challenges forvisual analysis. A large number of entities or a densely con-nected set quickly render the graph unreadable due to clutter.Typed relationships leading to multigraphs cannot clearly berepresented in hierarchical layout or edge bundling, commonclutter reduction techniques. We propose a novel approach tovisual analysis of complex graphs based on two metaphors:semantic blossom and selective expansion. Instead of showingthe whole graph, we display only a small representative subsetof nodes, each with a compressed summary of relations in asemantic blossom. Users apply selective expansion to traversethe graph and discover the subset of interest. A preliminaryevaluation showed that our approach is intuitive and usefulfor graph exploration and provided insightful ideas for futureimprovements.
2014

Pammer-Schindler Viktoria, Simon Jörg Peter, Wilding Karin, Keller Stephan, Scherer Reinhold

Designing for Engaging BCI Training: A Jigsaw Puzzle

Proceedings of the 2015 Annual Symposium on Computer-Human Interaction in Play (CHI Play 2015), 2014

Konferenz
Brain-computer interface (BCI) technology translatesbrain activity to machine-intelligible patterns, thusserving as input “device” to computers. BCI traininggames make the process of acquiring training data forthe machine learning more engaging for the users. Inthis work, we discuss the design space for BCI traininggames based on existing literature, and a traininggame in form of a Jigsaw Puzzle. The game wastrialled with four cerebral palsy patients. All patientswere very acceptant of the involved technology, which,we argue, relates back to the concept of BCI traininggames plus the adaptations we made. On the otherhand, the data quality was unsatisfactory. Hence, infuture work both concept and implementation need tobe finetuned to achieve a balance between useracceptance and data quality.
2014

Visual Analysis and Knowledge Discovery for Text

Large-Scale Data Analytics, Springer, Aris Gkoulalas-Divanis, Abderrahim Labbi (eds., IBM Research), Springer, 2014

Journal
2014

Ley Tobias, Tammets Kairit, Lindstaedt Stefanie

Orchestrating Collaboration and Community Technologies for Individual and Organisational Learning

Technology Enhanced Professional Learning–Processes, Practices and Tools, Littlejohn, Allison; Margaryan, Anoush, Routledge, 2014

Buch
2014

Suggesting Visualisations for Published Data

Proceedings of the 5th International Conference on Information Visualization Theory and Applications (IVAPP 2014), 2014

Research papers are Published in various digital libraries, which deploy their own meta-models and tech- nologies to manage, query, and analyze scientific facts therein. Commonly they only consider the meta-data provided with each article, but not the contents. Hence, reaching into the contents of publications is inherently a tedious task. On top of that, scientific data within publications are hardcoded in a fixed format (e.g. tables). So, even if one manages to get a glimpse of the data Published in digital libraries, it is close to impossible to carry out any analysis on them other than what was intended by the authors. More effective querying and analysis methods are required to better understand scientific facts. In this paper, we present the web-based CODE Visualisation Wizard, which provides visual analysis of scientific facts with emphasis on automating the visualisation process, and present an experiment of its application. We also present the entire analytical process and the corresponding tool chain, including components for extraction of scientific data from publica- tions, an easy to use user interface for querying RDF knowledge bases, and a tool for semantic annotation of scientific data sets.
2014

Linked Data Query Wizard: A Novel Interface for Accessing SPARQL Endpoints

Proceedings of Linked Data on the Web (LDOW) @ WWW 2014, 2014

In an interconnected world, Linked Data is more important than ever before. However, it is still quite difficult to access this new wealth of semantic data directly without having in-depth knowledge about SPARQL and related semantic technologies. Also, most people are currently used to consuming data as 2-dimensional tables. Linked Data is by definition always a graph, and not that many people are used to handle data in graph structures. Therefore we present the Linked Data Query Wizard, a web-based tool for displaying, accessing, filtering, exploring, and navigating Linked Data stored in SPARQL endpoints. The main innovation of the interface is that it turns the graph structure of Linked Data into a tabular interface and provides easy-to-use interaction possibilities by using metaphors and techniques from current search engines and spreadsheet applications that regular web users are already familiar with.
2014

User Controllability in an Hybrid Talk Recommender System

In Proceedings of the ACM 2014 International Conference on Intelligent User Interfaces, ACM, 2014

2014

Virtuelle AAL Assistenz in der Laienpflege; eine (kritische) technik- und sozialwissenschaftliche Fallanalyse des Projekts DALIA

Assistenztechnik für betreutes Wohnen - Beiträge zum Usability Day XII, G. Kempter, W. Ritter, Pabst Science Publishers , 2014

2014

Modeling, Managing, Exposing, and Linking Ontologies with a Wiki-based Tool

LREC, 2014

In the last decade, the need of having effective and useful tools for the creation and the management of linguistic resources significantly increased. One of the main reasons is the necessity of building linguistic resources (LRs) that, besides the goal of expressing effectively the domain that users want to model, may be exploited in several ways. In this paper we present a wiki-based collaborative tool for modeling ontologies, and more in general any kind of linguistic resources, called MoKi. This tool has been customized in the context of an EU-funded project for addressing three important aspects of LRs modeling: (i) the exposure of the created LRs, (ii) for providing features for linking the created resources to external ones, and (iii) for producing multilingual LRs in a safe manner.
2014

Long Time No See: The Probability of Reusing Tags as a Function of Frequency and Recency

Proceedings of the Companion Publication of the 23rd International Conference on World Wide Web Companion, International World Wide Web Conferences Steering Committee, ACM, 2014

In this paper, we introduce a tag recommendation algorithm that mimics the way humans draw on items in their long-term mem- ory. This approach uses the frequency and recency of previous tag assignments to estimate the probability of reusing a particular tag. Using three real-world folksonomies gathered from bookmarks in BibSonomy, CiteULike and Flickr, we show how incorporating a time-dependent component outperforms conventional “most pop- ular 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 fre- quency analysis, our algorithm outperforms other well-established algorithms, such as FolkRank, Pairwise Interaction Tensor Fac- torization and Collaborative Filtering. We conclude that our ap- proach provides an accurate and computationally efficient model of a user’s temporal tagging behavior. We demonstrate how effec- tive principles of information retrieval can be designed and imple- mented if human memory processes are taken into account.
2014

Towards a Scalable Social Recommender Engine for Online Marketplaces: The Case of Apache Solr

Proceedings of the Companion Publication of the 23rd International Conference on World Wide Web Companion, International World Wide Web Conferences Steering Committee, ACM, 2014

Recent research has unveiled the importance of online social networks for improving the quality of recommenders in several domains, what has encouraged the research community to investigate ways to better exploit the social information for recommendations. However, there is a lack of work that offers details of frameworks that allow an easy integration of social data with traditional recommendation algorithms in order to yield a straight-forward and scalable implementation of new and existing systems. Furthermore, it is rare to find details of performance evaluations of recommender systems such as hardware and software specifications or benchmarking results of server loading tests. In this paper we intend to bridge this gap by presenting the details of a social recommender engine for online marketplaces built upon the well-known search engine Apache Solr. We describe our architecture and also share implementation details to facilitate the re-use of our approach by people implementing recommender systems. In addition, we evaluate our framework from two perspectives: (a) recommendation algorithms and data sources, and (b) system performance under server stress tests. Using a dataset from the SecondLife virtual world that has both trading and social interactions, we contribute to research in social recommenders by showing how certain social features allow to improve recommendations in online marketplaces. On the platform implementation side, our evaluation results can serve as a baseline to people searching for performance references in terms of scalability, model training and testing trade-offs, real-time server performance and the impact of model updates in a production system.
2014

Semantic Blossom Graph: A new Approach for Visual Graph Exploration

Proceedings of the 18th International Conference on Information Visualisation (IV2014), 2014

Graphs are widely used to represent relationships between entities. Indeed, their simplicity in depicting connectedness backed by a mathematical formalism, make graphs an ideal metaphor to convey relatedness between entities irrespective of the domain. However, graphs pose several challenges for visual analysis. A large number of entities or a densely connected set quickly render the graph unreadable due to clutter. Typed relationships leading to multigraphs cannot clearly be represented in hierarchical layout or edge bundling, common clutter reduction techniques. We propose a novel approach to visual analysis of complex graphs based on two metaphors: semantic blossom and selective expansion. Instead of showing the whole graph, we display only a small representative subset of nodes, each with a compressed summary of relations in a semantic blossom. Users apply selective expansion to traverse the graph and discover the subset of interest. A preliminary evaluation showed that our approach is intuitive and useful for graph exploration and provided insightful ideas for future improvements.
2014

TagRec: Towards A Standardized Tag Recommender Benchmarking Framework

In Proceedings of the 25th ACM Conference on Hypertext and Social Media (HT 2014), ACM, New York, NY, USA, 2014

In this paper, we introduce TagRec, a standardized tag recommender benchmarking framework implemented in Java. The purpose of TagRec is to provide researchers with a framework that supports all steps of the development process of a new tag recommendation algorithm in a reproducible way, including methods for data pre-processing, data modeling, data analysis and recommender evaluation against state-of-the-art baseline approaches. We demonstrate the performance of the algorithms implemented in TagRec in terms of prediction quality and runtime using an extensive evaluation of a real-world folksonomy dataset. Furthermore, TagRec contains two novel tag recommendation approaches based on models derived from human cognition and human memory theories.
2014

Detecting Outliers in Cell Phone Data: Correcting Trajectories to Improve Traffic Modeling

Journal of the Transportation Research Board, 2014

Konferenz
Using cell phone signaling data for traffic modeling has great potential. Due to the high coverage rate, it can be used in addition to stationary sensors or even act as replacement when deploying stationary sensors is not possible and/or too expensive. Though, one must be aware that cell phone signaling data is error-prone and must be pre-processed in order to use it for traffic modeling. First, the positions reported by cell phone signaling data may be inaccurate. Second, it could be possible that additional data is introduced to obfuscate the actual movement due to privacy issues. We present three different filters to smooth the trajectories generated by cell phone movements. For evaluation, we applied these filters to cell phone trajectories and compared them to their corresponding GPS-based tracks. The evaluation data covers 4.933 automatically and 5 manually collected tracks. The proposed filters significantly improve the speed and position estimation compared to the raw trajectories of cell phone movements.
2014

SocRecM: A Scalable Social Recommender Engine for Online Marketplaces

In Proceedings of the 25th ACM Conference on Hypertext and Social Media (HT 2014), ACM, New York, NY, USA, 2014

In this paper, we present work-in-progress on SocRecM, a novel social recommendation framework for online marketplaces. We demonstrate that SocRecM is not only easy to integrate with existing Web technologies through a RESTful, scalable and easy-to-extend service-based architecture but also reveal the extent to which various social features and recommendation approaches are useful in an online social marketplace environment.
2014

Iterative Augmentation of a Medical Training Simulator: Effects of Affective Metacognitive Scaffolding

Computers & Education, Elsevier, 2014

Konferenz
2014

Unsupervised document structure analysis of digital scientific articles

International Journal on Digital Libraries, Springer, 2014

Konferenz
Text mining and information retrieval in large collections of scientific literature require automated processing systems that analyse the documents' content. However, the layout of scientific articles is highly varying across publishers, and common digital document formats are optimised for presentation, but lack structural information. To overcome these challenges, we have developed a processing pipeline that analyses the structure a PDF document using a number of unsupervised machine learning techniques and heuristics. Our system uses only information available from the current document and does not require any pre-trained model. First, contiguous text blocks are extracted from the raw character stream. Next, we determine geometrical relations between these blocks, which, together with geometrical and font information, are then used categorize the blocks into different classes. Based on this resulting logical structure we finally extract the body text and the table of contents of a scientific article. We separately evaluate the individual stages of our pipeline on a number of different datasets and compare it with other document structure analysis approaches. We show that it outperforms a state-of-the-art system in terms of the quality of the extracted body text and table of contents. Our unsupervised approach could provide a basis for advanced digital library scenarios that involve diverse and dynamic corpora.
2014

Mehr als nur Suche – Wie moderne Informationsrückgewinnung Wissen zugänglich macht

Conference Proceedings - Grazer Symposium Virtuelles Fahrzeug, 2014

2014

Security Concepts for a Distributed Architecture for Activity Logging and Analysis

14th International Conference on Knowledge Technologies and Data-driven Business (i-KNOW 2014), 2014

We describe security concepts for a distributed architecture for activity logging and analysis. The described system collects user and usage data from multiple devices (PC and mobile). Such data is used to create open learner models for reflection on and improvement of time management. Additionally, such data is the basis for adaptation of notification mechanisms. We propose concepts for secure local storage of collected data, network communication and user authentication, and secure data storage and processing on the server side. We only touch partially on security concepts for client services and applications. The proposed concept is thus applicable for all systems with distributed activity logging and server-based analysis components.
2014

How groups of people interact with each other on Twitter during academic conferences

In Proceedings of the 2014 ACM Conference on Computer Supported Cooperative Work , ACM, 2014

2014

Stegmaier Florian, Seifert Christin, Kern Roman, Höfler Patrick, Bayerl Sebastian, Granitzer Michael, Kosch Harald, Lindstaedt Stefanie , Mutlu Belgin, Sabol Vedran, Schlegel Kai

Unleashing semantics of research data

Specifying Big Data Benchmarks, Springer, Berlin, Heidelberg, 2014

Buch
Research depends to a large degree on the availability and quality of primary research data, i.e., data generated through experiments and evaluations. While the Web in general and Linked Data in particular provide a platform and the necessary technologies for sharing, managing and utilizing research data, an ecosystem supporting those tasks is still missing. The vision of the CODE project is the establishment of a sophisticated ecosystem for Linked Data. Here, the extraction of knowledge encapsulated in scientific research paper along with its public release as Linked Data serves as the major use case. Further, Visual Analytics approaches empower end users to analyse, integrate and organize data. During these tasks, specific Big Data issues are present.
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