Publikationen

Hier finden Sie von Know-Center MitarbeiterInnen verfasste wissenschaftliche Publikationen

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.
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

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

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

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.
2013

Höfler Patrick, Granitzer Michael, Sabol Vedran, Lindstaedt Stefanie

Linked Data Query Wizard: A Tabular Interface for the Semantic Web

ESWC 2013, LNCS 7882, P. Cimiano et al., Springer, Heidelberg, 2013

Konferenz
Linked Data has become an essential part of the Semantic Web. A lot of Linked Data is already available in the Linked Open Data cloud, which keeps growing due to an influx of new data from research and open government activities. However, it is still quite difficult to access this wealth of semantically enriched data directly without having in-depth knowledge about SPARQL and related semantic technologies. In this paper, we present the Linked Data Query Wizard, a prototype that provides a Linked Data interface for non-expert users, focusing on keyword search as an entry point and a tabular interface providing simple functionality for filtering and exploration.
2012

Helic Denis, Körner C., Granitzer Michael, Strohmaier M., Trattner Christoph

Navigational efficiency of broad vs. narrow folksonomies

In Proceedings of the 23rd Conference on Hypertext and Social Media (HT2012). ACM, 2012, 2012

Konferenz
Although many social tagging systems share a common tripartitegraph structure, the collaborative processes that aregenerating these structures can differ significantly. For example,while resources on Delicious are usually tagged by allusers who bookmark the web page cnn.com, photos on Flickrare usually tagged just by a single user who uploads thephoto. In the literature, this distinction has been describedas a distinction between broad vs. narrow folksonomies.This paper sets out to explore navigational differences betweenbroad and narrow folksonomies in social hypertextualsystems. We study both kinds of folksonomies on a datasetprovided by Mendeley - a collaborative platform where userscan annotate and organize scientific articles with tags. Ourexperiments suggest that broad folksonomies are more usefulfor navigation, and that the collaborative processes thatare generating folksonomies matter qualitatively. Our findingsare relevant for system designers and engineers aimingto improve the navigability of social tagging systems.
2011

Declerck Thierry, Granitzer Michael, Grzegorzek Marcin, Romanelli Massimo, Rüger Stefan, Sintek Michael

Semantic Multimedia - 5th International Conference on Semantic and Digital Media Technologies, SAMT 2010

Lecture Notes in Computer Science, Vol. 6725, Declerck, T.; Granitzer, M.; Grzegorzek, M.; Romanelli, M.; Rüger, S.; Sintek, M., Springer, 2011

Konferenz
2011

Granitzer Michael, Lindstaedt Stefanie

Web 2.0: Applications and Mechanisms J.UCS Special Issue

JUCS - Journal of Universal Computing, 2011

Journal
2011

Granitzer Michael, Kienreich Wolfgang, Seifert Christin

Visualizing Text Classification Models with Voronoi Word Clouds

Proceedings 15th International Conference Information Visualisation (IV), 2011

Journal
2011

Horn Christopher, Lex Elisabeth, Granitzer Michael

Who Tweets: Detecting User Types and Tweet Quality using Supervised Classification

IADIS Multiconference on Computer Science and Information Systems, 2011

Konferenz
Social networking tools like Twitter are the latest trend in the global world. However, due to the increasing amount ofcontent in Twitter, there is a need for information filtering by facets like user type and content quality. In this work, weaddress this challenge by classifying users into three user types, "news", "personal user", and "advertisements".Additionally, we assess the quality of the Tweets by classifying them into "factual" versus "opinionated". We evaluatedword stemming and regular expressions as data pre-processing techniques and found that with simple regularexpressions, a sound classification accuracy of more than 80% can be achieved. Besides, we propose a web-based TwitterClassification Application that enables to manually annotate Tweets into a set of pre-defined classes with maintainableeffort.
2011

Granitzer Michael, Lindstaedt Stefanie

Semantic Web: Theory and Applications

Journal of Universal Computer Science, 2011

Journal
2011

Granitzer Michael, Lindstaedt Stefanie

Knowledge Work : Knowledge Worker Productivity , Collaboration and User Support

J.UCS - Journal of Universal Computer Science, 2011

Journal
2011

Seifert Christin, Ulbrich Eva Pauline, Granitzer Michael

Word Clouds for Efficient Document Labeling

The Fourteenth International Conference on Discovery Science (DS 2011), Lecture Notes in Computer Science, Springer, 2011

Konferenz
In text classification the amount and quality of training datais crucial for the performance of the classifier. The generation of trainingdata is done by human labelers - a tedious and time-consuming work. Wepropose to use condensed representations of text documents instead ofthe full-text document to reduce the labeling time for single documents.These condensed representations are key sentences and key phrases andcan be generated in a fully unsupervised way. The key phrases are presentedin a layout similar to a tag cloud. In a user study with 37 participantswe evaluated whether document labeling with these condensedrepresentations can be done faster and equally accurate by the humanlabelers. Our evaluation shows that the users labeled word clouds twiceas fast but as accurately as full-text documents. While further investigationsfor different classification tasks are necessary, this insight couldpotentially reduce costs for the labeling process of text documents.
2011

Kern Roman, Zechner Mario, Granitzer Michael

Model Selection Strategies for Author Disambiguation

IEEE Computer Society: 8th International Workshop on Text-based Information Retrieval in Procceedings of 22th International Conference on Database and Expert Systems Applications (DEXA 11), IEEE , 2011

Konferenz
Author disambiguation is a prerequisite for utilizingbibliographic metadata in citation analysis. Automaticdisambiguation algorithms mostly rely on cluster-based disambiguationstrategies for identifying unique authors given theirnames and publications. However, most approaches rely onknowing the correct number of unique authors a-priori, whichis rarely the case in real world settings. In this publicationwe analyse cluster-based disambiguation strategies and developa model selection method to estimate the number of distinctauthors based on co-authorship networks. We show that, givenclean textual features, the developed model selection methodprovides accurate guesses of the number of unique authors.
2011

Kow Weng Onn, Sabol Vedran, Granitzer Michael, Kienreich Wolfgang, Lukose Dickson

A Visual SOA-based Ontology Alignment Tool

in Proceedings of the Sixth International Workshop on Ontology Matching (OM-2011), CEUR-WS. org, 2011

Journal
Ontology alignment is the process of matching related concepts fromdifferent ontologies. We propose a semi-automatic, visual approach whichcombines two algorithms for finding candidate alignments with visualnavigation and analysis tools. The implementation is based on a ServiceOrientedArchitecture (SOA) to achieve scalability.
2011

Horn Christopher, Pimas Oliver, Granitzer Michael, Lex Elisabeth

Realtime Ad Hoc Search in Twitter: Know-Center at TREC Microblog Track 2011

Proceedings of TREC 2011, 2011

In this paper, we outline our experiments carried out at theTREC Microblog Track 2011. Our system is based on a plain text indexextracted from Tweets crawled from twitter.com. This index hasbeen used to retrieve candidate Tweets for the given topics. The resultingTweets were post-processed and then analyzed using three differentapproaches: (i) a burst detection approach, (ii) a hashtag analysis, and(iii) a Retweet analysis. Our experiments consisted of four runs: Firstly,a combination of the Lucene ranking with the burst detection, and secondly,a combination of the Lucene ranking, the burst detection, and thehashtag analysis. Thirdly, a combination of the Lucene ranking, the burstdetection, the hashtag analysis, and the Retweet analysis, and fourthly,again a combination of the Lucene ranking with the burst detection butin this case with more sophisticated query language and post-processing.We achieved the best MAP values overall in the fourth run.
2011

Shahzad Syed K, Granitzer Michael, Helic Denis

Ontological Model Driven GUI Development: User Interface Ontology Approach

6th International Conference on Computer Sciences and Convergence Information Technology (ICCIT), IEEE, 2011

Konferenz
Ontology and Semantic Framework has becomepervasive in computer science. It has huge impact at database,business logic and user interface for a range of computerapplications. This framework is also being introduced, presentedor plugged at user interfaces for various software and websites.However, establishment of structured and standardizedontological model based user interface development environmentis still a challenge. This paper talks about the necessity of such anenvironment based on User Interface Ontology (UIO). To explorethis phenomenon, this research focuses at the User Interfaceentities, their semantics, uses and relationships among them. Thefirst part focuses on the development of User Interface Ontology.In the second step, this ontology is mapped to the domainontology to construct a User Interface Model. Finally, theresulting model is quantified and instantiated for a user interfacedevelopment to support our framework. This UIO is anextendable framework that allows defining new sub-conceptswith their ontological relationships and constraints.
2011

Granitzer Michael, Tochtermann Klaus

Future Internet and the Library World

ZEITSCHRIFT FUR BIBLIOTHEKSWESEN UND BIBLIOGRAPHIE, 2011

Journal
2011

Kern Roman, Seifert Christin, Zechner Mario, Granitzer Michael

Vote/Veto Meta-Classifier for Authorship Identification

CLEF 2011: Proceedings of the 2011 Conference on Multilingual and Multimodal Information Access Evaluation (Lab and Workshop Notebook Papers), Amsterdam, The Netherlands, 2011

For the PAN 2011 authorship identification challenge we have developeda system based on a meta-classifier which selectively uses the results ofmultiple base classifiers. In addition we also performed feature engineering basedon the given domain of e-mails. We present our system as well as results on theevaluation dataset. Our system performed second and third best in the authorshipattribution task on the large data sets, and ranked middle for the small data set inthe attribution task and in the verification task.
2010

Kern Roman, Seifert Christin, Granitzer Michael

A Hybrid System for German Encyclopedia Alignment

International Journal on Digital Libraries, Springer, 2010

Journal
Collaboratively created on-line encyclopediashave become increasingly popular. Especially in terms ofcompleteness they have begun to surpass their printedcounterparts. Two German publishers of traditional encyclopediashave reacted to this challenge and started aninitiative to merge their corpora to create a single, more completeencyclopedia. The crucial step in this merging processis the alignment of articles. We have developed a two-stephybrid system to provide high-accurate alignments with lowmanual effort. First, we apply an information retrieval based,automatic alignment algorithm. Second, the articles with alow confidence score are revised using a manual alignmentscheme carefully designed for quality assurance. Our evaluationshows that a combination of weighting and rankingtechniques utilizing different facets of the encyclopedia articlesallow to effectively reduce the number of necessary manualalignments. Further, the setup of the manual alignment turned out to be robust against inter-indexer inconsistencies.As a result, the developed system empowered us to align fourencyclopedias with high accuracy and low effort.
2010

Lex Elisabeth, Granitzer Michael, Juffinger A.

A Comparison of Stylometric and Lexical Features for Web Genre Classification and Emotion Classification in Blogs

IEEE Computer Society: 7th International Workshop on Text-based Information Retrieval in Procceedings of 21th International Conference on Database and Expert Systems Applications (DEXA 10)., IEEE, 2010

Konferenz
In the blogosphere, the amount of digital content is expanding and for search engines, new challenges have been imposed. Due to the changing information need, automatic methods are needed to support blog search users to filter information by different facets. In our work, we aim to support blog search with genre and facet information. Since we focus on the news genre, our approach is to classify blogs into news versus rest. Also, we assess the emotionality facet in news related blogs to enable users to identify people’s feelings towards specific events. Our approach is to evaluate the performance of text classifiers with lexical and stylometric features to determine the best performing combination for our tasks. Our experiments on a subset of the TREC Blogs08 dataset reveal that classifiers trained on lexical features perform consistently better than classifiers trained on the best stylometric features.
2010

Lirk G., Granitzer Michael, Söhnnichsen A., Kulczycki P.

Wissensmanagement in EBM

EbM - ein Gewinn für die Arzt-Patient-Beziehung?. Forum Medizin 21 der Paracelsus Medizinischen Privatuniversität & 11. EbM-Jahrestagung des Deutschen Netzwerks Evidenzbasierte Medizin, German Medical Science GMS Publishing House, 2010

Konferenz
2010

Granitzer Michael

Adaptive Term Weighting through Stochastic Optimization

11th International Conference, CICLing 2010, Iasi, Romania, March 22-25, 2010, Gelbukh, A., Springer, 2010

Konferenz
Term weighting strongly influences the performance of text miningand information retrieval approaches. Usually term weights are determined throughstatistical estimates based on static weighting schemes. Such static approacheslack the capability to generalize to different domains and different data sets. Inthis paper, we introduce an on-line learning method for adapting term weightsin a supervised manner. Via stochastic optimization we determine a linear transformationof the term space to approximate expected similarity values amongdocuments. We evaluate our approach on 18 standard text data sets and showthat the performance improvement of a k-NN classifier ranges between 1% and12% by using adaptive term weighting as preprocessing step. Further, we provideempirical evidence that our approach is efficient to cope with larger problems
2010

Granitzer Michael, Kienreich Wolfgang

Semantische Technologien: Stand der Forschung und Visionen

Internationales Rechtsinformatik Symposion (IRIS 10), OCG, 2010

Konferenz
2010

Granitzer Michael

Enterprise Search

Lexikon der Bibliotheks- und Informationswissenschaft, Umlauf, K., Gradmann, S. , Anton Hiersemann Verlag, 2010

Buch
2010

Klieber Hans-Werner, Granitzer Michael, Gaisbauer M.

Semantically enhanced Software Documentation Processes

Serdica Journal of Computing, 2010

Journal
High-quality software documentation is a substantial issue forunderstanding software systems. Shorter time-to-market software cycles increasethe importance of automatism for keeping the documentation up todate. In this paper, we describe the automatic support of the software documentationprocess using semantic technologies. We introduce a softwaredocumentation ontology as an underlying knowledge base. The defined ontologyis populated automatically by analysing source code, software documentationand code execution. Through selected results we demonstratethat the use of such semantic systems can support software documentationprocesses efficiently.
2010

Lex Elisabeth, Granitzer Michael, Juffinger A.

Facet Classification of Blogs: Know-Center at the TREC 2009 Blog Distillation Task

Proceedings of the 18th Text REtrieval Conference, 2010

Konferenz
In this paper, we outline our experiments carried out at the TREC 2009 Blog Distillation Task. Our system is based on a plain text index extracted from the XML feeds of the TREC Blogs08 dataset. This index was used to retrieve candidate blogs for the given topics. The resulting blogs were classified using a Support Vector Machine that was trained on a manually labelled subset of the TREC Blogs08 dataset. Our experiments included three runs on different features: firstly on nouns, secondly on stylometric properties, and thirdly on punctuation statistics. The facet identification based on our approach was successful, although a significant number of candidate blogs were not retrieved at all.
2010

Lex Elisabeth, Granitzer Michael, Juffinger A., Seifert C.

Efficient Cross-Domain Classification of Weblogs

International Journal of Intelligent Computing Research (IJICR), Vol.1, Issue 2, Infonomics Society, 2010

Journal
Text classification is one of the core applicationsin data mining due to the huge amount ofuncategorized textual data available. Training a textclassifier results in a classification model that reflectsthe characteristics of the domain it was learned on.However, if no training data is available, labeled datafrom a related but different domain might be exploitedto perform cross-domain classification. In our work,we aim to accurately classify unlabeled weblogs intocommonly agreed upon newspaper categories usinglabeled data from the news domain. The labeled newsand the unlabeled blog corpus are highly dynamicand hourly growing with a topic drift, so theclassification needs to be efficient. Our approach is toapply a fast novel centroid-based text classificationalgorithm, the Class-Feature-Centroid Classifier(CFC), to perform efficient cross-domainclassification. Experiments showed that thisalgorithm achieves a comparable accuracy thank-Nearest Neighbour (k-NN) and Support VectorMachines (SVM), yet at linear time cost for trainingand classification. We investigate the classifierperformance and generalization ability using aspecial visualization of classifiers. The benefit of ourapproach is that the linear time complexity enables usto efficiently generate an accurate classifier,reflecting the topic drift, several times per day on ahuge dataset.
2010

Lex Elisabeth, Granitzer Michael, Juffinger A., Muhr M.

Stylometric Features for Emotion Level Classification in News Related Blogs

Proceedings of the 9th ACM RIAO Conference , LE CENTRE DE HAUTES ETUDES INTERNATIONALES D'INFORMATIQUE DOCUMENTAIRE, 2010

Konferenz
Breaking news and events are often posted in the blogospherebefore they are published by any media agency. Therefore,the blogosphere is a valuable resource for news-relatedblog analysis. However, it is crucial to first sort out newsunrelatedcontent like personal diaries or advertising blogs.Besides, there are different levels of emotionality or involvementwhich bias the news information to a certain extent.In our work, we evaluate topic-independent stylometric featuresto classify blogs into news versus rest and to assess theemotionality in these blogs. We apply several text classifiersto determine the best performing combination of featuresand algorithms. Our experiments revealed that with simplestyle features, blogs can be classified into news versus restand their emotionality can be assessed with accuracy valuesof almost 80%.
2010

Lex Elisabeth, Granitzer Michael, Juffinger A.

Objectivity Classification in Online Media

21st ACM SIGWEB Conference on Hypertext and Hypermedia (HT2010), ACM, 2010

Konferenz
In this work, we assess objectivity in online news media. Wepropose to use topic independent features and we show ina cross-domain experiment that with standard bag-of-wordmodels, classifiers implicitly learn topics. Our experimentsrevealed that our methodology can be applied across differenttopics with consistent classification performance.
2010

Kern Roman, Granitzer Michael, Muhr M.

KCDC: Word Sense Induction by Using Grammatical Dependencies and Sentence Phrase Structure

Proceedings of SemEval-2, 2010

Konferenz
Word sense induction and discrimination(WSID) identifies the senses of an ambiguousword and assigns instances of thisword to one of these senses. We have builda WSID system that exploits syntactic andsemantic features based on the results ofa natural language parser component. Toachieve high robustness and good generalizationcapabilities, we designed our systemto work on a restricted, but grammaticallyrich set of features. Based on theresults of the evaluations our system providesa promising performance and robustness.
2010

Kern Roman, Granitzer Michael, Muhr M.

Analysis of Structural Relationships for Hierarchical Cluster Labeling

Proceeding of the 33rd international ACM SIGIR Conference on Research and Development in information Retrieval, ACM, 2010

Konferenz
Cluster label quality is crucial for browsing topic hierarchiesobtained via document clustering. Intuitively, the hierarchicalstructure should influence the labeling accuracy. However,most labeling algorithms ignore such structural propertiesand therefore, the impact of hierarchical structureson the labeling accuracy is yet unclear. In our work weintegrate hierarchical information, i.e. sibling and parentchildrelations, in the cluster labeling process. We adaptstandard labeling approaches, namely Maximum Term Frequency,Jensen-Shannon Divergence, χ2 Test, and InformationGain, to take use of those relationships and evaluatetheir impact on 4 different datasets, namely the Open DirectoryProject, Wikipedia, TREC Ohsumed and the CLEFIP European Patent dataset. We show, that hierarchicalrelationships can be exploited to increase labeling accuracyespecially on high-level nodes.
2010

Sabol Vedran, Granitzer Michael, Seifert C.

Classifier Hypothesis Generation Using Visual Analysis Methods

NDT: Networked Digital Technologies, Springer, 2010

Konferenz
Classifiers can be used to automatically dispatch the abundanceof newly created documents to recipients interested in particulartopics. Identification of adequate training examples is essential forclassification performance, but it may prove to be a challenging task inlarge document repositories. We propose a classifier hypothesis generationmethod relying on automated analysis and information visualisation.In our approach visualisations are used to explore the document sets andto inspect the results of machine learning methods, allowing the user toassess the classifier performance and adapt the classifier by graduallyrefining the training set.
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
2010

Kern Roman, Granitzer Michael

German Encyclopedia Alignment Based on Information Retrieval Techniques

ECDL 2010: Research and Advanced Technology for Digital Libraries, 2010

Konferenz
Collaboratively created online encyclopedias have becomeincreasingly popular. Especially in terms of completeness they have begunto surpass their printed counterparts. Two German publishers oftraditional encyclopedias have reacted to this challenge and decided tomerge their corpora to create a single more complete encyclopedia. Thecrucial step in this merge process is the alignment of articles. We havedeveloped a system to identify corresponding entries from different encyclopediccorpora. The base of our system is the alignment algorithmwhich incorporates various techniques developed in the field of informationretrieval. We have evaluated the system on four real-world encyclopediaswith a ground truth provided by domain experts. A combinationof weighting and ranking techniques has been found to deliver a satisfyingperformance.
2010

Kern Roman, Zechner Mario, Granitzer Michael, Muhr M.

External and Intrinsic Plagiarism Detection using a Cross-Lingual Retrieval and Segmentation System Lab Report for PAN at CLEF 2010

2nd International Competition on Plagiarism Detection, 2010

Konferenz
We present our hybrid system for the PAN challenge at CLEF 2010.Our system performs plagiarism detection for translated and non-translated externallyas well as intrinsically plagiarized document passages. Our external plagiarismdetection approach is formulated as an information retrieval problem, usingheuristic post processing to arrive at the final detection results. For the retrievalstep, source documents are split into overlapping blocks which are indexed via aLucene instance. Suspicious documents are similarly split into consecutive overlappingboolean queries which are performed on the Lucene index to retrieve aninitial set of potentially plagiarized passages. For performance reasons queriesmight get rejected via a heuristic before actually being executed. Candidate hitsgathered via the retrieval step are further post-processed by performing sequenceanalysis on the passages retrieved from the index with respect to the passagesused for querying the index. By applying several merge heuristics bigger blocksare formed from matching sequences. German and Spanish source documentsare first translated using word alignment on the Europarl corpus before enteringthe above detection process. For each word in a translated document severaltranslations are produced. Intrinsic plagiarism detection is done by finding majorchanges in style measured via word suffixes after the documents have been partitionedby an linear text segmentation algorithm. Our approach lead us to the thirdoverall rank with an overall score of 0.6948.
2010

Sabol Vedran, Granitzer Michael, Muhr M.

Scalable Recursive Top-Down Hierarchical Clustering Approach with implicit Model Selection for Textual Data Sets

IEEE Computer Society: 7th International Workshop on Text-based Information Retrieval in Procceedings of 21th International Conference on Database and Expert Systems Applications (DEXA 10)., IEEE, 2010

Konferenz
Automatic generation of taxonomies can be usefulfor a wide area of applications. In our application scenario atopical hierarchy should be constructed reasonably fast froma large document collection to aid browsing of the data set.The hierarchy should also be used by the InfoSky projectionalgorithm to create an information landscape visualizationsuitable for explorative navigation of the data. We developedan algorithm that applies a scalable, recursive, top-downclustering approach to generate a dynamic concept hierarchy.The algorithm recursively applies a workflow consisting ofpreprocessing, clustering, cluster labeling and projection into2D space. Besides presenting and discussing the benefits ofcombining hierarchy browsing with visual exploration, we alsoinvestigate the clustering results achieved on a real world dataset.
2010

Lex Elisabeth, Khan I., Bischof H., Granitzer Michael

Assessing the Quality of Web Content

Proceedings of the ECML/PKDD Discovery Challenge 2010, Online, 2010

Konferenz
2010

Seifert C., Granitzer Michael

User-based active learning

International Conference on Data Mining Workshops (Workshop on Visual Analytics and Knowledge Discovery), Fan, W., Hsu, W.,Webb, G. I., Liu, B., Zhang, C., Gunopulos, D., Wu, X., IEEE, 2010

Konferenz
Active learning has been proven a reliable strategyto reduce manual efforts in training data labeling. Suchstrategies incorporate the user as oracle: the classifier selectsthe most appropriate example and the user provides the label.While this approach is tailored towards the classifier, moreintelligent input from the user may be beneficial. For instance,given only one example at a time users are hardly ableto determine whether this example is an outlier or not. Inthis paper we propose user-based visually-supported activelearning strategies that allow the user to do both, selectingand labeling examples given a trained classifier. While labelingis straightforward, selection takes place using a interactivevisualization of the classifier’s a-posteriori output probabilities.By simulating different user selection strategies we show,that user-based active learning outperforms uncertainty basedsampling methods and yields a more robust approach ondifferent data sets. The obtained results point towards thepotential of combining active learning strategies with resultsfrom the field of information visualization.
2010

Shahzad Syed K., Granitzer Michael

Ontological Framework Driven GUI Development

Proceedings of I-KNOW, 2010

Konferenz
The user experience of any software or website consists of elements from theconceptual to the concrete level. These elements of user experience assist in the design anddevelopment of user interfaces. On the other hand, Ontologies provide a framework forcomputable representation of user interface elements and underlying data. This paper discussesstrategies of introducing ontologies at different user interface layers adapted from userexperience elements. These layers range from abstract levels (e.g. User needs/ApplicationObjectives) to concrete levels (e.g. Application User Interface) in term of data representation.The proposed ontological framework enables device independent, semi-automated GUIconstruction which we will demonstrate at a personal information management example.
2010

Granitzer Michael, Sabol Vedran, Kienreich Wolfgang, Lukose Dickson, Onn Kow Weng

Visual Analyses on Linked Data - An Opportunity for both Fields

The 2011 STI Semantic Summit, Riga, Latvia, 2010

2010

Granitzer Michael, Kienreich Wolfgang, Sabol Vedran, Lex Elisabeth

Knowledge Relationship Discovery and Visually Enhanced Access for the Media Domain

Medien-Wissen-Bildung. Explorationen visualisierter und kollaborativer Wissensräume, Innsbruck University Press, 2010

Konferenz
Technological advances and paradigmatic changes in the utilization of the World Wide Web havetransformed the information seeking strategies of media consumers and invalidated traditionalbusiness models of media providers. We discuss relevant aspects of this development and presenta knowledge relationship discovery pipeline to address the requirements of media providers andmedia consumers. We also propose visually enhanced access methods to bridge the gap betweencomplex media services and the information needs of the general public. We conclude that acombination of advanced processing methods and visualizations will enable media providers totake the step from content-centered to service-centered business models and, at the same time,will help media consumers to better satisfy their personal information needs.
2010

Erol S., Granitzer Michael, Happ S., Jantunen S., Jennings B., Koschmider A., Nurcan S., Rossi D., Schmidt R.

Combining BPM and Social Software: Contradiction or Chance?

Journal of software maintenance and evolution: research and practice, John Wiley & Sons, Ltd., 2010

Journal
2010

Granitzer Michael, Lanthaler Markus, Gütl Christian

Semantic Web services: state of the art

Proceedings of the IADIS international conference-Internet technologies and society 2010, IADIS Press, 2010

Konferenz
Service-oriented architectures (SOA) built on Web services were a first attempt to streamline and automate business processes in order to increase productivity but the utopian promise of uniform service interface standards, metadata, and universal service registries, in the form of the SOAP, WSDL and UDDI standards has proven elusive. Furthermore, the RPC-oriented model of those traditional Web services is not Web-friendly. Thus more and more prominent Web service providers opted to expose their services based on the REST architectural style. Nevertheless there are still problems on formal describing, finding, and orchestrating RESTful services. While there are already a number of different approaches none so far has managed to break out of its academic confines. This paper focuses on an extensive survey comparing the existing state-of-the-art technologies for semantically annotated Web services as a first step towards a proposal designed specifically for RESTful services.
2009

Zechner Mario, Granitzer Michael

K-Means on the Graphics Processor: Design And Experimental Analysis

International Journal on Advances in Systems and Measurements, Volume 2, Number 2&3, Paleologu, C., 2009

Journal
2009

Granitzer Michael, Zechner Mario, Seifert C.

Context based Wikipedia Linking

Advances in Focused Retrieval 7th International Workshop of the Initiative for the Evaluation of XML Retrieval (INEX 2008), Geva, S., Kamps, J., Trotman, A., Springer, 2009

Konferenz
2009

Sabol Vedran, Kienreich Wolfgang, Klieber Hans-Werner, Granitzer Michael, Muhr M.

Visual Knowledge Discovery in Dynamic Enterprise Text Repositories

Proceedings of the 13th International Conference on Information Visualisation (IV09), IEEE Computer Society, 2009

Konferenz
2009

Granitzer Michael, Stocker A.

Can Intra-Organizational Wikis Facilitate Knowledge Transfer and Learning? An Explorative Case Study

Proceedings of eLBa - eLearning Baltics 2009, 2009

Konferenz
2009

Muhr M., Granitzer Michael

Automatic Cluster Number Selection using a Split and Merge K-Means Approach

6th International Workshop on Text-based Information Retrieval in Procceedings of 20th International Conference on Database and Expert Systems Applications (DEXA 09), IEEE Computer Society, 2009

Konferenz
2009

Granitzer M., Kienreich Wolfgang, Sabol Vedran, Augustin A.

Taxonomy Extraction from German Encyclopedic Texts

In Proceedings of the Malaysian Joint Conference on Artificial Intelligence 2009, Kuala Lumpur, Malaysia, 2009

Konferenz
2009

Klieber Hans-Werner, Sabol Vedran, Kern Roman, Granitzer Michael, Muhr M., Ättl G.

Knowledge Discovery Using the Knowminer Framework

IADIS International Conference Information Systems 2009, 2009

Konferenz
2009

Granitzer Michael, Lex Elisabeth, Juffinger A.

Blog Credibility Ranking by Exploiting Verified Content

Proceedings of the 3rd Workshop on Information Credibility on the Web at 18th World Wide Web Conference, 2009

Konferenz
People use weblogs to express thoughts, present ideas and share knowledge. However, weblogs can also be misused to influence and manipulate the readers. Therefore the credibility of a blog has to be validated before the available information is used for analysis. The credibility of a blogentry is derived from the content, the credibility of the author or blog itself, respectively, and the external references or trackbacks. In this work we introduce an additional dimension to assess the credibility, namely the quantity structure. For our blog analysis system we derive the credibility therefore from two dimensions. Firstly, the quantity structure of a set of blogs and a reference corpus is compared and secondly, we analyse each separate blog content and examine the similarity with a verified news corpus. From the content similarity values we derive a ranking function. Our evaluation showed that one can sort out incredible blogs by quantity structure without deeper analysis. Besides, the content based ranking function sorts the blogs by credibility with high accuracy. Our blog analysis system is therefore capable of providing credibility levels per blog.
2009

Lex Elisabeth, Granitzer Michael, Juffinger A., Seifert C.

Cross-Domain Classification: Trade-Off between Complexity and Accuracy

Proceedings of the 4th International Conference for Internet Technology and Secured Transactions (ICITST) 2009, 2009

Text classification is one of the core applications in data mining due to the huge amount of not categorized digital data available. Training a text classifier generates a model that reflects the characteristics of the domain. However, if no training data is available, labeled data from a related but different domain might be exploited to perform crossdomain classification. In our work, we aim to accurately classify unlabeled blogs into commonly agreed newspaper categories using labeled data from the news domain. The labeled news and the unlabeled blog corpus are highly dynamic and hourly growing with a topic drift, so a trade-off between accuracy and performance is required. Our approach is to apply a fast novel centroid-based algorithm, the Class-Feature-Centroid Classifier (CFC), to perform efficient cross-domain classification. Experiments showed that this algorithm achieves a comparable accuracy than k-NN and is slightly better than Support Vector Machines (SVM), yet at linear time cost for training and classification. The benefit of this approach is that the linear time complexity enables us to efficiently generate an accurate classifier, reflecting the topic drift, several times per day on a huge dataset.
2009

Willfort R., Lex Elisabeth, Granitzer Michael, Juffinger A.

Spectral Web Content Trend Analysis

Proc. of IADIS International Conference WWW/Internet, 2009

Konferenz
2009

Granitzer Michael, Malkom J., Ipsmiller D.

Wissensmanagement mit DYONIPOS: Konzepte, Algorithmen und Technologien

Tagungsband , Internationales Rechtsinformatik Symposion 2009 (to appear), Boorberg , 2009

2009

Lex Elisabeth, Granitzer Michael, Juffinger A., Seifert C.

Automated Blog Classification: A Cross Domain Approach

Proc. of IADIS International Conference WWW/Internet, 2009

Konferenz
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

Klieber Hans-Werner, Sabol Vedran, Granitzer Michael, Muhr M.

Using Ontologies For Software Documentation

Malaysian Joint Conference on Artificial Intelligence 2009, 2009

Konferenz
2009

Zechner Mario, Kern Roman, Granitzer Michael, Muhr M.

External and Intrinsic Plagiarism Detection Using Vector Space Models

Proceedings of the SEPLN'09 Workshop on Uncovering Plagiarism, Authorship and Social Software Misuse, 2009

Konferenz
2009

Granitzer Michael, Rath Andreas S., Kröll Mark, Ipsmiller D., Devaurs Didier, Weber Nicolas, Lindstaedt Stefanie , Seifert C.

Machine Learning based Work Task Classification

Journal of Digital Information Management, 2009

Journal
Increasing the productivity of a knowledgeworker via intelligent applications requires the identification ofa user’s current work task, i.e. the current work context a userresides in. In this work we present and evaluate machine learningbased work task detection methods. By viewing a work taskas sequence of digital interaction patterns of mouse clicks andkey strokes, we present (i) a methodology for recording thoseuser interactions and (ii) an in-depth analysis of supervised classificationmodels for classifying work tasks in two different scenarios:a task centric scenario and a user centric scenario. Weanalyze different supervised classification models, feature typesand feature selection methods on a laboratory as well as a realworld data set. Results show satisfiable accuracy and high useracceptance by using relatively simple types of features.
2009

Shahzad S., Granitzer Michael

Designing User Interfaces through Ontological User Models

Proceedings of the Fourth International Conference on Computer Sciences and Convergence Information Technology, ICCIT 2009, Seoul, Korea, IEEE Computer Society, 2009

Konferenz
2009

Zechner Mario, Granitzer Michael

A Competitive Learning Approach to Instance Selection for Support Vector Machines

To appear in: Proceedings of the 3rd International Conference on Knowledge Science, Engineering and Management, 2009

Konferenz
2009

Kern Roman, Granitzer Michael, Lindstaedt Stefanie , Ghidini C., Scheir Peter

ARS/SD: An Associative Retrieval Service for the Semantic Desktop

Networked Knowledge - Networked Media Integrating Knowledge Management, New Media Technologies and Semantic Systems, Studies in Computational Intelligence , Pellegrini, T., Auer, S., Tochtermann, K., Schaffert, S., Springer, 2009

Buch
While it is agreed that semantic enrichment of resources wouldlead to better search results, at present the low coverage of resources onthe web with semantic information presents a major hurdle in realizing thevision of search on the Semantic Web. To address this problem we investigatehow to improve retrieval performance in a setting where resources aresparsely annotated with semantic information. We suggest employing techniquesfrom associative information retrieval to find relevant material, whichwas not originally annotated with the concepts used in a query. We presentan associative retrieval service for the Semantic Desktop and evaluate if theuse of associative retrieval techniques increases retrieval performance.Evaluation of new retrieval paradigms, as retrieval in the Semantic Web oron the Semantic Desktop, presents an additional challenge as no off-the-shelftest corpora for evaluation exist. Hence we give a detailed description of the
2009

Kern Roman, Granitzer Michael

Efficient linear text segmentation based on information retrieval techniques

MEDES '09: Proceedings of the International Conference on Management of Emergent Digital EcoSystems, ACM, 2009

The task of linear text segmentation is to split a large text document into shorter fragments, usually blocks of consecutive sentences. The algorithms that demonstrated the best performance for this task come at the price of high computational complexity. In our work we present an algorithm that has a computational complexity of O(n) with n being the number of sentences in a document. The performance of our approach is evaluated against algorithms of higher complexity using standard benchmark data sets and we demonstrate that our approach provides comparable accuracy.
2009

Kern Roman, Juffinger A., Granitzer Michael

Application of Axiomatic Approaches to Crosslanguage Retrieval

Working Notes for the CLEF 2009 Workshop, 2009

Konferenz
2009

Lex Elisabeth, Granitzer Michael, Juffinger A.

Know-Center at TREC 2009 Blog Distillation Task: A Notebook Paper

Notebook of TREC 2009, 2009

Konferenz
2009

Zechner Mario, Granitzer Michael

Accelerating K-Means on the Graphics Processor via CUDA

Proceedings of the 2009 First International Conference on Intensive Applications and Services (INTENSIVE 2009), IEEE Computer Society, 2009

2008

Kern Roman, Granitzer Michael, Pammer-Schindler Viktoria

Extending Folksonomies for Image Tagging

WIAMIS 2008 , Special Session on Multimedia Metadata Management & Retrieval, IEEE Computer Society, Klagenfurt, 2008

Buch
2008

Kump Barbara, Kienreich Wolfgang, Granitzer Gisela, Granitzer Michael, Seifert C.

On the beauty and usability of tag clouds

Proceedings of the 12 International Conference on Information Visualization (IV2008), London, UK, July 9-11, 2008, IEEE Computer Society Press, 2008

Konferenz
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
2008

Granitzer Michael, Lux M., Spaniol M.

Multimedia Semantics - The Role of Metadata

Studies in Computational Intelligence , Vol. 101, Springer, Berlin, 2008

Buch
2008

Brunie L., Bailer Werner, Doeller M., Granitzer Michael, Klamma R., Kosch H., Lux M., Spaniol M.

Multimedia Metadata Standards

"Encyclopedia of Multimedia " 2nd edition, Springer, Berlin, 2008

Buch
2008

Granitzer Michael, Granitzer Gisela, Lindstaedt Stefanie , Rath Andreas S., Groiss W.

Automating Knowledge Transfer and Creation in Knowledge Intensive Business Processes

Proceedings of the First Workshop on Business Process Management and Social Software BPMS2 08, September 1, 2008, Mailand, Italien, Springer, 2008

It is a well known fact that a wealth of knowledge lies in thehead of employees making them one of the most or even the most valuableasset of organisations. But often this knowledge is not documented andorganised in knowledge systems as required by the organisation, butinformally shared. Of course this is against the organisation’s aim forkeeping knowledge reusable as well as easily and permanently availableindependent of individual knowledge workers.In this contribution we suggest a solution which captures the collectiveknowledge to the benefit of the organisation and the knowledge worker.By automatically identifying activity patterns and aggregating them totasks as well as by assigning resources to these tasks, our proposed solutionfulfils the organisation’s need for documentation and structuring ofknowledge work. On the other hand it fulfils the the knowledge worker’sneed for relevant, currently needed knowledge, by automatically miningthe entire corporate knowledge base and providing relevant, contextdependent information based on his/her current task.
2008

Rath Andreas S., Weber Nicolas, Kröll Mark, Granitzer Michael, Dietzel O., Lindstaedt Stefanie

Context-Aware Knowledge Services

Workshop on Personal Information Management (PIM2008) at the 26th Computer Human Interaction Conference (CHI2008), Florence, Italy, 2008

Konferenz
Improving the productivity of knowledge workers is anopen research challenge. Our approach is based onproviding a large variety of knowledge services which takethe current work task and information need (work context)of the knowledge worker into account. In the following wepresent the DYONIPOS application which strives toautomatically identify a user’s work task and thencontextualizes different types of knowledge servicesaccordingly. These knowledge services then provideinformation (documents, people, locations) both from theuser’s personal as well as from the organizationalenvironment. The utility and functionality is illustratedalong a real world application scenario at the Ministry ofFinance in Austria.
2008

Granitzer Michael, Kröll Mark, Seifer Christin, Rath Andreas S., Weber Nicolas, Dietzel O., Lindstaedt Stefanie

Analysis of Machine Learning Techniques for Context Extraction

Proceedings of 2008 International Conference on Digital Information Management (ICDIM08), IEEE Computer Society Press, 2008

Konferenz
’Context is key’ conveys the importance of capturing thedigital environment of a knowledge worker. Knowing theuser’s context offers various possibilities for support, likefor example enhancing information delivery or providingwork guidance. Hence, user interactions have to be aggregatedand mapped to predefined task categories. Withoutmachine learning tools, such an assignment has to be donemanually. The identification of suitable machine learningalgorithms is necessary in order to ensure accurate andtimely classification of the user’s context without inducingadditional workload.This paper provides a methodology for recording user interactionsand an analysis of supervised classification models,feature types and feature selection for automatically detectingthe current task and context of a user. Our analysisis based on a real world data set and shows the applicabilityof machine learning techniques.
2008

Granitzer Gisela, Granitzer Michael

Die clevere Art der Suche

e-commerce magazin, Ausgabe 7, 2008, 2008

Konferenz
2008

Juffinger A., Kern Roman, Granitzer Michael

Exploiting Cooccurrence on Corpus and Document Level for Fair Crosslanguage Retrieval

Working Notes for the CLEF 2008 Workshop, 17-19 September, Aarhus, Denmark, 2008

Konferenz
2008

Granitzer Michael, Zechner Mario, Kolbitsch J., Kemper P., In't Velt R.

Evaluation of Automatic Linking Strategies for Wikipedia Pages

Proceedings of the IADIS WWW/Internet Conference 2008, IADIS, 2008

Konferenz
2008

Sabol Vedran, Kienreich Wolfgang, Granitzer Michael

Visualisation Techniques for Analysis and Exploration of Multimedia Data

Multimedia Semantics - The Role of Metadata, ISBN: 978-3-540-77472-3, Granitzer, M., Lux, M., Spaniol, M., Springer, 2008

Buch
2008

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

Discovery and evaluation of non-taxonomic relations in domain ontologies

International Journal of Metadata, Semantics and Ontologies, 2008

Konferenz
The identification and labelling of non-hierarchical relations are among the most challenging tasks in ontology learning. This paper describes a bottom-up approach for automatically suggesting ontology link types. The presented method extracts verb vectors from semantic relations identified in the domain corpus, aggregates them by computing centroids for known relation types and stores the centroids in a central Knowledge Base (KB). Comparing verb vectors extracted from unknown relations with the stored centroids yields link-type suggestions. Domain experts evaluate these suggestions, refining the KB and constantly improving the components accuracy. Using four sample ontologies on ’energy sources’, this paper demonstrates how link-type suggestion aids the ontology design process. It also provides a statistical analysis on the accuracy and average ranking performance of Batch Learning (BL) vs. Online Learning (OL).
2008

Juffinger A., Kern Roman, Granitzer Michael

Crosslanguage Retrieval based on Wikipedia Statistics

Proc. of 8th Workshop of the Cross-Language Evaluation Forum, CLEF 2008, 17-19 September, Aarhus, Denmark, 2008

Konferenz
2008

Granitzer Michael

KnowMiner - Konzeption und Entwicklung eines generischen Wissenserschließungsframeworks

Vdm Verlag Dr. Mueller (April 2008), 2008

Buch
2008

Granitzer Michael, Seifert C., Zechner Mario

Context Resolution Strategies for Automatic Wikipedia Linking

INEX 2008 pre-proceedings, Dagstuhl, Germany, Geva, S., Kamps, J., Trotman, A., Shlomo Geva and Jaap Kamps and Andrew Trotman (Eds.), 2008

Konferenz
2008

Sabol Vedran, Andrews K., Kienreich Wolfgang, Granitzer Michael

Text Mapping: Visualising Unstructured, Structured, and Time-Based Text Collections

Intelligent Decision Technologies, IOS Press, 2008

Journal
2007

Strohmaier M., Lux M., Granitzer Michael, Scheir Peter, Liaskos S., Yu E.

How Do Users Express Goals on the Web? - An Exploration of Intentional Structures in Web Search

We Know 07 International Workshop on Collaborative Knowledge Management for Web Information Systems, in conjunction with WISE 07, , Nancy, France, 2007

Konferenz
2007

Lux M., Granitzer Michael, Kern Roman

Some Aspects of Broad Folksonomies

TIR 07 Text Information Retrieval Workshop Procceedings of 18th International Conference on Database and Expert Systems Applications (DEXA 07), IEEE Computer Society, Regensburg, Germany, 2007

Konferenz
2007

Sabol Vedran, Granitzer Michael, Kienreich Wolfgang

Fused Exploration of Temporal Developments and Topical Relationships in Heterogeneous Data Sets

3rd International Symposium of Knowledge and Argument Visualization. Proceedings of IV07, 11th International Conference Information Visualisation, IEEE Computer Society, London, UK, 2007

Konferenz
2007

Scheir Peter, Granitzer Michael, Lindstaedt Stefanie

Evaluating an Information Retrieval System for the Semantic Desktop using Standard Measures from Information Retrieval

Lernen - Wissen - Adaption LWA 2007, 2007

Konferenz
Evaluation of information retrieval systems is a critical aspect of information retrieval research. New retrieval paradigms, as retrieval in the Semantic Web, present an additional challenge for system evaluation as no off-the-shelf test corpora for evaluation exist. This paper describes the approach taken to evaluate an information retrieval system built for the Semantic Desktop and demonstrates how standard measures from information retrieval research are employed for evaluation.
2007

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

Applying Vector Space Models to Ontology Link Type Suggestion

Proceedings of 4th IEEE International Conference on Innovations in Information Technology, Dubai, 2007, 2007

Konferenz
2007

Kröll Mark, Rath Andreas S., Weber Nicolas, Lindstaedt Stefanie , Granitzer Michael

Task Instance Classification via Graph Kernels

Mining and Learning with Graphs (MLG 07), Florenz, Italy, August 1-3, 2007, 2007

Journal
2007

Sabol Vedran, Gütl Christian, Neidhart T., Juffinger A., Klieber Hans-Werner, Granitzer Michael

Visualization Metaphors for Multi-modal Meeting

Workshop Multimedia Semantics - The Role of Metadata (WMSRM 07), Proceedings Band "Aachener Informatik Berichte", Aachen, 2007

Konferenz
The MISTRAL system, a service oriented architecture for semanticextraction of multimedia data from meeting recordings is described shortly. Itimproves on other similar systems by extracting a variety of semantic metadatafrom one media type and integrating it with concepts derived from other mediatypes, as well as by adding inference capabilities to resolve ambiguities and furtherenrich extracted data. On top of this state-of-the-art extraction functionality anumber of semantic-based, cross-modal visual applications for exploration andretrieval of extraction results were developed. Three selected applications,implemented upon the MISTRAL’s semantic application architecture, arepresented and described into detail in this paper.
2007

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

Distributed Web2.0 Crawling for Ontology Evolution

Proc.of 2nd IEEE International Conference on Digital Information Management, Lyon, 2007, 2007

Konferenz
2007

Scheir Peter, Granitzer Michael, Lindstaedt Stefanie

Evaluation of an Information Retrieval System for the Semantic Desktop using Standard Measures from Information Retrieval

Proceedings of Lernen-Wissen-Adaption, Halle/Saale, Germany, September 24-26, 2007, 2007

Konferenz
2007

Granitzer Michael, Scharl A., Weichselbraun A., Neidhart T., Wohlgenannt G.

Automated Ontology Learning and Validation using Hypothesis Testing

Proceedings of the Atlantic Web Intelligence Conference AWIC 200, Advances in Soft Computing, Springer, 2007

Konferenz
2007

Rath Andreas S., Kröll Mark, Lindstaedt Stefanie , Granitzer Michael

Low-Level Event Relationship Discovery for Knowledge Work Support

Proccedings of the 4th Conference on Professional Knowledge Management WM2007, ProKW2007, 28. - 30. März 2007, Potsdam, Germany, Gronau, N., GITO-Verlag, Berlin, 2007

Konferenz
2006

Granitzer Michael, Lindstaedt Stefanie , Tochtermann K., Kröll Mark, Rath Andreas S.

Contextual Retrieval in Knowledge Intensive Business Environments

Proceedings LWA 2006 - Lernen - Wissensentdeckung - Adaptivität, Hildesheim, Germany, October 9-11, 2006, Schaaf, M., Althoff, D., Universität Hildesheim, Hildesheim, 2006

Konferenz
Knowledge-intensive work plays an increasinglyimportant role in organisations of all types. Thiswork is characterized by a defined input and adefined output but not the way how to transformthe input to an output. Within this context, theresearch project DYONIPOS aims at encouragingthe two crucial roles in a knowledge-intensiveorganization - the process executer and the processengineer. Ad-hoc support will be providedfor the knowledge worker by synergizing the developmentof context sensitive, intelligent, andagile semantic technologies with contextual retrieval.DYONIPOS provides process executerswith guidance through business processes andjust-in-time resource support based on the currentuser context, that are the focus of this paper.
2006

Lux Mathias, Scheir Peter, Lindstaedt Stefanie , Granitzer Michael

Special Track on Advanced Semantic Technologies-Introduction

International Conference on Knowledge Management, 2006

Konferenz
2006

Kienreich Wolfgang, Granitzer Michael, Lux M.

Geospatial Anchoring of Encyclopedia Articles

Proceedings of IV06, 10th International Conference on Information Visualisation, London, England, 2006

Konferenz
2006

Reisinger D., Granitzer Michael, Lindstaedt Stefanie

Integrating Ad Hoc Processes and Standard Processes in Public Administrations

Proceedings of the OCG eGovernment Conference, Linz (Austria), 2006

Konferenz
2006

Klieber Hans-Werner, Sabol Vedran, Granitzer Michael, Kienreich Wolfgang, Kern Roman

KnowMiner - Ein Service orientiertes Knowledge Discovery Framework

GI-Edition 2006, Bonner Köllen Verlag, 2006

Konferenz
2006

Granitzer Michael

Semantic Technologies as Melting Pot for Knowledge

OCG Österreichische Computer Gesellschaft, Blumauer, A., Dösinger, G., Fundneider, T., Meindl, P., Wien, 2006

Journal
2006

Granitzer Michael

Statistische Verfahren der Textanalyse

Semantic Web - Wege zur vernetzten Wissensgesellschaft, Pellegrini, T., Blumauer, A., Springer, Berlin, Germany, 2006

Buch
2006

Rath Andreas S., Kröll Mark, Andrews K., Lindstaedt Stefanie , Granitzer Michael

Synergizing Standard and Ad-Hoc Processes

Lecture Notes in Computer Science LNAI 4333, International Conference on Practical Aspects of Knowledge Management, Springer Berlin, Berlin Heidelberg, 2006

Konferenz
In a knowledge-intensive business environment, knowledgeworkers perform their tasks in highly creative ways. This essential freedomrequired by knowledge workers often conflicts with their organization’sneed for standardization, control, and transparency. Within thiscontext, the research project DYONIPOS aims to mitigate this contradictionby supporting the process engineer with insights into the processexecuter’s working behavior. These insights constitute the basis for balancedprocess modeling. DYONIPOS provides a process engineer supportenvironment with advanced process modeling services, such as processvisualization, standard process validation, and ad-hoc process analysisand optimization services.
2006

Granitzer Michael, Sabol Vedran, Klieber Hans-Werner

MISTRAL: Service Orientierte Cross-Media Techniken zur Extraktion von Semantic aus multimedia Daten und Deren Anwendung

Inproceedings of Semantics 2005, Vienna, Trauner Verlag, 2006

Konferenz
2006

Lux M., Klieber Hans-Werner, Granitzer Michael

On the Complexity of Annotation with the High Level Metadata

Journal of Universal Knowledge Management, Graz, 2006

Journal
2006

Lux M., Granitzer Michael

Retrieval basierend auf Semantischen Metadaten

Tagungsband der Multikonferenz Wirtschaftsinformatik 2006, Passau (D), 2006

Konferenz
2006

Kienreich Wolfgang, Granitzer Michael, Sabol Vedran, Klieber Hans-Werner

Plagiarism Detection in Large Sets of Press Agency News Articles

TAKMA Workshop Procceedings of 17th International Conference on Database and Expert Systems Applications (DEXA 06), IEEE Computer Society, Krakaw, Polen, 2006

Konferenz
2006

Scheir Peter, Granitzer Michael, Lindstaedt Stefanie , Hofmair P.

The OntologyMapper plug-in: Supporting Semantic Annotation of Text-Documents by Classification

Semantic Systems From Vision to Applications - Proceedings of the SEMANTICS 2006, Vienna, Austria, November 28-30, 2006, Österreichische Computer Gesellschaft, Wien, 2006

Konferenz
In this contribution we present a tool for annotating documents, which are used for workintegratedlearning, with concepts from an ontology. To allow for annotating directly whilecreating or editing an ontology, the tool was realized as a plug-in for the ontology editor Protégé.Annotating documents with semantic metadata is a laborious task, most of the time knowledgerepresentations are created independently from the resources that should be annotated andadditionally in most work environments a high number of documents exist. To increase theefficiency of the person annotating, in our tool the process of assigning concepts to text-documentsis supported by automatic text-classification.
2005

Lux M., Granitzer Michael

Knowledge Discovery and Semantic Technologies

JUCS - Proceedings of I-Know 05, Graz, Austria, 2005

Konferenz
2005

Lux M., Granitzer Michael

Retrieval of MPEG-7 based Semantic Descriptions

BTW-Workshop „WebDB Meets IR“, Karlsruhe, 2005

Konferenz
2005

Lux M., Granitzer Michael

A Fast And Simple Path Index Based Retrieval Approach for Graph Based Semantic Descriptions

Fachberichte Informatik, Universität Koblenz, ISSN 1860-4471, Stein, B., zu Eißen, S. M., Koblenz, Germany, 2005

Konferenz
2005

Kienreich Wolfgang, Sabol Vedran, Granitzer Michael, Klieber Hans-Werner, Lux M., Sarka W.

A Visual Query Interface for a Very Large Newspaper Article Repository

Procceedings of 16th International Conference on Database and Expert Systems Applications (DEXA 05), IEEE Computer Society, Copenhagen, Denmark, 2005

Konferenz
2005

Kienreich Wolfgang, Granitzer Michael, Sabol Vedran, Klieber Hans-Werner, Lux M., Sarka W.

Visual Analysis of Search Results Obtained from Very Large Newspaper Article Repository

Proceedings of ISGI 2005, CODATA International Symposium on Generalization of Information, Berlin, Germany, 2005

Konferenz
2005

Kienreich Wolfgang, Granitzer Michael

Visualising Knowledge Webs for Encyclopedia Articles

Proceedings of the 9th International Conference on Information Visualisation (IV05), IEEE Computer Society, London, England, 2005

Konferenz
2005

Dösinger G., Granitzer Michael

Projektmanagement in der anwendungsorientierten Forschung

OnePoint Report Nr. 6 (Q4/2005), Newsletter, 2005

Journal
2005

Sabol Vedran, Granitzer Michael, Sarka W.

MISTRAL - Measurable, Intelligent and Reliable Semantic Extraction and Retrieval of Multimedia Data

2nd European Workshop on the Integration of Knowledge, Semantic and Digital Media Technologies, London, UK, 2005

Konferenz
2005

Granitzer Michael

Wissenserschließung: Pfade durch den digitalen Informationsdschungel

wissensmanagement - Das Magazin für Führungskräfte, 2005

Journal
2005

Granitzer Michael, Auer P.

Experiments With Hierarchical Text Classification

Proceedings of 9th IASTED International Conference onArtifical Intelligence, IASTED, ACTA Press, Benidorm, Spain, 2005

Konferenz
2004

Lux M., Klieber Hans-Werner, Granitzer Michael

Caliph & Emir: Semantics in Multimedia Retrieval and Annotation

19th CODATA Conference, Berlin, Berlin, 2004

Konferenz
2004

Lux M., Granitzer Michael, Kienreich Wolfgang, Sabol Vedran, Klieber Hans-Werner, Sarka W.

Cross Media Retrieval in Knowledge Discovery

Lecture Notes in Computer Science, Springer, Vienna, Austria, 2004

Konferenz
2004

Andrews K., Kienreich Wolfgang, Sabol Vedran, Granitzer Michael

The Visualisation of Large Hierarchical Document Spaces with InfoSky

Proceedings of CODATA Prague Workshop on Information Visualisation, Presentation and Design, Prague, Czech, 2004

Konferenz
2004

Granitzer Michael, Kienreich Wolfgang, Sabol Vedran, Andrews K.

Evaluating a System for Interactive Exploration of Large, Hierarchically Structured Document Repositories

InfoVis 2004, the tenth annual IEEE Symposium on Information Visualization, Austin, Texas, USA, 2004

Konferenz
2003

Andrews K., Kienreich Wolfgang, Sabol Vedran, Granitzer Michael

Interactive Poster: Visualising Large Hierarchically StructuredDocument Repositories with InfoSky

InfoVis 2003, Seattle, 2003

Konferenz
2003

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

InfoSky: Visual Exploration of Large Hierarchical Document Repositories

Proceedings of HCI 2003 International, Creta, Greece, 2003

Konferenz
2003

Kienreich Wolfgang, Sabol Vedran, Granitzer Michael, Kappe F., Andrews K.

InfoSky: A System for Visual Exploration of Very Large, Hierarchically Structured Knowledge Spaces

Proceedings der GI Workshopwoche, Workshop der Fachgruppe Wissensmanagement, Karlsruhe, 2003

Konferenz
2003

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

Enhancing Environmental Search Engines with Information Landscapes

Proceedings of International Symposium on Environmental Software Systems, Semmering, Austria, 2003

Konferenz
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

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

Topic Cascades: An interactive interface for exploration of clustered web search results based on the SVG standard

In Proceedings of the Seventh International Conference on Knowledge-Based Intelligent Information, Springer, Oxford, England, 2003

Konferenz
2003

Granitzer Michael, Kienreich Wolfgang, Sabol Vedran, Dösinger G.

WebRat: Supporting Agile Knowledge Retrieval through Dynamic, Incremental Clustering and Automatic Labelling of Web Search Result Sets

Proceedings of 1st IEEE Workshop on Knowledge Management for Distributed, Agile Processes, Linz, Austria, 2003

Konferenz
2002

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

Applications of a Lightweight, Web-Based Retrieval, Clustering and Visualisation Framework

Proceedings of the 4th International Conference on Practical Aspects of Knowledge Management, Vienna Austria, 2002

Konferenz
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

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

InfoSky: Eine neue Technologie zur Erforschung großer, hierarchischer Wissensräume

KnowTech 2002, 4. Konferenz zum Einsatz von Knowledge Management in Wirtschaft und Verwaltung (www.knowtech2002.de), München,Germany, 2002

Konferenz
2002

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

Intelligent Maps and Information Landscapes: Two new Approaches to support Search and Retrieval of Environmental Information Objects.

Proceedings of the International Symposium on Environmental Informatics, Vienna Austria, 2002

Konferenz
2002

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

WebRat

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

Journal
Kontakt Karriere

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