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

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.
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

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

Granitzer Michael, Lindstaedt Stefanie

Knowledge Work : Knowledge Worker Productivity , Collaboration and User Support

J.UCS - Journal of Universal Computer Science, 2011

Journal
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

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.
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

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

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

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

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

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.
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

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

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

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.
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

Granitzer Michael

KnowMiner - Konzeption und Entwicklung eines generischen Wissenserschließungsframeworks

Vdm Verlag Dr. Mueller (April 2008), 2008

Buch
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 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.
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

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
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

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.
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
2004

Lux M., Klieber Hans-Werner, Granitzer Michael

Caliph & Emir: Semantics in Multimedia Retrieval and Annotation

19th CODATA Conference, Berlin, Berlin, 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

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
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

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

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

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
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
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

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

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
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
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