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

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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.
2011

Granitzer Michael, Lindstaedt Stefanie

Web 2.0: Applications and Mechanisms J.UCS Special Issue

JUCS - Journal of Universal Computing, 2011

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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

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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

Granitzer Michael, Lindstaedt Stefanie

Knowledge Work : Knowledge Worker Productivity , Collaboration and User Support

J.UCS - Journal of Universal Computer Science, 2011

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2011

Granitzer Michael, Lindstaedt Stefanie

Semantic Web: Theory and Applications

Journal of Universal Computer Science, 2011

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2011

Granitzer Michael, Kienreich Wolfgang, Seifert Christin

Visualizing Text Classification Models with Voronoi Word Clouds

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

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2011

Granitzer Michael, Tochtermann Klaus

Future Internet and the Library World

ZEITSCHRIFT FUR BIBLIOTHEKSWESEN UND BIBLIOGRAPHIE, 2011

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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

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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

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

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2010

Kern Roman, Seifert Christin, Granitzer Michael

A Hybrid System for German Encyclopedia Alignment

International Journal on Digital Libraries, Springer, 2010

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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

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

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2010

Klieber Hans-Werner, Granitzer Michael, Gaisbauer M.

Semantically enhanced Software Documentation Processes

Serdica Journal of Computing, 2010

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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.
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

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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

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

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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

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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

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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

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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

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2006

Granitzer Michael

Semantic Technologies as Melting Pot for Knowledge

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

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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

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2005

Granitzer Michael

Wissenserschließung: Pfade durch den digitalen Informationsdschungel

wissensmanagement - Das Magazin für Führungskräfte, 2005

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2005

Dösinger G., Granitzer Michael

Projektmanagement in der anwendungsorientierten Forschung

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

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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

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2002

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

WebRat

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

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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

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