QuickSearch:   Number of matching entries: 0.

Search Settings

    AuthorTitleYearJournal/ProceedingsReftypeDOI/URL
    Berendt, B., Hotho, A. & Stumme, G. Bridging the Gap--Data Mining and Social Network Analysis for Integrating Semantic Web and Web 2.0 2010 Web Semantics: Science, Services and Agents on the World Wide Web
    Vol. 8(2-3), pp. 95 - 96 
    article DOI URL 
    BibTeX:
    @article{berendt2010bridging,
      author = {Berendt, Bettina and Hotho, Andreas and Stumme, Gerd},
      title = {Bridging the Gap--Data Mining and Social Network Analysis for Integrating Semantic Web and Web 2.0},
      journal = {Web Semantics: Science, Services and Agents on the World Wide Web},
      year = {2010},
      volume = {8},
      number = {2-3},
      pages = {95 - 96},
      note = {Bridging the Gap--Data Mining and Social Network Analysis for Integrating Semantic Web and Web 2.0; The Future of Knowledge Dissemination: The Elsevier Grand Challenge for the Life Sciences},
      url = {http://www.sciencedirect.com/science/article/B758F-4YXK4HW-1/2/4cb514565477c54160b5e6eb716c32d7},
      doi = {DOI: 10.1016/j.websem.2010.04.008}
    }
    
    Hotho, A., Benz, D., Eisterlehner, F., Jäschke, R., Krause, B., Schmitz, C. & Stumme, G. Publikationsmanagement mit BibSonomy -- ein Social-Bookmarking-System für Wissenschaftler 2010 HMD -- Praxis der Wirtschaftsinformatik
    Vol. Heft 271, pp. 47-58 
    article  
    Abstract: Kooperative Verschlagwortungs- bzw. Social-Bookmarking-Systeme wie Delicious, Mister Wong oder auch unser eigenes System BibSonomy erfreuen sich immer größerer Beliebtheit und bilden einen zentralen Bestandteil des heutigen Web 2.0. In solchen Systemen erstellen Nutzer leichtgewichtige Begriffssysteme, sogenannte Folksonomies, die die Nutzerdaten strukturieren. Die einfache Bedienbarkeit, die Allgegenwärtigkeit, die ständige Verfügbarkeit, aber auch die Möglichkeit, Gleichgesinnte spontan in solchen Systemen zu entdecken oder sie schlicht als Informationsquelle zu nutzen, sind Gründe für ihren gegenwärtigen Erfolg. Der Artikel führt den Begriff Social Bookmarking ein und diskutiert zentrale Elemente (wie Browsing und Suche) am Beispiel von BibSonomy anhand typischer Arbeitsabläufe eines Wissenschaftlers. Wir beschreiben die Architektur von BibSonomy sowie Wege der Integration und Vernetzung von BibSonomy mit Content-Management-Systemen und Webauftritten. Der Artikel schließt mit Querbezügen zu aktuellen Forschungsfragen im Bereich Social Bookmarking.
    BibTeX:
    @article{hotho2010publikationsmanagement,
      author = {Hotho, Andreas and Benz, Dominik and Eisterlehner, Folke and Jäschke, Robert and Krause, Beate and Schmitz, Christoph and Stumme, Gerd},
      title = {Publikationsmanagement mit BibSonomy -- ein Social-Bookmarking-System für Wissenschaftler},
      journal = {HMD -- Praxis der Wirtschaftsinformatik},
      year = {2010},
      volume = {Heft 271},
      pages = {47-58}
    }
    
    Körner, C., Benz, D., Strohmaier, M., Hotho, A. & Stumme, G. Stop Thinking, start Tagging - Tag Semantics emerge from Collaborative Verbosity 2010 Proceedings of the 19th International World Wide Web Conference (WWW 2010)  inproceedings URL 
    Abstract: Recent research provides evidence for the presence of emergent semantics in collaborative tagging systems. While several methods have been proposed, little is known about the factors that influence the evolution of semantic structures in these systems. A natural hypothesis is that the quality of the emergent semantics depends on the pragmatics of tagging: Users with certain usage patterns might contribute more to the resulting semantics than others. In this work, we propose several measures which enable a pragmatic differentiation of taggers by their degree of contribution to emerging semantic structures. We distinguish between categorizers, who typically use a small set of tags as a replacement for hierarchical classification schemes, and describers, who are annotating resources with a wealth of freely associated, descriptive keywords. To study our hypothesis, we apply semantic similarity measures to 64 different partitions of a real-world and large-scale folksonomy containing different ratios of categorizers and describers. Our results not only show that ‘verbose’ taggers are most useful for the emergence of tag semantics, but also that a subset containing only 40% of the most ‘verbose’ taggers can produce results that match and even outperform the semantic precision obtained from the whole dataset. Moreover, the results suggest that there exists a causal link between the pragmatics of tagging and resulting emergent semantics. This work is relevant for designers and analysts of tagging systems interested (i) in fostering the semantic development of their platforms, (ii) in identifying users introducing “semantic noise”, and (iii) in learning ontologies.
    BibTeX:
    @inproceedings{koerner2010thinking,
      author = {Körner, Christian and Benz, Dominik and Strohmaier, Markus and Hotho, Andreas and Stumme, Gerd},
      title = {Stop Thinking, start Tagging - Tag Semantics emerge from Collaborative Verbosity},
      booktitle = {Proceedings of the 19th International World Wide Web Conference (WWW 2010)},
      publisher = {ACM},
      year = {2010},
      url = {http://www.kde.cs.uni-kassel.de/benz/papers/2010/koerner2010thinking.pdf}
    }
    
    Mitzlaff, F., Benz, D., Stumme, G. & Hotho, A. Visit me, click me, be my friend: An analysis of evidence networks of user relationships in Bibsonomy 2010 Proceedings of the 21st ACM conference on Hypertext and hypermedia  inproceedings  
    BibTeX:
    @inproceedings{eisterlehner2010visit,
      author = {Mitzlaff, Folke and Benz, Dominik and Stumme, Gerd and Hotho, Andreas},
      title = {Visit me, click me, be my friend: An analysis of evidence networks of user relationships in Bibsonomy},
      booktitle = {Proceedings of the 21st ACM conference on Hypertext and hypermedia},
      year = {2010}
    }
    
    Cattuto, C., Benz, D., Hotho, A. & Stumme, G. Semantic Grounding of Tag Relatedness in Social Bookmarking Systems 2008 The Semantic Web - ISWC 2008
    Vol. 5318The Semantic Web - ISWC 2008, pp. 615-631 
    incollection DOI URL 
    Abstract: Collaborative tagging systems have nowadays become important data sources for populating semantic web applications. For tasks like synonym detection and discovery of concept hierarchies, many researchers introduced measures of tag similarity. Even though most of these measures appear very natural, their design often seems to be rather ad hoc, and the underlying assumptions on the notion of similarity are not made explicit. A more systematic characterization and validation of tag similarity in terms of formal representations of knowledge is still lacking. Here we address this issue and analyze several measures of tag similarity: Each measure is computed on data from the social bookmarking system del.icio.us and a semantic grounding is provided by mapping pairs of similar tags in the folksonomy to pairs of synsets in Wordnet, where we use validated measures of semantic distance to characterize the semantic relation between the mapped tags. This exposes important features of the investigated similarity measures and indicates which ones are better suited in the context of a given semantic application.
    BibTeX:
    @incollection{tagging-cattuto,
      author = {Cattuto, Ciro and Benz, Dominik and Hotho, Andreas and Stumme, Gerd},
      title = {Semantic Grounding of Tag Relatedness in Social Bookmarking Systems},
      booktitle = {The Semantic Web - ISWC 2008},
      journal = {The Semantic Web - ISWC 2008},
      publisher = {Springer Berlin / Heidelberg},
      year = {2008},
      volume = {5318},
      pages = {615--631},
      url = {http://tagora-project.eu/wp-content/2009/09/cattuto_iswc2008.pdf},
      doi = {http://dx.doi.org/10.1007/978-3-540-88564-1\_39}
    }
    
    Hoser, B., Hotho, A., Jäschke, R., Schmitz, C. & Stumme, G. Semantic Network Analysis of Ontologies 2006
    Vol. 4011The Semantic Web: Research and Applications, pp. 514-529 
    inproceedings URL 
    Abstract: A key argument for modeling knowledge in ontologies is the easy
    -use and re-engineering of the knowledge. However, beside
    nsistency checking, current ontology engineering tools provide
    ly basic functionalities for analyzing ontologies. Since
    tologies can be considered as (labeled, directed) graphs, graph
    alysis techniques are a suitable answer for this need. Graph
    alysis has been performed by sociologists for over 60 years, and
    sulted in the vivid research area of Social Network Analysis
    NA). While social network structures in general currently receive
    gh attention in the Semantic Web community, there are only very
    w SNA applications up to now, and virtually none for analyzing the
    ructure of ontologies.

    e illustrate in this paper the benefits of applying SNA to
    tologies and the Semantic Web, and discuss which research topics
    ise on the edge between the two areas. In particular, we discuss
    w different notions of centrality describe the core content and
    ructure of an ontology. From the rather simple notion of degree
    ntrality over betweenness centrality to the more complex
    genvector centrality based on Hermitian matrices, we illustrate
    e insights these measures provide on two ontologies, which are
    fferent in purpose, scope, and size.

    BibTeX:
    @inproceedings{hoser2006semantic,
      author = {Hoser, Bettina and Hotho, Andreas and Jäschke, Robert and Schmitz, Christoph and Stumme, Gerd},
      title = {Semantic Network Analysis of Ontologies},
      booktitle = {The Semantic Web: Research and Applications},
      publisher = {Springer},
      year = {2006},
      volume = {4011},
      pages = {514-529},
      url = {http://www.kde.cs.uni-kassel.de/stumme/papers/2006/hoser2006semantic.pdf}
    }
    
    Strube, M. & Ponzetto, S.P. WikiRelate! computing semantic relatedness using wikipedia 2006 proceedings of the 21st national conference on Artificial intelligence - Volume 2, pp. 1419-1424  inproceedings URL 
    Abstract: Wikipedia provides a knowledge base for computing word relatedness in a more structured fashion than a search engine and with more coverage than WordNet. In this work we present experiments on using Wikipedia for computing semantic relatedness and compare it to WordNet on various benchmarking datasets. Existing relatedness measures perform better using Wikipedia than a baseline given by Google counts, and we show that Wikipedia outperforms WordNet when applied to the largest available dataset designed for that purpose. The best results on this dataset are obtained by integrating Google, WordNet and Wikipedia based measures. We also show that including Wikipedia improves the performance of an NLP application processing naturally occurring texts.
    BibTeX:
    @inproceedings{Strube:2006:WCS:1597348.1597414,
      author = {Strube, Michael and Ponzetto, Simone Paolo},
      title = {WikiRelate! computing semantic relatedness using wikipedia},
      booktitle = {proceedings of the 21st national conference on Artificial intelligence - Volume 2},
      publisher = {AAAI Press},
      year = {2006},
      pages = {1419--1424},
      url = {http://dl.acm.org/citation.cfm?id=1597348.1597414}
    }
    
    Stumme, G., Hotho, A. & Berendt, B. Semantic Web Mining - State of the Art and Future Directions 2006 Journal of Web Semantics
    Vol. 4(2), pp. 124-143 
    article URL 
    Abstract: SemanticWeb Mining aims at combining the two fast-developing research areas SemanticWeb andWeb Mining.
    is survey analyzes the convergence of trends from both areas: an increasing number of researchers is working on
    proving the results ofWeb Mining by exploiting semantic structures in theWeb, and they make use ofWeb Mining
    chniques for building the Semantic Web. Last but not least, these techniques can be used for mining the Semantic
    b itself.
    e Semantic Web is the second-generation WWW, enriched by machine-processable information which supports
    e user in his tasks. Given the enormous size even of today’s Web, it is impossible to manually enrich all of
    ese resources. Therefore, automated schemes for learning the relevant information are increasingly being used.
    b Mining aims at discovering insights about the meaning of Web resources and their usage. Given the primarily
    ntactical nature of the data being mined, the discovery of meaning is impossible based on these data only. Therefore,
    rmalizations of the semantics of Web sites and navigation behavior are becoming more and more common.
    rthermore, mining the Semantic Web itself is another upcoming application. We argue that the two areas Web
    ning and Semantic Web need each other to fulfill their goals, but that the full potential of this convergence is not
    t realized. This paper gives an overview of where the two areas meet today, and sketches ways of how a closer
    tegration could be profitable.
    BibTeX:
    @article{jws2006Semantic,
      author = {Stumme, Gerd and Hotho, Andreas and Berendt, Bettina},
      title = {Semantic Web Mining - State of the Art and Future Directions},
      journal = {Journal of Web Semantics},
      publisher = {Elsevier},
      year = {2006},
      volume = {4},
      number = {2},
      pages = {124-143},
      url = {http://www.kde.cs.uni-kassel.de/stumme/papers/2006/stumme2006semantic.pdf}
    }
    
    Berendt, B., Hotho, A., Mladenic, D., van Someren, M., Spiliopoulou, M. & Stumme, G. A Roadmap for Web Mining: From Web to Semantic Web. 2004
    Vol. 3209Web Mining: From Web to Semantic Web, pp. 1-22 
    inproceedings URL 
    Abstract: The purpose of Web mining is to develop methods and systems for discovering models of objects and processes on the World Wide Web and for web-based systems that show adaptive performance. Web Mining integrates three parent areas: Data Mining (we use this term here also for the closely related areas of Machine Learning and Knowledge Discovery), Internet technology and World Wide Web, and for the more recent Semantic Web. The World Wide Web has made an enormous amount of information electronically accessible. The use of email, news and markup languages like HTML allow users to publish and read documents at a world-wide scale and to communicate via chat connections, including information in the form of images and voice records. The HTTP protocol that enables access to documents over the network via Web browsers created an immense improvement in communication and access to information. For some years these possibilities were used mostly in the scientific world but recent years have seen an immense growth in popularity, supported by the wide availability of computers and broadband communication. The use of the internet for other tasks than finding information and direct communication is increasing, as can be seen from the interest in ldquoe-activitiesrdquo such as e-commerce, e-learning, e-government, e-science.
    BibTeX:
    @inproceedings{berendt2004roadmap,
      author = {Berendt, Bettina and Hotho, Andreas and Mladenic, Dunja and van Someren, Maarten and Spiliopoulou, Myra and Stumme, Gerd},
      title = {A Roadmap for Web Mining: From Web to Semantic Web.},
      booktitle = {Web Mining: From Web to Semantic Web},
      publisher = {Springer},
      year = {2004},
      volume = {3209},
      pages = {1-22},
      url = {http://www.kde.cs.uni-kassel.de/stumme/papers/2004/berendt2004roadmap.pdf}
    }
    
    Berendt, B., Hotho, A. & Stumme, G. Usage Mining for and on the Semantic Web 2004 Data Mining Next Generation Challenges and Future Directions, pp. 461-481  incollection URL 
    Abstract: Semantic Web Mining aims at combining the two fast-developing
    search areas Semantic Web and Web Mining.
    b Mining aims at discovering insights about the meaning of Web
    sources and their usage. Given the primarily syntactical nature
    data Web mining operates on, the discovery of meaning is
    possible based on these data only. Therefore, formalizations of
    e semantics of Web resources and navigation behavior are
    creasingly being used. This fits exactly with the aims of the
    mantic Web: the Semantic Web enriches the WWW by
    chine-processable information which supports the user in his
    sks. In this paper, we discuss the interplay of the Semantic Web
    th Web Mining, with a specific focus on usage mining.
    BibTeX:
    @incollection{berendt04usage,
      author = {Berendt, Bettina and Hotho, Andreas and Stumme, Gerd},
      title = {Usage Mining for and on the Semantic Web},
      booktitle = {Data Mining  Next Generation Challenges and Future Directions},
      publisher = {AAAI Press},
      year = {2004},
      pages = {461-481},
      url = {http://www.kde.cs.uni-kassel.de/stumme/papers/2004/berendt04usage.pdf}
    }
    
    Web Mining: From Web to Semantic Web, First European Web Mining Forum, EMWF 2003, Cavtat-Dubrovnik, Croatia, September 22, 2003, Revised Selected and Invited Papers 2004
    Vol. 3209 
    proceedings URL 
    BibTeX:
    @proceedings{berendt2004web,,
      title = {Web Mining: From Web to Semantic Web, First European Web
    
    Mining Forum, EMWF 2003, Cavtat-Dubrovnik, Croatia, September
    22, 2003, Revised Selected and Invited Papers}, publisher = {Springer}, year = {2004}, volume = {3209}, note = {http://km.aifb.uni-karlsruhe.de/ws/ewmf03/}, url = {http://springerlink.metapress.com/content/unvvag26dttf/} }
    Tane, J., Schmitz, C. & Stumme, G. Semantic resource management for the web: an e-learning application 2004 Proc. 13th International World Wide Web Conference (WWW 2004), pp. 1-10  inproceedings URL 
    BibTeX:
    @inproceedings{tane04semantic,
      author = {Tane, Julien and Schmitz, Christoph and Stumme, Gerd},
      title = {Semantic resource management for the web: an e-learning application},
      booktitle = {Proc. 13th International World Wide Web Conference (WWW 2004)},
      year = {2004},
      pages = {1-10},
      url = {http://www.www2004.org/proceedings/docs/2p1.pdf}
    }
    
    Agarwal, S., Fankhauser, P., Gonzalez-Ollala, J., Hartmann, J., Hollfelder, S., Jameson, A., Klink, S., Lehti, P., Ley, M., Rabbidge, E., Schwarzkopf, E., Shrestha, N., Stojanovic, N., Studer, R., Stumme, G. & Walter, B. Semantic Methods and Tools for Information Portals 2003
    Vol. 34INFORMATIK 2003 -- Innovative Informatikanwendungen (Band 1), pp. 116-131 
    inproceedings URL 
    Abstract: The paper describes a set of approaches for representing and
    cessing information within a semantically structured information
    rtal, while offering the possibility to integrate own
    formation. It discusses research performed within the project
    emantic Methods and Tools for Information Portals (SemIPort)'.
    particular, it focuses on (1) the development of scalable
    oring, processing and querying methods for semantic data, (2)
    sualization and browsing of complex data inventories, (3)
    rsonalization and agent-based interaction, and (4) the
    hancement of web mining approaches for use within a
    mantics-based portal.
    BibTeX:
    @inproceedings{agarwal03semantic,
      author = {Agarwal, Sudhir and Fankhauser, Peter and Gonzalez-Ollala, Jorge and Hartmann, Jens and Hollfelder, Silvia and Jameson, Anthony and Klink, Stefan and Lehti, Patrick and Ley, Michael and Rabbidge, Emma and Schwarzkopf, Eric and Shrestha, Nitesh and Stojanovic, Nenad and Studer, Rudi and Stumme, Gerd and Walter, Bernd},
      title = {Semantic Methods and Tools for Information Portals},
      booktitle = {INFORMATIK 2003 -- Innovative Informatikanwendungen (Band 1)},
      publisher = {Gesellschaft für Informatik},
      year = {2003},
      volume = {34},
      pages = {116-131},
      url = {http://www.kde.cs.uni-kassel.de/stumme/papers/2003/agarwal2003semantic.pdf}
    }
    
    Hotho, A., Staab, S. & Stumme, G. Text Clustering Based on Background Knowledge 2003
    Vol. 425 
    techreport URL 
    Abstract: Text document clustering plays an important role in providing intuitive
    vigation and browsing mechanisms by organizing large amounts of information
    to a small number of meaningful clusters. Standard partitional or agglomerative
    ustering methods efficiently compute results to this end.
    wever, the bag of words representation used for these clustering methods is often
    satisfactory as it ignores relationships between important terms that do not
    -occur literally. Also, it is mostly left to the user to find out why a particular partitioning
    s been achieved, because it is only specified extensionally. In order to
    al with the two problems, we integrate background knowledge into the process of
    ustering text documents.
    rst, we preprocess the texts, enriching their representations by background knowledge
    ovided in a core ontology — in our application Wordnet. Then, we cluster
    e documents by a partitional algorithm. Our experimental evaluation on Reuters
    wsfeeds compares clustering results with pre-categorizations of news. In the experiments,
    provements of results by background knowledge compared to the baseline
    n be shown for many interesting tasks.
    cond, the clustering partitions the large number of documents to a relatively small
    mber of clusters, which may then be analyzed by conceptual clustering. In our approach,
    applied Formal Concept Analysis. Conceptual clustering techniques are
    own to be too slow for directly clustering several hundreds of documents, but they
    ve an intensional account of cluster results. They allow for a concise description
    commonalities and distinctions of different clusters. With background knowledge
    ey even find abstractions like “food” (vs. specializations like “beef” or “corn”).
    us, in our approach, partitional clustering reduces first the size of the problem
    ch that it becomes tractable for conceptual clustering, which then facilitates the
    derstanding of the results.
    BibTeX:
    @techreport{hotho03textclustering,
      author = {Hotho, Andreas and Staab, Steffen and Stumme, Gerd},
      title = {Text Clustering Based on Background Knowledge},
      year = {2003},
      volume = {425},
      url = {http://www.kde.cs.uni-kassel.de/stumme/papers/2003/hotho2003text.pdf}
    }
    
    Semantic Web Mining. Proc. of the Semantic Web Mining Workshop of the 13th Europ. Conf. on Machine Learning (ECML'02) / 6th Europ. Conf. on Principles and Practice of Knowledge Discovery in Databases (PKDD'02) 2002   proceedings URL 
    BibTeX:
    @proceedings{berendt02semantic,,
      title = {Semantic Web Mining. Proc. of the Semantic Web Mining Workshop of the 13th Europ. Conf. on
    
    Machine Learning (ECML'02) / 6th Europ. Conf. on Principles and
    Practice of Knowledge Discovery in Databases (PKDD'02)}, year = {2002}, url = {http://km.aifb.uni-karlsruhe.de/ws/semwebmine2002/online_html} }
    Berendt, B., Hotho, A. & Stumme, G. Towards Semantic Web Mining 2002 The Semantic Web -- ISWC 2002, pp. 264-278  inproceedings URL 
    BibTeX:
    @inproceedings{berendt02towards,
      author = {Berendt, B. and Hotho, A. and Stumme, G.},
      title = {Towards Semantic Web Mining},
      booktitle = {The Semantic Web -- ISWC 2002},
      publisher = {Springer},
      year = {2002},
      pages = {264-278},
      url = {http://www.kde.cs.uni-kassel.de/stumme/papers/2002/ISWC02.pdf}
    }
    
    Bozsak, E., Ehrig, M., Handschuh, S., Hotho, A., Maedche, A., Motik, B., Oberle, D., Schmitz, C., Staab, S., Stojanovic, L., Stojanovic, N., Studer, R., Stumme, G., Sure, Y., Tane, J., Volz, R. & Zacharias, V. KAON - Towards a large scale Semantic Web 2002
    Vol. 2455Proceedings of the Third International Conference on E-Commerce and Web Technologies (EC-Web 2002), Aix-en-Provence, France, pp. 304-313 
    inproceedings URL 
    BibTeX:
    @inproceedings{bozsak2002towards,
      author = {Bozsak, E. and Ehrig, Marc and Handschuh, Siegfried and Hotho, Andreas and Maedche, Alexander and Motik, Boris and Oberle, Daniel and Schmitz, Christoph and Staab, Steffen and Stojanovic, Ljiljana and Stojanovic, Nenad and Studer, Rudi and Stumme, Gerd and Sure, York and Tane, Julien and Volz, Raphael and Zacharias, Valentin},
      title = {KAON - Towards a large scale Semantic Web},
      booktitle = {Proceedings of the Third International Conference on E-Commerce and Web Technologies (EC-Web 2002), Aix-en-Provence, France},
      publisher = {Springer},
      year = {2002},
      volume = {2455},
      pages = {304-313},
      url = {http://www.aifb.uni-karlsruhe.de/WBS/ysu/publications/2002_ecweb_kaon.pdf}
    }
    
    Gonzalez-Olalla, J. & Stumme, G. Semantic Methods and Tools for Information Portals - The SemIPort Project (Project Description) 2002 Semantic Web Mining. Proc. of the Semantic Web Mining Workshop of the 13th Europ. Conf., pp. 90  inproceedings URL 
    BibTeX:
    @inproceedings{gonzalez02semantic,
      author = {Gonzalez-Olalla, J. and Stumme, G.},
      title = {Semantic Methods and Tools for Information Portals - The SemIPort Project (Project Description)},
      booktitle = {Semantic Web Mining. Proc. of the Semantic Web Mining Workshop of the 13th Europ. Conf.},
      year = {2002},
      pages = {90},
      url = {http://www.kde.cs.uni-kassel.de/stumme/papers/2002/gonzalez2002semantic.pdf}
    }
    
    Stumme, G., Berendt, B. & Hotho, A. Usage Mining for and on the Semantic Web 2002 Proc. NSF Workshop on Next Generation Data Mining, pp. 77-86  inproceedings URL 
    BibTeX:
    @inproceedings{stumme02usage,
      author = {Stumme, G. and Berendt, B. and Hotho, A.},
      title = {Usage Mining for and on the Semantic Web},
      booktitle = {Proc. NSF Workshop on Next Generation Data Mining},
      year = {2002},
      pages = {77-86},
      url = {http://www.kde.cs.uni-kassel.de/stumme/papers/2002/NSF-NGDM02.pdf}
    }
    
    Stumme, G. Using Ontologies and Formal Concept Analysis for Organizing Business Knowledge 2002 Wissensmanagement mit Referenzmodellen -- Konzepte für die Anwendungssystem- und Organisationsgestaltung, pp. 163-174  incollection URL 
    BibTeX:
    @incollection{stumme02using,
      author = {Stumme, G.},
      title = {Using Ontologies and Formal Concept Analysis for Organizing Business Knowledge},
      booktitle = {Wissensmanagement mit Referenzmodellen -- Konzepte für die Anwendungssystem- und Organisationsgestaltung},
      publisher = {Physica},
      year = {2002},
      pages = {163-174},
      url = {http://www.kde.cs.uni-kassel.de/stumme/papers/2001/REFMOD01.ps}
    }
    

    Created by JabRef on 21/07/2019.