@article{stumme03off, title = {Off to New Shores -- Conceptual Knowledge Discovery and Processing}, author = {G. Stumme}, journal = {Intl. J. Human-Comuter Studies (IJHCS)}, month = {September}, number = 3, pages = {287-325}, volume = 59, year = 2003, url = {http://www.kde.cs.uni-kassel.de/stumme/papers/2003/stumme2003off.pdf}, comment = {alpha}, abstract = {In the last years, the main orientation of Formal Concept Analysis (FCA) has turned from mathematics towards computer science. This article provides a review of this new orientation and analyzes why and how FCA and computer science attracted each other. It discusses FCA as a knowledge representation formalism using five knowledge representation principles provided by Davis, Shrobe, and Szolovits (1993). It then studies how and why mathematics-based researchers got attracted by computer science. We will argue for continuing this trend by integrating the two research areas FCA and Ontology Engineering. The second part of the article discusses three lines of research which witness the new orientation of Formal Concept Analysis: FCA as a conceptual clustering technique and its application for supporting the merging of ontologies; the efficient computation of association rules and the structuring of the results; and the visualization and management of conceptual hierarchies and ontologies including its application in an email management system.}, biburl = {http://www.bibsonomy.org/bibtex/23ad5183ad5e15d93898a798bd5063194/stumme}, keywords = {fca concept knowledge conceptual processing Knowledge Processing OntologyHandbook discovery habilitation analysis formal 2003 FCA myown Conceptual} } @article{stumme03off, title = {Off to New Shores -- Conceptual Knowledge Discovery and Processing}, author = {G. Stumme}, journal = {Intl. J. Human-Computer Studies (IJHCS)}, month = {September}, number = 3, pages = {287-325}, volume = 59, year = 2003, url = {http://www.kde.cs.uni-kassel.de/stumme/papers/2003/stumme2003off.pdf}, comment = {alpha}, abstract = {In the last years, the main orientation of Formal Concept Analysis (FCA) has turned from mathematics towards computer science. This article provides a review of this new orientation and analyzes why and how FCA and computer science attracted each other. It discusses FCA as a knowledge representation formalism using five knowledge representation principles provided by Davis, Shrobe, and Szolovits (1993). It then studies how and why mathematics-based researchers got attracted by computer science. We will argue for continuing this trend by integrating the two research areas FCA and Ontology Engineering. The second part of the article discusses three lines of research which witness the new orientation of Formal Concept Analysis: FCA as a conceptual clustering technique and its application for supporting the merging of ontologies; the efficient computation of association rules and the structuring of the results; and the visualization and management of conceptual hierarchies and ontologies including its application in an email management system.}, biburl = {http://www.bibsonomy.org/bibtex/2cc4310197d6c258f0fd00bb09b9b6e7f/stumme}, keywords = {Knowledge Conceptual conceptual formal habilitation myown knowledge concept analysis discovery processing Processing fca 2003} } @inproceedings{hotho03explaining, title = {Explaining Text Clustering Results using Semantic Structures}, address = {Heidelberg}, author = {Andreas Hotho and Steffen Staab and Gerd Stumme}, booktitle = {Knowledge Discovery in Databases: PKDD 2003, 7th European Conference on Principles and Practice of Knowledge Discovery in Databases}, editor = {Nada Lavra\v{c} and Dragan Gamberger and Hendrik BlockeelLjupco Todorovski}, pages = {217-228}, publisher = {Springer}, series = {LNAI}, volume = 2838, year = 2003, url = {http://www.kde.cs.uni-kassel.de/stumme/papers/2003/hotho2003explaining.pdf}, comment = {alpha}, abstract = {Common text clustering techniques offer rather poor capabilities for explaining to their users why a particular result has been achieved. They have the disadvantage that they do not relate semantically nearby terms and that they cannot explain how resulting clusters are related to each other. In this paper, we discuss a way of integrating a large thesaurus and the computation of lattices of resulting clusters into common text clustering in order to overcome these two problems. As its major result, our approach achieves an explanation using an appropriate level of granularity at the concept level as well as an appropriate size and complexity of the explaining lattice of resulting clusters.}, biburl = {http://www.bibsonomy.org/bibtex/253a943b6be4b34cf4e5329d0b58e99f6/stumme}, keywords = {fca semantic myown clustering concept text formal 2003 ontologies semantics analysis} } @inproceedings{hotho03wordnet, title = {Wordnet improves text document clustering}, address = {Toronto}, author = {A Hotho and S. Staab and G. Stumme}, booktitle = {Proc. SIGIR Semantic Web Workshop}, year = 2003, url = {http://www.kde.cs.uni-kassel.de/stumme/papers/2003/hotho2003wordnet.pdf}, comment = {alpha}, biburl = {http://www.bibsonomy.org/bibtex/204c7d86337d68e4ed9ae637029c43414/stumme}, keywords = {document ir information mining discovery myown kdd data 2003 text clustering knowledge retrieval kmeans wordnet} } @inproceedings{studer03building, title = {Building and Using the Semantic Web}, address = {Osaka, Japan}, author = {Rudi Studer and Gerd Stumme and Siegfried Handschuh and Andreas Hotho and B. Motik}, booktitle = {New Trends in Knowledge Processing -- Data Mining, Semantic Web and Computational}, month = {March 10-11,}, pages = {31-34}, year = 2003, url = {http://www.kde.cs.uni-kassel.de/stumme/papers/2003/Sanken03.pdf}, comment = {alpha}, biburl = {http://www.bibsonomy.org/bibtex/2a0e7b52680f1876cdd9cd21f7cb2f95c/stumme}, keywords = {2003 kdd semantic data mining web ontologies myown} } @article{hotho03semantic, title = {Semantic Web -- State of the Art and Future Directions}, author = {Andreas Hotho and Gerd Stumme and Rudi Studer and Raphael Volz}, journal = {Künstliche Intelligenz}, number = 3, pages = {5-9}, year = 2003, url = {http://www.kde.cs.uni-kassel.de/stumme/papers/2003/KI03_Themenheft.pdf}, comment = {alpha}, abstract = {The paper presents the vision of the Se- mantic Web and describes ontologies and associated metadata as the building blocks of the SemanticWeb. Current research topics and promising application ar- eas are discussed as well.}, biburl = {http://www.bibsonomy.org/bibtex/2b5b149d07fb802ff5fffeec5e7f11fb8/stumme}, keywords = {myown 2003} } @article{cole03document, title = {Document Retrieval for Email Search and Discovery using Formal Concept Analysis}, author = {Richard J. Cole and Peter W. Eklund and Gerd Stumme}, journal = {Journal of Applied Artificial Intelligence (AAI)}, number = 3, pages = {257-280}, volume = 17, year = 2003, url = {http://www.kde.cs.uni-kassel.de/stumme/papers/2003/AAI03_emails.pdf}, comment = {alpha}, abstract = {This paper discusses an document discovery tool based on conceptual clustering by formal concept analysis. The program allows users to navigate email using a visual lattice metaphor rather than a tree. It implements a virtual file structure over email where files and entire directories can appear in multiple positions. The content and shape of the lattice formed by the conceptual ontology can assist in email discovery. The system described provides more flexibility in retrieving stored emails than what is normally available in email clients. The paper discusses how conceptual ontologies can leverage traditional document retrieval systems and aid knowledge discovery in document collections.}, biburl = {http://www.bibsonomy.org/bibtex/2473f5c2cca394fac0de61086082a09de/stumme}, keywords = {email formal concept 2003 fca retrieval analysis nepomuk search myown information} } @article{hereth03conceptual, title = {Conceptual Knowledge Discovery - a Human-Centered Approach}, author = {Joachim Hereth and Gerd Stumme and Rudolf Wille and Uta Wille}, journal = {Journal of Applied Artificial Intelligence (AAI)}, number = 3, pages = {281-301}, volume = 17, year = 2003, url = {http://www.kde.cs.uni-kassel.de/stumme/papers/2003/hereth2003conceptual.pdf}, comment = {alpha}, abstract = {In this paper we discuss Conceptual Knowledge Discovery in Databases (CKDD) as it is developing in the field of Conceptual Knowledge Processing. Conceptual Knowledge Processing is based on the mathematical theory of Formal Concept Analysis which has become a successful theory for data analysis during the last two decades. CKDD aims to support a human-centered process of discovering knowledge from data by visualizing and analyzing the conceptual structure of the data. We dicuss how the management system TOSCANA for conceptual information systems supports CKDD, and illustrate it by two applications in database marketing and flight movement analysis. Finally, we present a new tool for conceptual deviation discovery, Chianti.}, biburl = {http://www.bibsonomy.org/bibtex/2edffeb9bd2aaac559f2a6233dd49ae3b/stumme}, keywords = {discovery myown formal 2003 analysis knowledge conceptual human concept kdd fca} } @techreport{hotho03textclustering, title = {Text Clustering Based on Background Knowledge}, author = {Andreas Hotho and Steffen Staab and Gerd Stumme}, institution = {University of Karlsruhe, Institute AIFB}, type = {Technical Report }, volume = 425, year = 2003, url = {http://www.kde.cs.uni-kassel.de/stumme/papers/2003/hotho2003text.pdf}, comment = {alpha}, abstract = {Text document clustering plays an important role in providing intuitive navigation and browsing mechanisms by organizing large amounts of information into a small number of meaningful clusters. Standard partitional or agglomerative clustering methods efficiently compute results to this end. However, the bag of words representation used for these clustering methods is often unsatisfactory as it ignores relationships between important terms that do not co-occur literally. Also, it is mostly left to the user to find out why a particular partitioning has been achieved, because it is only specified extensionally. In order to deal with the two problems, we integrate background knowledge into the process of clustering text documents. First, we preprocess the texts, enriching their representations by background knowledge provided in a core ontology — in our application Wordnet. Then, we cluster the documents by a partitional algorithm. Our experimental evaluation on Reuters newsfeeds compares clustering results with pre-categorizations of news. In the experiments, improvements of results by background knowledge compared to the baseline can be shown for many interesting tasks. Second, the clustering partitions the large number of documents to a relatively small number of clusters, which may then be analyzed by conceptual clustering. In our approach, we applied Formal Concept Analysis. Conceptual clustering techniques are known to be too slow for directly clustering several hundreds of documents, but they give an intensional account of cluster results. They allow for a concise description of commonalities and distinctions of different clusters. With background knowledge they even find abstractions like “food” (vs. specializations like “beef” or “corn”). Thus, in our approach, partitional clustering reduces first the size of the problem such that it becomes tractable for conceptual clustering, which then facilitates the understanding of the results.}, biburl = {http://www.bibsonomy.org/bibtex/261d58db419af0dbc3681432588219c3d/stumme}, keywords = {clustering concept analysis fca ontologies semantic formal myown background 2003 knowledge web text} } @inproceedings{agarwal03semantic, title = {Semantic Methods and Tools for Information Portals}, address = {Bonn}, author = {Sudhir Agarwal and Peter Fankhauser and Jorge Gonzalez-Ollala and Jens Hartmann and Silvia Hollfelder and Anthony Jameson and Stefan Klink and Patrick Lehti and Michael Ley and Emma Rabbidge and Eric Schwarzkopf and Nitesh Shrestha and Nenad Stojanovic and Rudi Studer and Gerd Stumme and Bernd Walter}, booktitle = {INFORMATIK 2003 -- Innovative Informatikanwendungen (Band 1)}, editor = {K. Dittrich and W. König and A. Oberweis and K. Rannenberg and W. Wahlster}, pages = {116-131}, publisher = {Gesellschaft für Informatik}, series = {LNI}, volume = 34, year = 2003, url = {http://www.kde.cs.uni-kassel.de/stumme/papers/2003/agarwal2003semantic.pdf}, comment = {alpha}, abstract = {The paper describes a set of approaches for representing and accessing information within a semantically structured information portal, while offering the possibility to integrate own information. It discusses research performed within the project `Semantic Methods and Tools for Information Portals (SemIPort)'. In particular, it focuses on (1) the development of scalable storing, processing and querying methods for semantic data, (2) visualization and browsing of complex data inventories, (3) personalization and agent-based interaction, and (4) the enhancement of web mining approaches for use within a semantics-based portal.}, biburl = {http://www.bibsonomy.org/bibtex/28f2983e0f20c26ff98577059343f2cd4/stumme}, keywords = {myown ontologies portals 2003 semiport information informationsportale web semantic} } @inproceedings{tane03courseware, title = {The Courseware Watchdog: an Ontology-based tool for finding and organizing learning material}, author = {Julien Tane and Christoph Schmitz and Gerd Stumme and Steffen Staab and R. Studer}, booktitle = {Mobiles Lernen und Forschen - Beiträge der Fachtagung an der Universität}, editor = {Klaus David and Lutz Wegner}, month = {November}, pages = {93-104}, publisher = {Kassel University Press}, year = 2003, url = {http://www.kde.cs.uni-kassel.de/stumme/papers/2003/tane2003courseware.pdf}, comment = {alpha}, abstract = {Topics in education are changing with an ever faster pace. E-Learning resources tend to be more and more decentralised. Users need increasingly to be able to use the resources of the web. For this, they should have tools for finding and organizing information in a decentral way. In this, paper, we show how an ontology-based tool suite allows to make the most of the resources available on the web.}, biburl = {http://www.bibsonomy.org/bibtex/2850949481723b7dd03768ccd96b25cb9/stumme}, keywords = {analysis e-learning watchdog crawling eLearning p2p myown padlr 2003 ontology ontologies formal edutella fca courseware concept} } @inproceedings{ganter03creation, title = {Creation and Merging of Ontology Top-Levels}, address = {Heidelberg}, author = {Bernhard Ganter and Gerd Stumme}, booktitle = {Conceptual Structures for Knowledge Creation and Communication.}, editor = {Aldo de Moor and Wilfried Lex and Bernhard Ganter}, pages = {131-145}, publisher = {Springer}, series = {LNAI}, volume = 2746, year = 2003, url = {http://www.kde.cs.uni-kassel.de/stumme/papers/2003/ganter2003creation.pdf}, comment = {alpha}, abstract = {We provide a new method for systematically structuring the top-down level of ontologies. It is based on an interactive, top--down knowledge acquisition process, which assures that the knowledge engineer considers all possible cases while avoiding redundant acquisition. The method is suited especially for creating/merging the top part(s) of the ontologies, where high accuracy is required, and for supporting the merging of two (or more) ontologies on that level.}, biburl = {http://www.bibsonomy.org/bibtex/263bd63cb06802a5308959d611c1a017a/stumme}, keywords = {ontologies concept myown 2003 fca formal analysis merging ontology} } @inproceedings{hotho03ontologies, title = {Ontologies improve text document clustering}, address = {Melbourne, Florida}, author = {Andreas Hotho and Steffen Staab and Gerd Stumme}, booktitle = {Proceedings of the 2003 IEEE International Conference on Data Mining}, month = {November 19-22,}, pages = {541-544 (Poster}, publisher = {IEEE {C}omputer {S}ociety}, year = 2003, url = {http://www.kde.cs.uni-kassel.de/stumme/papers/2003/hotho2003ontologies.pdf}, comment = {alpha}, biburl = {http://www.bibsonomy.org/bibtex/257a39c81cff1982dbefed529be934bee/stumme}, keywords = {myown data text mining kdd 2003 clustering ontologies} } @proceedings{hotho03lehren, title = {Lehren -- Lernen -- Wissen -- Adaptivität. Workshopwoche der GI-Fachgruppen/Arbeitskreise FGML, FGWM, ABIS, AKKD}, address = {Universität Karlsruhe}, editor = {A. Hotho and G. Stumme}, month = {October 6-8,}, year = 2003, url = {http://km.aifb.uni-karlsruhe.de/ws/LLWA/}, comment = {alpha}, biburl = {http://www.bibsonomy.org/bibtex/24d0edfc20579b879777174fd5709ac4a/stumme}, keywords = {abis workshop proceedings myown karlsruhe 2003 gi fgwm fgml fgkdml akkd} } @proceedings{berendt03european, title = {Proceedings of the 1st European Web Mining Forum (EWMF 2003)}, address = {Cavtat/Dubrovnik, Croatia}, editor = {B. Berendt and A. Hotho and D. Mladeni\'c and M. van Someren and M. Spiliopoulou and G. Stumme}, month = {September 22,}, year = 2003, url = {http://km.aifb.uni-karlsruhe.de/ws/ewmf03/}, comment = {alpha}, description = {Workshop of the 14th Europ. Conf. on Machine Learning (ECML'03) / 7th Europ. Conf. on Principles and Practice of Knowledge Discovery in Databases (PKDD'03)}, biburl = {http://www.bibsonomy.org/bibtex/2b895cb34882a1cae076c752b1528aeb0/stumme}, keywords = {2003 web knowledge mining myown ewmf Mining} } @proceedings{reimer03professionelles, title = {Professionelles Wissensmanagement -- Erfahrungen und Visionen. Proc. WM 2003}, address = {Bonn}, editor = {U. Reimer and A Abecker and A. Staab and G. Stumme}, publisher = {Gesellschaft für Informatik}, series = {LNI}, volume = 28, year = 2003, url = {http://wm2003.aifb.uni-karlsruhe.de/}, comment = {alpha}, biburl = {http://www.bibsonomy.org/bibtex/2728288f09f6d0f6dc4212e0b28cd3950/stumme}, keywords = {2003 wm conference proceedings wissensmanagement tagung myown} }