Atzmueller, M.; Lemmerich, F.; Krause, B. & Hotho, A.: Towards Understanding Spammers - Discovering Local Patterns for Concept Characterization and Description. In: Knobbe, J. F. A. (Hrsg.):
Proc. LeGo-09: From Local Patterns to Global Models, Workshop at the 2009 European Conference on Machine Learning and Principles and Practice of Knowledge Discovery in Databases. 2009
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Atzmueller, M.; Lemmerich, F.; Krause, B. & Hotho, A.: Who are the Spammers? Understandable Local Patterns for Concept Description.
7th Conference on Computer Methods and Systems. Krakow, Poland: 2009
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Benz, D.; Krause, B.; Kumar, G. P.; Hotho, A. & Stumme, G.: Characterizing Semantic Relatedness of Search Query Terms.
Proceedings of the 1st Workshop on Explorative Analytics of Information Networks (EIN2009). Bled, Slovenia: 2009
[BibTeX]
Benz, D.; Eisterlehner, F.; Hotho, A.; Jäschke, R.; Krause, B. & Stumme, G.: Managing publications and bookmarks with BibSonomy. In: Cattuto, C.; Ruffo, G. & Menczer, F. (Hrsg.):
HT '09: Proceedings of the 20th ACM Conference on Hypertext and Hypermedia. New York, NY, USA: ACM, 2009, S. 323-324
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[BibTeX]
In this demo we present BibSonomy, a social bookmark and publication sharing system.
Hotho, A.; Jäschke, R.; Benz, D.; Grahl, M.; Krause, B.; Schmitz, C. & Stumme, G.: Social Bookmarking am Beispiel BibSonomy. In: Blumauer, A. & Pellegrini, T. (Hrsg.):
Social Semantic Web. Berlin, Heidelberg: Springer, 2009X.media.press , S. 363-391
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BibSonomy ist ein kooperatives Verschlagwortungssystem (Social Bookmarking System), betrieben vom Fachgebiet Wissensverarbeitung
der Universität Kassel. Es erlaubt das Speichern und Organisieren von Web-Lesezeichen und Metadaten für wissenschaftlichePublikationen. In diesem Beitrag beschreiben wir die von BibSonomy bereitgestellte Funktionalität, die dahinter stehende Architektursowie das zugrunde liegende Datenmodell. Ferner erläutern wir Anwendungsbeispiele und gehen auf Methoden zur Analyse der in BibSonomy und ähnlichen Systemen enthaltenen Daten ein.
Jäschke, R.; Eisterlehner, F.; Hotho, A. & Stumme, G.: Testing and Evaluating Tag Recommenders in a Live System. In: Benz, D. & Janssen, F. (Hrsg.):
Workshop on Knowledge Discovery, Data Mining, and Machine Learning. 2009, S. 44 -51
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The challenge to provide tag recommendations for collaborative tagging systems has attracted quite some attention of researchers lately. However, most research focused on evaluation and development of appropriate methods rather than tackling the practical challenges of how to integrate recommendation methods into real tagging systems, record and evaluate their performance. In this paper we describe the tag recommendation framework we developed for our social bookmark and publication sharing system BibSonomy. With the intention to develop, test, and evaluate recommendation algorithms and supporting cooperation with researchers, we designed the framework to be easily extensible, open for a variety of methods, and usable independent from BibSonomy. Furthermore, this paper presents an evaluation of two exemplarily deployed recommendation methods, demonstrating the power of the framework.
Markines, B.; Cattuto, C.; Menczer, F.; Benz, D.; Hotho, A. & Stumme, G.: Evaluating Similarity Measures for Emergent Semantics of Social Tagging.
18th International World Wide Web Conference. 2009, S. 641-641
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Social bookmarking systems and their emergent information structures, known as folksonomies, are increasingly important data sources for Semantic Web applications. A key question for harvesting semantics from these systems is how to extend and adapt traditional notions of similarity to folksonomies, and which measures are best suited for applications such as navigation support, semantic search, and ontology learning. Here we build an evaluation framework to compare various general folksonomy-based similarity measures derived from established information-theoretic, statistical, and practical measures. Our framework deals generally and symmetrically with users, tags, and resources. For evaluation purposes we focus on similarity among tags and resources, considering different ways to aggregate annotations across users. After comparing how tag similarity measures predict user-created tag relations, we provide an external grounding by user-validated semantic proxies based on WordNet and the Open Directory. We also investigate the issue of scalability. We ?nd that mutual information with distributional micro-aggregation across users yields the highest accuracy, but is not scalable; per-user projection with collaborative aggregation provides the best scalable approach via incremental computations. The results are consistent across resource and tag similarity.
Voss, J.; Hotho, A. & Jäschke, R.: Mapping Bibliographic Records with Bibliographic Hash Keys. In: Kuhlen, R. (Hrsg.):
Information: Droge, Ware oder Commons?. Verlag Werner Hülsbusch, 2009Proceedings of the ISI
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This poster presents a set of hash keys for bibliographic records called bibkeys. Unlike other methods of duplicate detection, bibkeys can directly be calculated from a set of basic metadata fields (title, authors/editors, year). It is shown how bibkeys are used to map similar bibliographic records in BibSonomy and among distributed library catalogs and other distributed databases.