Beitrag in einem Tagungsband
Mining Association Rules in Folksonomies
Details zur Publikation
Autor(inn)en: | Jäschke, R.; Hotho, A.; Stumme, G.; Schmitz, C. |
Herausgeber: | Batagelj, Vladimir; Bock, Hans-Hermann; Ferligoj, Anuška ; Žiberna, Aleš |
Verlag: | Springer |
Verlagsort / Veröffentlichungsort: | Berlin, Heidelberg |
Publikationsjahr: | 2006 |
Seitenbereich: | 261-270 |
Buchtitel: | Data Science and Classification: Proc. of the 10th IFCS Conf. |
Titel der Buchreihe: | Studies in Classification, Data Analysis, and Knowledge Organization |
ISBN: | 978-3-540-34415-5 |
eISBN: | 978-3-540-34416-2 |
Zusammenfassung, Abstract
Social bookmark tools are rapidly emerging on the Web. In suchsystems users are setting up lightweight conceptual structurescalled folksonomies. These systems provide currently relatively fewstructure. We discuss in this paper, how association rule miningcan be adopted to analyze and structure folksonomies, and how the results can be usedfor ontology learning and supporting emergent semantics. Wedemonstrate our approach on a large scale dataset stemming from anonline system.
Social bookmark tools are rapidly emerging on the Web. In suchsystems users are setting up lightweight conceptual structurescalled folksonomies. These systems provide currently relatively fewstructure. We discuss in this paper, how association rule miningcan be adopted to analyze and structure folksonomies, and how the results can be usedfor ontology learning and supporting emergent semantics. Wedemonstrate our approach on a large scale dataset stemming from anonline system.
Schlagwörter
association, folksonomy, iccs_example, l3s, mining, ol_tut2010, rule, trias_example
