Beitrag in einem Tagungsband
Tag Recommendations in Folksonomies



Details zur Publikation
Autor(inn)en:
Jäschke, R.; Marinho, B.; Hotho, A.; Schmidt-Thieme, L.; Stumme, G.
Herausgeber:
Andrzej Skowron, Dunja Mladenic, Stan Matwin, Ramon López de Mántaras, Jacek Koronacki, Joost N. Kok
Verlag:
Springer
Verlagsort / Veröffentlichungsort:
Berlin, Heidelberg
Publikationsjahr:
2007
Seitenbereich:
506-514
Buchtitel:
Knowledge Discovery in Databases: PKDD 2007, 11th European Conference on Principles and Practice of Knowledge Discovery in Databases
Titel der Buchreihe:
Lecture Notes in Computer Science
Jahrgang/Band:
4702

Zusammenfassung, Abstract
Collaborative tagging systems allow users to assign keywords—so called “tags”—to resources. Tags are used for navigation, finding resources and serendipitous browsing and thus provide an immediate benefit for users. These systems usually include tag recommendation mechanisms easing the process of finding good tags for a resource, but also consolidating the tag vocabulary across users. In practice, however, only very basic recommendation strategies are applied.In this paper we evaluate and compare two recommendation algorithms on largescale real life datasets: an adaptation of user-based collaborative filtering and a graph-based recommender built on top of FolkRank. We show that both provide better results than non-personalized baseline methods. Especially the graph-based recommender outperforms existing methods considerably.


Schlagwörter
folksonomy, l3s, recommender, tagging, wp5


Autor(inn)en / Herausgeber(innen)

Zuletzt aktualisiert 2019-25-07 um 12:12