ARKTiS - A Fast Tag Recommender System Based On Heuristics

Thomas Kleinbauer, Sebastian Germesin

In: Folke Eisterlehner, Andreas Hotho, Robert Jäschke (Hrsg.). ECML PKDD Discovery Challenge 2009. European Conference on Machine Learning and Principles and Practice of Knowledge Discovery in Databases (ECML PKDD-09) Discovery Challenge September 7-11 Bled Slovenia 497 ISBN 1613-0073 CEUR-WS 2009.


This paper describes the tag recommender system ARKTiS, our contribution to the 2009 ECML PKDD tag discovery challenge. ARKTiS consists of two separate modules for BibTEX entries and for bookmarked web pages. For generating tags, we distinguish between so-called internal and external methods, depending on whether a tag was extracted from the given information about a resource or whether additional resources were employed.

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kleinbauer_germesin_tagging_ecml09.pdf (pdf, 224 KB)

Deutsches Forschungszentrum für Künstliche Intelligenz
German Research Center for Artificial Intelligence