%0 Conference Paper %1 ju2009weighting %A Ju, Sanghun %A Hwang, Kyu-Baek %B ECML PKDD Discovery Challenge 2009 (DC09) %C Bled, Slovenia %D 2009 %E Eisterlehner, Folke %E Hotho, Andreas %E Jäschke, Robert %I CEUR Workshop Proceedings %K 2009 ECML09 _todo bookmarking folksonomy recommendation socialTagging %P 109--118 %T A Weighting Scheme for Tag Recommendation in Social Bookmarking Systems %U http://sunsite.informatik.rwth-aachen.de/Publications/CEUR-WS/Vol-497/ %V 497 %X Social bookmarking is an effective way for sharing knowledge about a vast amount of resources on the World Wide Web. In many social bookmarking systems, users bookmark Web resources with a set of informal tags which they think are appropriate for describing them. Hence, automatic tag recommendation for social bookmarking systems could facilitate and boost the annotation process. For the tag recommendation task, we exploited three kinds of information sources, i.e., resource descriptions, previously annotated tags on the same resource, and previously annotated tags by the same person. A filtering method for removing inappropriate candidates and a weighting scheme for combining information from multiple sources were devised and deployed for ECML PKDD Discovery Challenge 2009. F-measure values of the proposed approach are 0.17975 for task #1 and 0.32039 for task #2, respectively.

@inproceedings{ju2009weighting, abstract = {Social bookmarking is an effective way for sharing knowledge about a vast amount of resources on the World Wide Web. In many social bookmarking systems, users bookmark Web resources with a set of informal tags which they think are appropriate for describing them. Hence, automatic tag recommendation for social bookmarking systems could facilitate and boost the annotation process. For the tag recommendation task, we exploited three kinds of information sources, i.e., resource descriptions, previously annotated tags on the same resource, and previously annotated tags by the same person. A filtering method for removing inappropriate candidates and a weighting scheme for combining information from multiple sources were devised and deployed for ECML PKDD Discovery Challenge 2009. F-measure values of the proposed approach are 0.17975 for task #1 and 0.32039 for task #2, respectively.}, added-at = {2010-01-29T16:22:11.000+0100}, address = {Bled, Slovenia}, author = {Ju, Sanghun and Hwang, Kyu-Baek}, biburl = {https://www.bibsonomy.org/bibtex/2e5743fb0ebe9f604288012600772f48b/trude}, booktitle = {ECML PKDD Discovery Challenge 2009 (DC09)}, editor = {Eisterlehner, Folke and Hotho, Andreas and Jäschke, Robert}, interhash = {1a81d9e5621aacf0a43d9f11a74917d4}, intrahash = {e5743fb0ebe9f604288012600772f48b}, issn = {1613-0073}, keywords = {2009 ECML09 _todo bookmarking folksonomy recommendation socialTagging}, month = {September}, pages = {109--118}, publisher = {CEUR Workshop Proceedings}, timestamp = {2011-03-05T17:11:01.000+0100}, title = {A Weighting Scheme for Tag Recommendation in Social Bookmarking Systems}, url = {http://sunsite.informatik.rwth-aachen.de/Publications/CEUR-WS/Vol-497/}, volume = 497, year = 2009 }