A Bookmark Recommender System Based on Social Bookmarking Services and Wikipedia Categories

Social book marking services allow users to add bookmarks of web pages with freely chosen keywords as tags. Personalized recommender systems recommend new and useful bookmarks added by other users. We propose a new method to find similar users and to select relevant bookmarks in a social book markin...

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Vydáno v:2013 14th ACIS International Conference on Software Engineering, Artificial Intelligence, Networking and Parallel/Distributed Computing s. 409 - 413
Hlavní autoři: Yoshida, Takumi, Inoue, Ushio
Médium: Konferenční příspěvek
Jazyk:angličtina
japonština
Vydáno: IEEE 01.07.2013
Témata:
algorithm
Electronic publishing
Encyclopedias
folksonomy
Internet
recommender
Recommender systems
Tagging
Web pages
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Shrnutí:Social book marking services allow users to add bookmarks of web pages with freely chosen keywords as tags. Personalized recommender systems recommend new and useful bookmarks added by other users. We propose a new method to find similar users and to select relevant bookmarks in a social book marking service. Our method is lightweight, because it uses a small set of important tags for each user to find useful bookmarks to recommend. Our method is also powerful, because it employs the Wikipedia category database to deal with the diversity of tags among users. The evaluation using the Hatena bookmark service in Japan shows that our method significantly increases the number of relevant bookmarks recommended without notable increase of irrelevant bookmarks.
DOI:10.1109/SNPD.2013.3