Difference between revisions of "A Bookmark Recommender System based on Social Bookmarking Services and Wikipedia Categories"
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| + | | title = A Bookmark Recommender System based on Social Bookmarking Services and Wikipedia Categories | ||
| + | | date = 2013 | ||
| + | | authors = [[Takumi Yoshida]]<br />[[Ushio Inoue]] | ||
| + | | doi = 10.1109/SNPD.2013.3 | ||
| + | | link = https://dl.acm.org/citation.cfm?id=2553326 | ||
| + | }} | ||
'''A Bookmark Recommender System based on Social Bookmarking Services and Wikipedia Categories''' - scientific work related to [[Wikipedia quality]] published in 2013, written by [[Takumi Yoshida]] and [[Ushio Inoue]]. | '''A Bookmark Recommender System based on Social Bookmarking Services and Wikipedia Categories''' - scientific work related to [[Wikipedia quality]] published in 2013, written by [[Takumi Yoshida]] and [[Ushio Inoue]]. | ||
== Overview == | == Overview == | ||
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. Authors propose a new method to find similar users and to select relevant bookmarks in a social book marking service. Authors method is lightweight, because it uses a small set of important tags for each user to find useful bookmarks to recommend. Authors 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 method significantly increases the number of relevant bookmarks recommended without notable increase of irrelevant bookmarks. | 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. Authors propose a new method to find similar users and to select relevant bookmarks in a social book marking service. Authors method is lightweight, because it uses a small set of important tags for each user to find useful bookmarks to recommend. Authors 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 method significantly increases the number of relevant bookmarks recommended without notable increase of irrelevant bookmarks. | ||
Revision as of 09:40, 19 January 2020
Authors | Takumi Yoshida Ushio Inoue |
|---|---|
Publication date | 2013 |
DOI | 10.1109/SNPD.2013.3 |
Links | Original |
A Bookmark Recommender System based on Social Bookmarking Services and Wikipedia Categories - scientific work related to Wikipedia quality published in 2013, written by Takumi Yoshida and Ushio Inoue.
Overview
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. Authors propose a new method to find similar users and to select relevant bookmarks in a social book marking service. Authors method is lightweight, because it uses a small set of important tags for each user to find useful bookmarks to recommend. Authors 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 method significantly increases the number of relevant bookmarks recommended without notable increase of irrelevant bookmarks.
