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SUMMARY:NLP Reading Group: Collaborative topic modeling for recommending s
 cientific articles - Jimme Jardine (University of Cambridge)
DTSTART:20120216T140000Z
DTEND:20120216T150000Z
UID:TALK36498@talks.cam.ac.uk
CONTACT:Jimme Jardine
DESCRIPTION:Jimme will be talking about:\n\nResearchers have access to lar
 ge online archives of scientific articles. As a consequence\, finding rele
 vant papers has become more difficult. Newly formed online communities of 
 researchers sharing citations provides a new way to solve this problem. In
  this paper\, we develop an algorithm to recommend scientific articles to 
 users of an online community. Our approach combines the merits of traditio
 nal collaborative filtering and probabilistic topic modeling. It provides 
 an interpretable latent structure for users and items\, and can form recom
 mendations about both existing and newly published articles. We study a la
 rge subset of data from CiteULike\, a bibliography sharing service\, and s
 how that our algorithm provides a more effective recommender system than t
 raditional collaborative filtering.\n\n@inproceedings{wang2011collaborativ
 e\,\n  title={Collaborative topic modeling for recommending scientific art
 icles}\,\n  author={Wang\, C. and Blei\, D.M.}\,\n  booktitle={Proceedings
  of the 17th ACM SIGKDD international conference on Knowledge discovery an
 d data mining}\,\n  pages={448--456}\,\n  year={2011}\,\n  organization={A
 CM}\n}
LOCATION:GS15\, Computer Laboratory
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