Presentation	2014-02-06 Collaborative Filtering Based on Latent Dirichlet Allocation for Tweet Recommendation Reflecting User Preference Keita WATANABE, Shohei KATO,
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Abstract(in English)	Recently, Twitter attracts much attention as real time information sources. However, conventional searching methods like keyword search are not enough to acquire information about user interest from Twitter immediately, because user must type a keyword every time when they want to search. Consequently, the real time recommendation system based on user interest is requrired. It is importante for such a system to analyze user interest from Twitter. In this paper, we propose a method of analyzing user interest used by collaborative filtering based on latent dirichlet allocation.
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Keyword(in English)	Recommendation System / Web Mining / Topic Model
Paper #	NLC2013-50
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Committee	NLC
Conference Date	2014/1/30(1days)
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Paper Information
Registration To	Natural Language Understanding and Models of Communication (NLC)
Language	JPN
Title (in Japanese)	(See Japanese page)
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Title (in English)	Collaborative Filtering Based on Latent Dirichlet Allocation for Tweet Recommendation Reflecting User Preference
Sub Title (in English)
Keyword(1)	Recommendation System
Keyword(2)	Web Mining
Keyword(3)	Topic Model
1st Author's Name	Keita WATANABE
1st Author's Affiliation	Graduate School of Engineering, Nagoya Institute of Technology()
2nd Author's Name	Shohei KATO
2nd Author's Affiliation	Graduate School of Engineering, Nagoya Institute of Technology
Date	2014-02-06
Paper #	NLC2013-50
Volume (vol)	vol.113
Number (no)	429
Page	pp.pp.-
#Pages	6
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