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.
Keyword(in Japanese) (See Japanese page)
Keyword(in English) Recommendation System / Web Mining / Topic Model
Paper # NLC2013-50
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Conference Information
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)
Sub Title (in Japanese) (See Japanese page)
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
Date of Issue