Topic model for user reviews with adaptive windows

Takuya Konishi, Fuminori Kimura, Akira Maeda

研究成果: Chapter in Book/Report/Conference proceedingConference contribution

抄録

We discuss the problem in applying topic models to user reviews. Different from ordinary documents, reviews in a same category are similar to each other. This makes it difficult to estimate meaningful topics from these reviews. In this paper, we develop a new model for this problem using the distance dependent Chinese restaurant process. It need not decide the size of windows and can consider neighboring sentences adaptively. We compare this model to the Multi-grain latent Dirichlet allocation which has been proposed previously, and show that our model achieves better results in terms of perplexity.

本文言語英語
ホスト出版物のタイトルAdvances in Information Retrieval - 35th European Conference on IR Research, ECIR 2013, Proceedings
ページ730-733
ページ数4
DOI
出版ステータス出版済み - 2013
外部発表はい
イベント35th European Conference on Information Retrieval, ECIR 2013 - Moscow, ロシア連邦
継続期間: 3 24 20133 27 2013

出版物シリーズ

名前Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)
7814 LNCS
ISSN(印刷版)0302-9743
ISSN(電子版)1611-3349

会議

会議35th European Conference on Information Retrieval, ECIR 2013
国/地域ロシア連邦
CityMoscow
Period3/24/133/27/13

All Science Journal Classification (ASJC) codes

  • 理論的コンピュータサイエンス
  • コンピュータ サイエンス(全般)

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