Movie recommendation using reviews on the web

Takahiro Hayashi*, Rikio Onai

*Corresponding author for this work

Research output: Contribution to journalArticlepeer-review

5 Citations (Scopus)

Abstract

This paper proposes a movie recommendation system using movie reviews on the Web. The system receives a movie review from a user, estimates the user’s interests on movies from the review, and provides other persons’ reviews to the user based on interest matching. This paper assumes that user’s interests on movies appear on words which are positively or negatively evaluated in a review. Under the assumption, the system detects such words from the user’s review, and chooses other persons’ reviews to recommend in which the detected words are positively evaluated. Experimental results have shown that more than 1/3 of recommended reviews can motivate users to watch the movies mentioned in the reviews. In addition, the results have indicated that combining the proposed recommendationmethod and a conventional TF-IDF based recommendation method is important for more efficient recommendation.

Original languageEnglish
Pages (from-to)102-111
Number of pages10
JournalTransactions of the Japanese Society for Artificial Intelligence
Volume30
Issue number1
Publication statusPublished - 2015 Jan 6
Externally publishedYes

Keywords

  • Movie recommendation
  • Recommendation systems
  • User reviews

ASJC Scopus subject areas

  • Software
  • Artificial Intelligence

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