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.
|ジャーナル||Transactions of the Japanese Society for Artificial Intelligence|
|出版ステータス||Published - 2015 1月 6|
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