Topic tracking model for analyzing consumer purchase behavior

Tomoharu Iwata, Shinji Watanabe, Takeshi Yamada, Naonori Ueda

研究成果: Conference contribution

111 被引用数 (Scopus)

抄録

We propose a new topic model for tracking timevarying consumer purchase behavior, in which consumer interests and item trends change over time. The proposed model can adaptively track changes in interests and trends based on current purchase logs and previously estimated interests and trends. The online nature of the proposed method means we do not need to store past data for current inferences and so we can considerably reduce the computational cost and the memory requirement. We use real purchase logs to demonstrate the effectiveness of the proposed method in terms of the prediction accuracy of purchase behavior and the computational cost of the inference.

本文言語English
ホスト出版物のタイトルIJCAI-09 - Proceedings of the 21st International Joint Conference on Artificial Intelligence
出版社International Joint Conferences on Artificial Intelligence
ページ1427-1432
ページ数6
ISBN(印刷版)9781577354260
出版ステータスPublished - 2009 1 1
外部発表はい
イベント21st International Joint Conference on Artificial Intelligence, IJCAI 2009 - Pasadena, United States
継続期間: 2009 7 112009 7 16

出版物シリーズ

名前IJCAI International Joint Conference on Artificial Intelligence
ISSN(印刷版)1045-0823

Conference

Conference21st International Joint Conference on Artificial Intelligence, IJCAI 2009
CountryUnited States
CityPasadena
Period09/7/1109/7/16

ASJC Scopus subject areas

  • Artificial Intelligence

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