短期間のユーザ行動に基づいたトピックモデルによる解析手法

カテゴリ: 論文誌(論文単位)

グループ名: 【C】電子・情報・システム部門

発行日: 2017/07/01

タイトル(英語): Analysis for Short Term User Behavior with Topic Model

著者名: 上辻　慶典（大阪府立大学），柳本　豪一（大阪府立大学），吉岡　理文（大阪府立大学）

著者名(英語): Keisuke Uetsuji (Osaka Prefecture University), Hidekazu Yanagimoto (Osaka Prefecture University), Michifumi Yoshioka (Osaka Prefecture University)

キーワード: アクセスログ，トピックモデル　　Access log，Topic model

要約(英語): There are many online shops in the Internet and a lot of persons buy products in those shops. Many online shops provide advertisements and item recommendations to attract their customers, but to achieve satisfactory customer experience, shops have to change advertisement and recommendation strategies for every customer's intents, since his/her intent decides whether provided advertisements and recommendations are useful or not. Hence it is important for online shops to estimate customer's intents. One of the resources we can use to estimate is an access log, including information on customer's movement in the online shop. If the movements depend on customer's intents, we can extract knowledge on them from the access logs. However, tracking user's changeable intents is difficult for existing time-series topic models since there would be few user activities in a time slice. In this paper, we propose a new topic model combining a topic model for behavior analysis with a model for short text analysis. In experiments, we show that our new model can track user's intents appropriately.

本誌: 電気学会論文誌C（電子・情報・システム部門誌） Vol.137 No.7 （2017） 特集：平成28年電子・情報・システム部門大会

本誌掲載ページ: 974-979 p

原稿種別: 論文／日本語

電子版へのリンク: https://www.jstage.jst.go.jp/article/ieejeiss/137/7/137_974/_article/-char/ja/