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[Keyword] Web browsing behavior(1hit)

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  • Representation Learning for Users' Web Browsing Sequences

    Yukihiro TAGAMI  Hayato KOBAYASHI  Shingo ONO  Akira TAJIMA  

     
    PAPER-Artificial Intelligence, Data Mining

      Pubricized:
    2018/04/20
      Vol:
    E101-D No:7
      Page(s):
    1870-1879

    Modeling user activities on the Web is a key problem for various Web services, such as news article recommendation and ad click prediction. In our work-in-progress paper[1], we introduced an approach that summarizes each sequence of user Web page visits using Paragraph Vector[3], considering users and URLs as paragraphs and words, respectively. The learned user representations are used among the user-related prediction tasks in common. In this paper, on the basis of analysis of our Web page visit data, we propose Backward PV-DM, which is a modified version of Paragraph Vector. We show experimental results on two ad-related data sets based on logs from Web services of Yahoo! JAPAN. Our proposed method achieved better results than those of existing vector models.