• An Advice Recommender System Based on Complaint Data Analysis  PDF  プレプリント
    Liang Yang, Daisuke Kitayama, Kazutoshi Sumiya
    Proceedings of the Workshop on Recommendation in Complex Scenarios co-located with 13th ACM Conference on Recommender Systems (RecSys 2019), pp.35-39, Copenhagen, Denmark, 2019年9月, 査読有
  • 概要
    Nowadays, there are a large number of users who post complaints about a certain service on the Internet. Because users have vari- ous values and views, even if they receive the same service, they may complain in different ways. However, it is quite difficult to respond to various user demands for service in real time and there are almost no direct solutions when users feel dissatisfied with a certain service. Therefore, in this paper, we propose an advice rec- ommender system by analyzing complaint data from Fuman Kaitori Center. First, the system generates query keywords according to various user complaints about a certain service by calculating the score of each query. Then suitable web pages containing advice are recommended from the results of the query. This advice could address users’ dissatisfaction and respond to their various demands in a comprehensive way. Also, we verify the usability of proposed system by using a questionnaire survey evaluation.
  • スライド