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  • Open Access


    Research on Tourist Routes Recommendation Based on the User Preference Drifting Over Time

    Chunjing Xiao1,∗, Yongwei Qiao2, Kewen Xia1, Yuxiang Zhang3

    Computer Systems Science and Engineering, Vol.33, No.2, pp. 95-103, 2018, DOI:10.32604/csse.2018.33.095

    Abstract Tourist routes recommendation is a way to improve the tourist experience and the efficiency of tourism companies. Session-based methods divide all users’ interaction histories into the same number sessions with fixed time window and treat the user preference as time sequences. There have few or even no interaction in some sessions for some users because of the high sparsity and temporal characteristics of tourist data. That lead to many session-based methods can not be applied to routes recommendation due to aggravate the sparsity. In order to better adapt and apply the characteristics of tourism data… More >

  • Open Access


    Tensor-Based User Trajectory Mining

    Chen Yu, Qinmin Hong, Dezhong Yao, Hai Jin

    Computer Systems Science and Engineering, Vol.33, No.2, pp. 87-94, 2018, DOI:10.32604/csse.2018.33.087

    Abstract The rapid expansion of GPS-embedded devices has showed the emerging new look of location-based services, enabling such offerings as travel guide services and location-based social networks. One consequence is the accumulation of a rich supply of GPS trajectories, indicating individuals’ historical position. Based on these data, we aim to mine the hot route by using a collaborative tensor calculation method. We present an efficient trajectory data processing model for mining the hot route. In this paper, we rst model the individual’s trajectory log, extract sources and destinations, use map matching to get the corresponding road More >

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