Context-Aware Systems and Applications. 4th International Conference, ICCASA 2015, Vung Tau, Vietnam, November 26-27, 2015, Revised Selected Papers

Research Article

User Timeline and Interest-Based Collaborative Filtering on Social Network

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  • @INPROCEEDINGS{10.1007/978-3-319-29236-6_14,
        author={Xuan Pham and Jason Jung and Bui Nam and Tuong Nguyen},
        title={User Timeline and Interest-Based Collaborative Filtering on Social Network},
        proceedings={Context-Aware Systems and Applications. 4th International Conference, ICCASA 2015, Vung Tau, Vietnam, November 26-27, 2015, Revised Selected Papers},
        proceedings_a={ICCASA},
        year={2016},
        month={4},
        keywords={Recommendation systems Context User timeline User interest},
        doi={10.1007/978-3-319-29236-6_14}
    }
    
  • Xuan Pham
    Jason Jung
    Bui Nam
    Tuong Nguyen
    Year: 2016
    User Timeline and Interest-Based Collaborative Filtering on Social Network
    ICCASA
    Springer
    DOI: 10.1007/978-3-319-29236-6_14
Xuan Pham1,*, Jason Jung2,*, Bui Nam2,*, Tuong Nguyen3,*
  • 1: QuangBinh University
  • 2: ChungAng University
  • 3: Yeungnam University
*Contact email: pxhauqbu@gmail.com, j2jung@gmail.com, hoainam.bk2012@gmail.com, tuongtringuyen@gmail.com

Abstract

A lot of users and large amount of information have been posted and shared through on-line systems. User timeline and interest are important features on recommendation systems (e.g., user likes watching action movies in the morning, and likes watching drama movies in the afternoon however he/she likes watching thriller movies in the evening) and also on social network. There are some recommendation applications have been developed on social network to support users selecting what kind of wanted items based on user timeline and interest. However, there is not any approaches based on user timeline and interest have been proposed that user interest have been separated into partitions of user interest. Thus, a recommendation mechanism will be applied on social networks based on extracting user timeline and user interest that is necessary. In this paper, we propose a new approach that user interest will be determined on a set of time partitions.