Cloud Computing, Security, Privacy in New Computing Environments. 7th International Conference, CloudComp 2016, and First International Conference, SPNCE 2016, Guangzhou, China, November 25–26, and December 15–16, 2016, Proceedings

Research Article

Question Recommendation Based on User Model in CQA

  • @INPROCEEDINGS{10.1007/978-3-319-69605-8_9,
        author={Junfeng Wang and Lei Su and Jun Chen and Di Jiang},
        title={Question Recommendation Based on User Model in CQA},
        proceedings={Cloud Computing, Security, Privacy in New Computing Environments. 7th International Conference, CloudComp 2016, and First International Conference, SPNCE 2016, Guangzhou, China, November 25--26, and December 15--16, 2016, Proceedings},
        proceedings_a={CLOUDCOMP},
        year={2017},
        month={11},
        keywords={Community question answering system Question recommendation User’ dynamic interest User’ expertise},
        doi={10.1007/978-3-319-69605-8_9}
    }
    
  • Junfeng Wang
    Lei Su
    Jun Chen
    Di Jiang
    Year: 2017
    Question Recommendation Based on User Model in CQA
    CLOUDCOMP
    Springer
    DOI: 10.1007/978-3-319-69605-8_9
Junfeng Wang1,*, Lei Su1,*, Jun Chen1, Di Jiang1
  • 1: Kunming University of Science and Technology
*Contact email: w327918069@163.com, s28341@hotmail.com

Abstract

At present, people no longer meet the way of communication between users and the Internet. And more and more people choose the interaction between users and users to get information. The community question answering system is one of the new information sharing model. In the community question answering system, users are not only the questioner but also the answer and the question is the link between the users. With the increasing number of users and the increasing number of questions and answers, it makes many questions which just were raised disappear in the category pages of the home page. Leading to the efficiency of the questions be answered greatly reduce. Aim at the recommended user’s interest, ability and time. In this paper we construct a dynamic user interest model and user expertise model. Experimental results show that the recommendation mechanism improves the efficiency of the recommendation to a certain extent.