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

Research Article

Travel Destination Recommendation Based on Probabilistic Spatio-temporal Inference

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  • @INPROCEEDINGS{10.1007/978-3-319-29236-6_10,
        author={Chang Choi and Junho Choi and Htet Lynn and Pankoo Kim},
        title={Travel Destination Recommendation Based on Probabilistic Spatio-temporal Inference},
        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 system Ontology Markov Logic Networks},
        doi={10.1007/978-3-319-29236-6_10}
    }
    
  • Chang Choi
    Junho Choi
    Htet Lynn
    Pankoo Kim
    Year: 2016
    Travel Destination Recommendation Based on Probabilistic Spatio-temporal Inference
    ICCASA
    Springer
    DOI: 10.1007/978-3-319-29236-6_10
Chang Choi1,*, Junho Choi1,*, Htet Lynn1,*, Pankoo Kim1,*
  • 1: Chosun University
*Contact email: enduranceaura@gmail.com, xdman@chosun.ac.kr, htetmyet@gmail.com, pkkim@chosun.ac.kr

Abstract

Recently, a lot of users are increasing for searching travel information through smart devices such as, tourist attractions, accommodation, entertainment, local gourmet food and so on. A general method for recommendation system has a data sparseness and the first rate problem. This problem can be solved by ontology and inference rules. In this paper, we propose the travel destination recommendation using Markov Logic Networks based on probabilistic spatio-temporal inference. The most inference engines determine simply if there is a result from inference or not. However, probabilistic inference methods have emerged and classified problems that cannot be defined easily in the probabilistic way, which provides better results.