2016 International Conference on Big Data and Smart Computing (BigComp) (2016)
Hong Kong, China
Jan. 18, 2016 to Jan. 20, 2016
Kyo-Joong Oh , School of Computing, KAIST, Daejeon, Republic of Korea
Zaemyung Kim , School of Computing, KAIST, Daejeon, Republic of Korea
Hyungrai Oh , Software Center, Samsung Electronics Inc., Suwon, Gyeonggi-do, Republic of Korea
Chae-Gyun Lim , School of Computing, KAIST, Daejeon, Republic of Korea
Gahgene Gweon , Dept. of Knowledge Service Engineering, KAIST, Daejeon, Republic of Korea
Recommending travel destinations on the basis of users' travel intentions is a research topic being studied recently in the field of intention analysis. This study considers travel intentions from a large number of travel-related reviews containing the reviewers' purpose for visiting the points of interest (POIs). We analyze travel intentions of 83,207 POIs using 6,791,427 reviews in www.TripAdvisor.com with domain-tailored word embedding model. Building an attraction network based on travel intentions helps to recommend travel destinations to travelers and reviewers. We present three prediction methods to recommend travel destinations with an attraction network and description logic. We also present the evaluation results of recommendations from some prediction scenarios. Consequently, the travel intention classification is commensurate with an analysis of intentions from textual data, and the attraction network is useful for recommending travel destinations on the basis of short-and long-term user preferences.
Recommender systems, Correlation, History, Data mining, Testing, Training, Knowledge engineering
Kyo-Joong Oh, Zaemyung Kim, Hyungrai Oh, Chae-Gyun Lim and G. Gweon, "Travel intention-based attraction network for recommending travel destinations," 2016 International Conference on Big Data and Smart Computing (BigComp)(BIGCOMP), Hong Kong, China, 2016, pp. 277-280.