ASSOCIATION RULE ANALYSIS FOR TOUR ROUTE RECOMMENDATION AND APPLICATION TO WCTSNOP
- 1Laboratory of Spatial Data Mining and Information Sharing of Ministry of Education, Spatial Information Research Centre of Fujian, Fuzhou University, Fuzhou University District Xueyuan Road, China
- 2Dept. of Computer Science, Fujian Provincial Key Laboratory of information Processing and Intelligent Control, Minjiang University, Fuzhou University District Xiyuangong Road, China
- 3College of Computer and Information Sciences, Fujian Agriculture and Forestry University, Fuzhou, China
- 4Fuzhou Silviscene Information Technology Co. Ltd, China
Keywords: Association Rule Analysis, FP-growth, Cultural Tourism Service, E-tourism, Route Recommendation
Abstract. The increasing E-tourism systems provide intelligent tour recommendation for tourists. In this sense, recommender system can make personalized suggestions and provide satisfied information associated with their tour cycle. Data mining is a proper tool that extracting potential information from large database for making strategic decisions. In the study, association rule analysis based on FP-growth algorithm is applied to find the association relationship among scenic spots in different cities as tour route recommendation. In order to figure out valuable rules, Kulczynski interestingness measure is adopted and imbalance ratio is computed. The proposed scheme was evaluated on Wangluzhe cultural tourism service network operation platform (WCTSNOP), where it could verify that it is able to quick recommend tour route and to rapidly enhance the recommendation quality.