{"title":"The Development of Folklore Tourism Integrating the Function Differentiation Model of Folklore Culture","authors":"Ya Ji","doi":"10.1109/icsgea.2018.00067","DOIUrl":null,"url":null,"abstract":"With the rapid development of folklore tourism (Folklore Tourism, FT), folklore tourism development (Development of folklore tourism, DFT) has become an important research hotspot which is aimed at helping people find interesting and attractive spots, especially when users travel outside hometown. To rise to the challenges above, I propose the Function Differentiation Model of Folklore Culture (FDMFC) in this paper to stimulate the users’ performance characteristics of the decision-making process. The model can integrate the factors above effectively to cope with the data’s sparseness especially in the off-site recommended scenarios. The development method of folklore tourism in this paper includes off-line model and online recommendation, two parts. The experiments were done on the self-performance data set of real Ts with large scale and its results show that this method has better recommendation results than other advanced folklore tourism development algorithms.","PeriodicalId":445324,"journal":{"name":"2018 International Conference on Smart Grid and Electrical Automation (ICSGEA)","volume":"77 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2018-06-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"2018 International Conference on Smart Grid and Electrical Automation (ICSGEA)","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/icsgea.2018.00067","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
引用次数: 0
Abstract
With the rapid development of folklore tourism (Folklore Tourism, FT), folklore tourism development (Development of folklore tourism, DFT) has become an important research hotspot which is aimed at helping people find interesting and attractive spots, especially when users travel outside hometown. To rise to the challenges above, I propose the Function Differentiation Model of Folklore Culture (FDMFC) in this paper to stimulate the users’ performance characteristics of the decision-making process. The model can integrate the factors above effectively to cope with the data’s sparseness especially in the off-site recommended scenarios. The development method of folklore tourism in this paper includes off-line model and online recommendation, two parts. The experiments were done on the self-performance data set of real Ts with large scale and its results show that this method has better recommendation results than other advanced folklore tourism development algorithms.