{"title":"基于个人资料的个性化旅游目的地推荐方法","authors":"Minghao Li, Jun Sasaki","doi":"10.1109/PIC53636.2021.9687061","DOIUrl":null,"url":null,"abstract":"Personalized tours have become popular worldwide. However, it is not easy to recommend destinations that are appropriate for individual tourists. This study examines a highly accurate recommendation method using two indexes: an objective index that judges the adaptability between a tourist’s profile and a destination; and a subjective index that judges attractiveness for the tourist. We tested the method using data from tourism websites and a questionnaire survey. We found that the method was effective in identifying adaptive and attractive tourist groups for well-known destinations in Iwate Prefecture, Japan.","PeriodicalId":297239,"journal":{"name":"2021 IEEE International Conference on Progress in Informatics and Computing (PIC)","volume":"7 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2021-12-17","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":"{\"title\":\"Recommendation Method for Attractive Destinations for Individual Tourists Using Profile Data\",\"authors\":\"Minghao Li, Jun Sasaki\",\"doi\":\"10.1109/PIC53636.2021.9687061\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"Personalized tours have become popular worldwide. However, it is not easy to recommend destinations that are appropriate for individual tourists. This study examines a highly accurate recommendation method using two indexes: an objective index that judges the adaptability between a tourist’s profile and a destination; and a subjective index that judges attractiveness for the tourist. We tested the method using data from tourism websites and a questionnaire survey. We found that the method was effective in identifying adaptive and attractive tourist groups for well-known destinations in Iwate Prefecture, Japan.\",\"PeriodicalId\":297239,\"journal\":{\"name\":\"2021 IEEE International Conference on Progress in Informatics and Computing (PIC)\",\"volume\":\"7 1\",\"pages\":\"0\"},\"PeriodicalIF\":0.0000,\"publicationDate\":\"2021-12-17\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"0\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"2021 IEEE International Conference on Progress in Informatics and Computing (PIC)\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/10.1109/PIC53636.2021.9687061\",\"RegionNum\":0,\"RegionCategory\":null,\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"\",\"JCRName\":\"\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"2021 IEEE International Conference on Progress in Informatics and Computing (PIC)","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/PIC53636.2021.9687061","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
Recommendation Method for Attractive Destinations for Individual Tourists Using Profile Data
Personalized tours have become popular worldwide. However, it is not easy to recommend destinations that are appropriate for individual tourists. This study examines a highly accurate recommendation method using two indexes: an objective index that judges the adaptability between a tourist’s profile and a destination; and a subjective index that judges attractiveness for the tourist. We tested the method using data from tourism websites and a questionnaire survey. We found that the method was effective in identifying adaptive and attractive tourist groups for well-known destinations in Iwate Prefecture, Japan.