{"title":"A Study on the Tourism Features Extraction from Photos in a Tourism Website by Image Analysis","authors":"Shuang Li, Jun Sasaki","doi":"10.1109/ICAwST.2019.8923581","DOIUrl":null,"url":null,"abstract":"For a foreign independent tour, it is difficult to find personally adaptive spots. Therefore, it is necessary to filter the tourism features of the tourist attractions that are suitable for a foreign independent tour. In this paper, we attempt to find an effective method to extract tourism features from photos on a tourism website. We propose a method to extract the subjects that can be regarded as tourism features. To determine the threshold value for the filtering of features, we conducted an experiment to extract tourism feature words. We also compared the results with our previous work, and the feasibility and limitations of the proposed method have been confirmed.","PeriodicalId":156538,"journal":{"name":"2019 IEEE 10th International Conference on Awareness Science and Technology (iCAST)","volume":"44 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2019-10-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"2019 IEEE 10th International Conference on Awareness Science and Technology (iCAST)","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/ICAwST.2019.8923581","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
For a foreign independent tour, it is difficult to find personally adaptive spots. Therefore, it is necessary to filter the tourism features of the tourist attractions that are suitable for a foreign independent tour. In this paper, we attempt to find an effective method to extract tourism features from photos on a tourism website. We propose a method to extract the subjects that can be regarded as tourism features. To determine the threshold value for the filtering of features, we conducted an experiment to extract tourism feature words. We also compared the results with our previous work, and the feasibility and limitations of the proposed method have been confirmed.