Jin-Yao Wang, Yu-Lun Chang, Wei-Sheng Zeng, Shian-Hua Lin
{"title":"Recommend Significant Tags to Travel Photos Based on Web Mining","authors":"Jin-Yao Wang, Yu-Lun Chang, Wei-Sheng Zeng, Shian-Hua Lin","doi":"10.1109/MUSIC.2012.22","DOIUrl":null,"url":null,"abstract":"As the rapid development of smart phones and applications, users are familiar to take photos with smart phones on the trip and share photos to friends on social networks. Those photos are usually tagged and shared with trivial location information, such as attractions derived from mobile locations contributed from Facebook users. However, these attractions are not useful for enhancing the photo semantics. In this paper, we propose the Tag Recommendation System (TRS) that automatically mine significant tags from Flickr's photos so that these tags can be recommended to improve the semantics of photos according to location information. Experiments based on the user experience show that TRS can achieve about 85% satisfaction rates.","PeriodicalId":260515,"journal":{"name":"2012 Third FTRA International Conference on Mobile, Ubiquitous, and Intelligent Computing","volume":"128 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2012-06-26","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"2","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"2012 Third FTRA International Conference on Mobile, Ubiquitous, and Intelligent Computing","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/MUSIC.2012.22","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
引用次数: 2
Abstract
As the rapid development of smart phones and applications, users are familiar to take photos with smart phones on the trip and share photos to friends on social networks. Those photos are usually tagged and shared with trivial location information, such as attractions derived from mobile locations contributed from Facebook users. However, these attractions are not useful for enhancing the photo semantics. In this paper, we propose the Tag Recommendation System (TRS) that automatically mine significant tags from Flickr's photos so that these tags can be recommended to improve the semantics of photos according to location information. Experiments based on the user experience show that TRS can achieve about 85% satisfaction rates.