Recommend Significant Tags to Travel Photos Based on Web Mining

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.
基于Web挖掘的旅游照片重要标签推荐
随着智能手机和应用的快速发展,用户已经熟悉在旅行中用智能手机拍照,并在社交网络上分享照片给朋友。这些照片通常被贴上标签,并与琐碎的位置信息一起分享,比如Facebook用户提供的移动位置带来的景点。然而,这些吸引力对增强照片语义没有帮助。在本文中,我们提出了标签推荐系统(Tag Recommendation System, TRS),该系统可以自动从Flickr的照片中挖掘重要的标签,并根据位置信息推荐这些标签以提高照片的语义。基于用户体验的实验表明,TRS可以达到85%左右的满意率。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
求助全文
约1分钟内获得全文 求助全文
来源期刊
自引率
0.00%
发文量
0
×
引用
GB/T 7714-2015
复制
MLA
复制
APA
复制
导出至
BibTeX EndNote RefMan NoteFirst NoteExpress
×
提示
您的信息不完整,为了账户安全,请先补充。
现在去补充
×
提示
您因"违规操作"
具体请查看互助需知
我知道了
×
提示
确定
请完成安全验证×
copy
已复制链接
快去分享给好友吧!
我知道了
右上角分享
点击右上角分享
0
联系我们:info@booksci.cn Book学术提供免费学术资源搜索服务,方便国内外学者检索中英文文献。致力于提供最便捷和优质的服务体验。 Copyright © 2023 布克学术 All rights reserved.
京ICP备2023020795号-1
ghs 京公网安备 11010802042870号
Book学术文献互助
Book学术文献互助群
群 号:481959085
Book学术官方微信