Cross-Media Entity Recognition in Nearly Parallel Visual and Textual Documents

K. Deschacht, Marie-Francine Moens, Wouter Robeyns
{"title":"Cross-Media Entity Recognition in Nearly Parallel Visual and Textual Documents","authors":"K. Deschacht, Marie-Francine Moens, Wouter Robeyns","doi":"10.5555/1931390.1931404","DOIUrl":null,"url":null,"abstract":"We present a novel approach to automatically annotate images solely using associated text. We detect and classify all entities (persons and objects) in the text after which we determine the salience (the importance of an entity in a text) and visualness (the extent to which an entity can be perceived visually) of these entities. We combine these measures to compute the probability that an entity is present in the image. The suitability of our approach was successfully tested on 900 image-text pairs of Yahoo! News.","PeriodicalId":120472,"journal":{"name":"RIAO Conference","volume":"18 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2007-05-30","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"5","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"RIAO Conference","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.5555/1931390.1931404","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
引用次数: 5

Abstract

We present a novel approach to automatically annotate images solely using associated text. We detect and classify all entities (persons and objects) in the text after which we determine the salience (the importance of an entity in a text) and visualness (the extent to which an entity can be perceived visually) of these entities. We combine these measures to compute the probability that an entity is present in the image. The suitability of our approach was successfully tested on 900 image-text pairs of Yahoo! News.
近乎平行的视觉和文本文档中的跨媒体实体识别
我们提出了一种仅使用相关文本自动注释图像的新方法。我们检测并分类文本中的所有实体(人和物体),然后确定这些实体的显著性(文本中实体的重要性)和可视性(实体可以在视觉上感知的程度)。我们结合这些度量来计算一个实体出现在图像中的概率。我们的方法的适用性已经成功地在900对Yahoo!新闻。
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:604180095
Book学术官方微信