Word Semantic Similarity Based on Document's Title

Mohamed Said Hamani, R. Maamri
{"title":"Word Semantic Similarity Based on Document's Title","authors":"Mohamed Said Hamani, R. Maamri","doi":"10.1109/DEXA.2013.12","DOIUrl":null,"url":null,"abstract":"Measuring similarity between words using a search engine based on page counts alone is a challenging task. Search engines consider a document as a bag of words, ignoring the position of words in a document. In order to measure semantic similarity between two given words, this paper proposes a transformation function for web measures along with a new approach that exploits the document's title attribute and uses page counts alone returned by Web search engines. Experimental results on benchmark datasets show that the proposed approach outperforms snippets alone methods, achieving a correlation coefficient up to 71%.","PeriodicalId":428515,"journal":{"name":"2013 24th International Workshop on Database and Expert Systems Applications","volume":"127 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2013-08-26","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"7","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"2013 24th International Workshop on Database and Expert Systems Applications","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/DEXA.2013.12","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
引用次数: 7

Abstract

Measuring similarity between words using a search engine based on page counts alone is a challenging task. Search engines consider a document as a bag of words, ignoring the position of words in a document. In order to measure semantic similarity between two given words, this paper proposes a transformation function for web measures along with a new approach that exploits the document's title attribute and uses page counts alone returned by Web search engines. Experimental results on benchmark datasets show that the proposed approach outperforms snippets alone methods, achieving a correlation coefficient up to 71%.
基于文档标题的词语义相似度研究
使用基于页面数的搜索引擎测量单词之间的相似性是一项具有挑战性的任务。搜索引擎将文档视为一袋单词,而忽略单词在文档中的位置。为了测量两个给定词之间的语义相似度,本文提出了一个web度量的转换函数,并提出了一种利用文档标题属性和单独使用web搜索引擎返回的页面数的新方法。在基准数据集上的实验结果表明,该方法优于单独使用片段的方法,相关系数高达71%。
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