Ontology Based Semantic Measures in Document Similarity Ranking

U. Sridevi, N. Nagaveni
{"title":"Ontology Based Semantic Measures in Document Similarity Ranking","authors":"U. Sridevi, N. Nagaveni","doi":"10.1109/ARTCom.2009.144","DOIUrl":null,"url":null,"abstract":"Recent work has shown that ontologies are useful to improve the performance of retrieval. In this paper, we present a new distance measure using ontologies. Ontology based correlation analysis is implemented to find the relations between the terms. Combining the ontology based correlation analysis and the traditional vector space model, the document similarity is calculated. Our results show that ontology based distance measure makes better relevance measure. The proposed method has been evaluated on USGS Science directory collection. Preliminary experiments results show that our method may generate relevant document in the top rank.","PeriodicalId":210885,"journal":{"name":"Advances in Recent Technologies in Communication and Computing","volume":null,"pages":null},"PeriodicalIF":0.0000,"publicationDate":"2009-10-27","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"8","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"Advances in Recent Technologies in Communication and Computing","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/ARTCom.2009.144","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
引用次数: 8

Abstract

Recent work has shown that ontologies are useful to improve the performance of retrieval. In this paper, we present a new distance measure using ontologies. Ontology based correlation analysis is implemented to find the relations between the terms. Combining the ontology based correlation analysis and the traditional vector space model, the document similarity is calculated. Our results show that ontology based distance measure makes better relevance measure. The proposed method has been evaluated on USGS Science directory collection. Preliminary experiments results show that our method may generate relevant document in the top rank.
查看原文
分享 分享
微信好友 朋友圈 QQ好友 复制链接
本刊更多论文
基于本体的语义度量在文档相似度排序中的应用
最近的研究表明,本体对提高检索性能很有用。本文提出了一种新的基于本体的距离度量方法。实现了基于本体的关联分析,查找词条之间的关系。将基于本体的关联分析与传统的向量空间模型相结合,计算了文档的相似度。结果表明,基于本体的距离度量是更好的相关性度量。该方法已在USGS科学目录收集中进行了评估。初步的实验结果表明,我们的方法可以生成排名靠前的相关文档。
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 去求助
来源期刊
自引率
0.00%
发文量
0
期刊最新文献
A Short Survey of Energy-Efficient Routing Protocols for Mobile Ad-Hoc Networks Ensuring Data Storage Security in Cloud Computing through Two-Way Handshake Based on Token Management Testing of Logic Blocks Using Built-In Self Test Scheme for FPGAs An Intriguing Property of Scaling Function in Wavelet Theory and its Verification Using Daubechies-Lagarias Algorithm Ontology Based Semantic Measures in Document Similarity Ranking
×
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
现在去查看 取消
×
提示
确定
0
微信
客服QQ
Book学术公众号 扫码关注我们
反馈
×
意见反馈
请填写您的意见或建议
请填写您的手机或邮箱
已复制链接
已复制链接
快去分享给好友吧!
我知道了
×
扫码分享
扫码分享
Book学术官方微信
Book学术文献互助
Book学术文献互助群
群 号:481959085
Book学术
文献互助 智能选刊 最新文献 互助须知 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 Book学术 All rights reserved.
ghs 京公网安备 11010802042870号 京ICP备2023020795号-1