A Survey of Semantic Similarity Methods for Ontology Based Information Retrieval

K. Saruladha, G. Aghila, S. Raj
{"title":"A Survey of Semantic Similarity Methods for Ontology Based Information Retrieval","authors":"K. Saruladha, G. Aghila, S. Raj","doi":"10.1109/ICMLC.2010.63","DOIUrl":null,"url":null,"abstract":"This paper discusses the various approaches used for identifying semantically similar concepts in an ontology. The purpose of this survey is to explore how these similarity computation methods could assist in ontology based query expansion. This query expansion method based on the similarity function is expected to improve the retrieval effectiveness of the ontology based Information retrieval models. Various similarity computation methods fall under three categories: Edge counting, information content and node based counting. The limitations of each of these approaches have been discussed in this paper.","PeriodicalId":423912,"journal":{"name":"2010 Second International Conference on Machine Learning and Computing","volume":"46 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2010-02-09","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"51","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"2010 Second International Conference on Machine Learning and Computing","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/ICMLC.2010.63","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
引用次数: 51

Abstract

This paper discusses the various approaches used for identifying semantically similar concepts in an ontology. The purpose of this survey is to explore how these similarity computation methods could assist in ontology based query expansion. This query expansion method based on the similarity function is expected to improve the retrieval effectiveness of the ontology based Information retrieval models. Various similarity computation methods fall under three categories: Edge counting, information content and node based counting. The limitations of each of these approaches have been discussed in this paper.
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
基于本体的信息检索语义相似度方法综述
本文讨论了用于识别本体中语义相似概念的各种方法。本调查的目的是探索这些相似度计算方法如何帮助基于本体的查询扩展。这种基于相似度函数的查询扩展方法有望提高基于本体的信息检索模型的检索效率。各种相似度计算方法分为三类:边缘计数、信息内容计数和基于节点计数。本文讨论了每种方法的局限性。
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
Modified Ant Miner for Intrusion Detection An Approach Based on Clustering Method for Object Finding Mobile Robots Using ACO Statistical Feature Extraction for Classification of Image Spam Using Artificial Neural Networks Recognition of Faces Using Improved Principal Component Analysis Autonomous Navigation in Rubber Plantations
×
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