A semantic similarity retrieval model based on Lucene

Ya Zhou, Xinqiang Wu, Ruyi Wang
{"title":"A semantic similarity retrieval model based on Lucene","authors":"Ya Zhou, Xinqiang Wu, Ruyi Wang","doi":"10.1109/ICSESS.2014.6933700","DOIUrl":null,"url":null,"abstract":"In recent years, more and more users hope the search results can meet human's demand when they use a search engine. On the basis of analysis and study on the open source Lucene system architecture, a semantic search system is designed based on the special XML data sources in this paper. What's more, we use the word item location and word semantic to improve the Lucene's search results and conduct experiments to test and verify the retrieval performance, the accuracy of similarity search, the space efficiency of index and the time-efficiency of supporting inquiry: And finally by deploying the Tomcat server to implement our implement system. The experiment results prove that compared with the original Lucene indexing system, our system can improve the indexing efficiency, query efficiency and accuracy.","PeriodicalId":6473,"journal":{"name":"2014 IEEE 5th International Conference on Software Engineering and Service Science","volume":"17 1","pages":"854-858"},"PeriodicalIF":0.0000,"publicationDate":"2014-06-27","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"5","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"2014 IEEE 5th International Conference on Software Engineering and Service Science","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/ICSESS.2014.6933700","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

In recent years, more and more users hope the search results can meet human's demand when they use a search engine. On the basis of analysis and study on the open source Lucene system architecture, a semantic search system is designed based on the special XML data sources in this paper. What's more, we use the word item location and word semantic to improve the Lucene's search results and conduct experiments to test and verify the retrieval performance, the accuracy of similarity search, the space efficiency of index and the time-efficiency of supporting inquiry: And finally by deploying the Tomcat server to implement our implement system. The experiment results prove that compared with the original Lucene indexing system, our system can improve the indexing efficiency, query efficiency and accuracy.
基于Lucene的语义相似度检索模型
近年来,越来越多的用户在使用搜索引擎时希望搜索结果能够满足人类的需求。本文在分析和研究开源Lucene系统架构的基础上,设计了一个基于特殊XML数据源的语义搜索系统。利用词项定位和词语义对Lucene的搜索结果进行改进,并进行实验,测试验证了Lucene的检索性能、相似度搜索的准确性、索引的空间效率和支持查询的时间效率。最后通过部署Tomcat服务器实现了我们的实现系统。实验结果证明,与原有的Lucene索引系统相比,我们的系统可以提高索引效率、查询效率和准确性。
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 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