Distributed Document Clustering for Search Engine

Chang Liu, Song-nian Yu, Qiang Guo
{"title":"Distributed Document Clustering for Search Engine","authors":"Chang Liu, Song-nian Yu, Qiang Guo","doi":"10.1109/ICWAPR.2009.5207461","DOIUrl":null,"url":null,"abstract":"Considering that data searched from the search engine is not comprehensive, and the inconsistencies between desired results and received results are inevitable, a more effective search tool called Distributed Document Clustering for Search Engine (DDCSE) is proposed in this paper. In the DDCSE, the utilizing of distributed clustering and several search engines is used to categorize the results, in order to feedback a set of better refined results. Experiments show that a significant improvement is achieved via the distribution document clustering, so as to refine the results and reduce the time used to filter out irrelevant data for the search engines.","PeriodicalId":424264,"journal":{"name":"2009 International Conference on Wavelet Analysis and Pattern Recognition","volume":"108 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2009-07-12","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"3","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"2009 International Conference on Wavelet Analysis and Pattern Recognition","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/ICWAPR.2009.5207461","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
引用次数: 3

Abstract

Considering that data searched from the search engine is not comprehensive, and the inconsistencies between desired results and received results are inevitable, a more effective search tool called Distributed Document Clustering for Search Engine (DDCSE) is proposed in this paper. In the DDCSE, the utilizing of distributed clustering and several search engines is used to categorize the results, in order to feedback a set of better refined results. Experiments show that a significant improvement is achieved via the distribution document clustering, so as to refine the results and reduce the time used to filter out irrelevant data for the search engines.
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
面向搜索引擎的分布式文档聚类
考虑到从搜索引擎中搜索到的数据不全面,期望结果和接收结果之间不可避免的不一致,本文提出了一种更有效的搜索工具——分布式文档聚类搜索引擎(DDCSE)。在DDCSE中,利用分布式聚类和多个搜索引擎对结果进行分类,以反馈一组更精细的结果。实验表明,通过分布式文档聚类,可以明显改善结果,减少搜索引擎过滤不相关数据的时间。
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
Analysis of Laplacian Support Vector Machines Intelligent computerized fabric texture recognition system by using Grey-based neural fuzzy clustering A new cooperative algorithm for signal detection Improved algorithm of the Back Propagation neural network and its application in fault diagnosis of air-cooling condenser HSICT: A method for romoving highlight and shading in color image
×
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