一种鲁棒的模糊文档聚类算法

Lifei Chen, Shengrui Wang, Q. Jiang
{"title":"一种鲁棒的模糊文档聚类算法","authors":"Lifei Chen, Shengrui Wang, Q. Jiang","doi":"10.1109/WAINA.2009.15","DOIUrl":null,"url":null,"abstract":"In many applications of document clustering, a document may include multiple topics and thus may relate to multiple categories at the same time. Most of the existing subspace clustering algorithms can only perform hard clustering on document collections. In this paper, a fuzzy algorithm named R-FPC is introduced for document clustering. The algorithm discovers soft partitions of a data set in the soft subspaces of the data space. Using the proposed R-Greedy initialization method, R-FPC can always generate stable clustering results with competitive accuracy. The experiments are conducted on some widely used corpuses and the results have shown effectiveness and robustness of the proposed methods.","PeriodicalId":159465,"journal":{"name":"2009 International Conference on Advanced Information Networking and Applications Workshops","volume":"28 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2009-05-26","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"6","resultStr":"{\"title\":\"A Robust Algorithm for Fuzzy Document Clustering\",\"authors\":\"Lifei Chen, Shengrui Wang, Q. Jiang\",\"doi\":\"10.1109/WAINA.2009.15\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"In many applications of document clustering, a document may include multiple topics and thus may relate to multiple categories at the same time. Most of the existing subspace clustering algorithms can only perform hard clustering on document collections. In this paper, a fuzzy algorithm named R-FPC is introduced for document clustering. The algorithm discovers soft partitions of a data set in the soft subspaces of the data space. Using the proposed R-Greedy initialization method, R-FPC can always generate stable clustering results with competitive accuracy. The experiments are conducted on some widely used corpuses and the results have shown effectiveness and robustness of the proposed methods.\",\"PeriodicalId\":159465,\"journal\":{\"name\":\"2009 International Conference on Advanced Information Networking and Applications Workshops\",\"volume\":\"28 1\",\"pages\":\"0\"},\"PeriodicalIF\":0.0000,\"publicationDate\":\"2009-05-26\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"6\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"2009 International Conference on Advanced Information Networking and Applications Workshops\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/10.1109/WAINA.2009.15\",\"RegionNum\":0,\"RegionCategory\":null,\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"\",\"JCRName\":\"\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"2009 International Conference on Advanced Information Networking and Applications Workshops","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/WAINA.2009.15","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
引用次数: 6

摘要

在文档聚类的许多应用程序中,一个文档可能包含多个主题,因此可能同时与多个类别相关。现有的子空间聚类算法大多只能对文档集合进行硬聚类。本文提出了一种用于文档聚类的模糊算法R-FPC。该算法在数据空间的软子空间中发现数据集的软分区。采用本文提出的R-Greedy初始化方法,R-FPC总能生成稳定的聚类结果,且具有竞争精度。在一些广泛使用的语料库上进行了实验,结果表明了所提方法的有效性和鲁棒性。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
A Robust Algorithm for Fuzzy Document Clustering
In many applications of document clustering, a document may include multiple topics and thus may relate to multiple categories at the same time. Most of the existing subspace clustering algorithms can only perform hard clustering on document collections. In this paper, a fuzzy algorithm named R-FPC is introduced for document clustering. The algorithm discovers soft partitions of a data set in the soft subspaces of the data space. Using the proposed R-Greedy initialization method, R-FPC can always generate stable clustering results with competitive accuracy. The experiments are conducted on some widely used corpuses and the results have shown effectiveness and robustness of the proposed methods.
求助全文
通过发布文献求助,成功后即可免费获取论文全文。 去求助
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