基于非均匀聚类方法的WWW图像搜索结果分组

Zhiwei Li, Gu Xu, Mingjing Li, Wei-Ying Ma, HongJiang Zhang
{"title":"基于非均匀聚类方法的WWW图像搜索结果分组","authors":"Zhiwei Li, Gu Xu, Mingjing Li, Wei-Ying Ma, HongJiang Zhang","doi":"10.1109/MMMC.2005.47","DOIUrl":null,"url":null,"abstract":"In this paper, a novel inhomogeneous clustering method is proposed for grouping web images. It is used to re-organize the search result of web image search engines into a hierarchical structure so that the users can conveniently browse the search result. This method takes into account various features associated with web images, and treats them in different ways. For the surrounding text extracted from the containing web pages, co-clustering approach is adopted; for low-level features of the image content and other features, one-way clustering approach is adopted. The clustering results of different approaches are combined together to produce the final image groups. Experimental results demonstrate the effectiveness of the proposed method.","PeriodicalId":121228,"journal":{"name":"11th International Multimedia Modelling Conference","volume":"1 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2005-01-12","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"11","resultStr":"{\"title\":\"Grouping WWW Image Search Results by Novel Inhomogeneous Clustering Method\",\"authors\":\"Zhiwei Li, Gu Xu, Mingjing Li, Wei-Ying Ma, HongJiang Zhang\",\"doi\":\"10.1109/MMMC.2005.47\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"In this paper, a novel inhomogeneous clustering method is proposed for grouping web images. It is used to re-organize the search result of web image search engines into a hierarchical structure so that the users can conveniently browse the search result. This method takes into account various features associated with web images, and treats them in different ways. For the surrounding text extracted from the containing web pages, co-clustering approach is adopted; for low-level features of the image content and other features, one-way clustering approach is adopted. The clustering results of different approaches are combined together to produce the final image groups. Experimental results demonstrate the effectiveness of the proposed method.\",\"PeriodicalId\":121228,\"journal\":{\"name\":\"11th International Multimedia Modelling Conference\",\"volume\":\"1 1\",\"pages\":\"0\"},\"PeriodicalIF\":0.0000,\"publicationDate\":\"2005-01-12\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"11\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"11th International Multimedia Modelling Conference\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/10.1109/MMMC.2005.47\",\"RegionNum\":0,\"RegionCategory\":null,\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"\",\"JCRName\":\"\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"11th International Multimedia Modelling Conference","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/MMMC.2005.47","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
引用次数: 11

摘要

本文提出了一种新的网络图像非同构聚类方法。它用于将网络图像搜索引擎的搜索结果重新组织成层次结构,使用户可以方便地浏览搜索结果。该方法考虑了与web图像相关的各种特征,并以不同的方式处理它们。对于从包含的网页中提取的周围文本,采用共聚类方法;对于图像内容的低级特征和其他特征,采用单向聚类方法。将不同方法的聚类结果结合在一起,生成最终的图像组。实验结果证明了该方法的有效性。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Grouping WWW Image Search Results by Novel Inhomogeneous Clustering Method
In this paper, a novel inhomogeneous clustering method is proposed for grouping web images. It is used to re-organize the search result of web image search engines into a hierarchical structure so that the users can conveniently browse the search result. This method takes into account various features associated with web images, and treats them in different ways. For the surrounding text extracted from the containing web pages, co-clustering approach is adopted; for low-level features of the image content and other features, one-way clustering approach is adopted. The clustering results of different approaches are combined together to produce the final image groups. Experimental results demonstrate the effectiveness of the proposed method.
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:604180095
Book学术官方微信