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Formal Concept Analysis Support for Web Document Clustering Based on Social Tagging

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成果类型:
期刊论文、会议论文
作者:
Ouyang, Chunping*;Yang, Xiaohua;Li, Xiaoyun;Liu, Zhiming
通讯作者:
Ouyang, Chunping
作者机构:
[Ouyang, Chunping; Yang, Xiaohua; Liu, Zhiming; Li, Xiaoyun] Univ S China, Sch Comp Sci & Technol, Hengyang 421001, Peoples R China.
通讯机构:
[Ouyang, Chunping] U
Univ S China, Sch Comp Sci & Technol, Hengyang 421001, Peoples R China.
语种:
英文
关键词:
formal concept analysis;social tagging;document clustering
期刊:
Proceeding of 2012 International Conference on Uncertainty Reasoning and Knowledge Engineering, URKE 2012
年:
2012
页码:
304-307
会议名称:
2nd International Conference on Uncertainty Reasoning and Knowledge Engineering (URKE)
会议时间:
AUG 14-15, 2012
会议地点:
Jakarta, INDONESIA
会议主办单位:
[Ouyang, Chunping;Yang, Xiaohua;Li, Xiaoyun;Liu, Zhiming] Univ S China, Sch Comp Sci & Technol, Hengyang 421001, Peoples R China.
会议赞助商:
IAMSIE
出版地:
345 E 47TH ST, NEW YORK, NY 10017 USA
出版者:
IEEE
ISBN:
978-1-4673-1460-2
机构署名:
本校为第一且通讯机构
院系归属:
计算机科学与技术学院
摘要:
Web document clustering is one of the most important research branches of Clustering Analyzing. The objective of web document clustering is to meet the need of retrieving web document efficiently from massive information in Internet. Recently social tagging is the important form of document organization in web 2.0, and the tagging as a document descriptor is used to improve the effectiveness of web searching. But a web document usually belongs to various category of tagging, which may lead to the difficulty of browsing web document based on single tagging. This paper explores the use of Formal...

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