NDLI: Frequent term based peer-to-peer text clustering

Content Provider	IEEE Xplore Digital Library
Author	Qing He Tingting Li Fuzhen Zhuang Zhongzhi Shi
Copyright Year	2010
Description	Author affiliation: The Key Laboratory of Intelligent Information Processing, Institute of Computing Technology, Chinese Academy of Sciences, China (Qing He; Tingting Li; Fuzhen Zhuang; Zhongzhi Shi)
Abstract	Text clustering is an important technology for automatically structuring large document collections. It is much more valuable in peer-to-peer networks. The high dimensionality of documents means much more communication could be saved if each node could get the approximate clustering result by distributed algorithm instead of transferring them into a center and do the clustering. Most of the existing text clustering algorithms in unstructured peer-to-peer networks are based on K-means algorithm. A problem of those algorithms is that the clustering quality may decreased with the increase of the network size. In this paper, we propose a text clustering algorithm based on frequent term sets for peer-to-peer networks. It requires relatively lower communication volume while achieving a clustering result whose quality will not be affected by the size of the network. Moreover, it gives a term set describing each cluster, which makes it possible for people to have a clear comprehension for the clustering result, and facilitates the users to find resource in the network or manage the local documents in accordance with the whole network.
Starting Page	352
Ending Page	355
File Size	346511
Page Count	4
File Format	PDF
ISBN	9781424480043
e-ISBN	9781424480074
DOI	10.1109/KAM.2010.5646177
Language	English
Publisher	Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Publisher Date	2010-10-20
Publisher Place	China
Access Restriction	Subscribed
Rights Holder	Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Subject Keyword	frequent term set text clustering distributed data mining Copper peer-to-peer
Content Type	Text
Resource Type	Article

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3	National Digital Library of India Office, Indian Institute of Technology Kharagpur	The administrative and infrastructural headquarters of the project	Dr. B. Sutradhar bsutra@ndl.gov.in
4	Project PI / Joint PI	Principal Investigator and Joint Principal Investigators of the project	Dr. B. Sutradhar bsutra@ndl.gov.in Prof. Saswat Chakrabarti will be added soon
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