By Topic

Content-Based Clustered P2P Search Model Depending on Set Distance

Sign In

Cookies must be enabled to login.After enabling cookies , please use refresh or reload or ctrl+f5 on the browser for the login options.

Formats Non-Member Member
$31 $13
Learn how you can qualify for the best price for this item!
Become an IEEE Member or Subscribe to
IEEE Xplore for exclusive pricing!
close button

puzzle piece

IEEE membership options for an individual and IEEE Xplore subscriptions for an organization offer the most affordable access to essential journal articles, conference papers, standards, eBooks, and eLearning courses.

Learn more about:

IEEE membership

IEEE Xplore subscriptions

2 Author(s)
Jing Wang ; Dept. of Comput. Sci., Univ. of Sci. & Technol. of China, Hefei ; Shoubao Yang

The main issues that affect query efficiency and search cost in content-based unstructured P2P search system are the complexity of computing the similarity of the documents brought by high dimensions and the great deal of redundant messages coming with flooding. This paper defines the documents similarity by the way of set distance. This method restrains the complexity of computing the document similarity in linear time. Also, this paper clusters the peers based on content by their set distance to reduce the query time and redundant messages. Simulations show that the content-based search model constructed by set distance not only has higher recall, but also reduce the search cost and query time to the rate of 40% and 30% of Gnutella

Published in:

Web Intelligence and Intelligent Agent Technology Workshops, 2006. WI-IAT 2006 Workshops. 2006 IEEE/WIC/ACM International Conference on

Date of Conference:

Dec. 2006