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class-based search system in unstructured peer-to-peer networks

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Date Issued:
2006
Summary:
Efficient searching is one of the important design issues in peer-to-peer (P2P) networks. Among various searching techniques, semantic-based searching has drawn significant attention recently. Gnutella-like efficient searching system (GES) [29] is such a system. GES derives node vector , a semantic summary of all documents on a node based on vector space model (VSM). The node-based topology adaptation algorithm and search protocol are then discussed. However, when there are many categories of documents at each node, the node vector representation may be inaccurate. We extend the idea of GES and present a class-based search system (CSS). It makes use of a document clustering algorithm: OSKM [27] to cluster all documents on a node into several classes. Each class can be viewed as a virtual node. As a result, class vector replaces node vector and plays an important role in class-based topology adaptation and search process, which makes CSS very efficient. Our simulation demonstrates that CSS outperforms GES.
Title: A class-based search system in unstructured peer-to-peer networks.
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Name(s): Huang, Juncheng.
Florida Atlantic University, Degree grantor
Wu, Jie, Thesis advisor
Type of Resource: text
Genre: Electronic Thesis Or Dissertation
Issuance: monographic
Date Issued: 2006
Publisher: Florida Atlantic University
Place of Publication: Boca Raton, Fla.
Physical Form: application/pdf
Extent: 115 p.
Language(s): English
Summary: Efficient searching is one of the important design issues in peer-to-peer (P2P) networks. Among various searching techniques, semantic-based searching has drawn significant attention recently. Gnutella-like efficient searching system (GES) [29] is such a system. GES derives node vector , a semantic summary of all documents on a node based on vector space model (VSM). The node-based topology adaptation algorithm and search protocol are then discussed. However, when there are many categories of documents at each node, the node vector representation may be inaccurate. We extend the idea of GES and present a class-based search system (CSS). It makes use of a document clustering algorithm: OSKM [27] to cluster all documents on a node into several classes. Each class can be viewed as a virtual node. As a result, class vector replaces node vector and plays an important role in class-based topology adaptation and search process, which makes CSS very efficient. Our simulation demonstrates that CSS outperforms GES.
Identifier: 9780542745485 (isbn), 13367 (digitool), FADT13367 (IID), fau:10217 (fedora)
Collection: FAU Electronic Theses and Dissertations Collection
Note(s): College of Engineering and Computer Science
Thesis (M.S.)--Florida Atlantic University, 2006.
Subject(s): Peer-to-peer architecture (Computer networks)
Management information systems
Computer security
Cascading style sheets
Web sites--Design
Held by: Florida Atlantic University Libraries
Persistent Link to This Record: http://purl.flvc.org/fcla/dt/13367
Sublocation: Digital Library
Use and Reproduction: Copyright © is held by the author, with permission granted to Florida Atlantic University to digitize, archive and distribute this item for non-profit research and educational purposes. Any reuse of this item in excess of fair use or other copyright exemptions requires permission of the copyright holder.
Use and Reproduction: http://rightsstatements.org/vocab/InC/1.0/
Host Institution: FAU
Is Part of Series: Florida Atlantic University Digital Library Collections.