Intelligent content-based retrieval for peer-to-peer networks

Intelligent content-based retrieval for peer-to-peer networks

In this thesis, we propose an intelligent P2P content-based document retrieval system known as iSearch-P2P. In iSearch-P2P, we have incorporated several intelligent techniques including Fuzzy Adaptive Resonance Theory (Fuzzy ART), Support Vector Machine (SVM) and k-Nearest Neighbor (k-NN) to perform...

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Bibliographic Details
Main Author: Rodionov Maxim.
Other Authors: Hui, Siu Cheung
Format: Theses and Dissertations
Published: 2008
Subjects:
DRNTU::Engineering::Computer science and engineering::Information systems::Information storage and retrieval
Online Access:http://hdl.handle.net/10356/2436
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Institution: Nanyang Technological University
Description
Summary:In this thesis, we propose an intelligent P2P content-based document retrieval system known as iSearch-P2P. In iSearch-P2P, we have incorporated several intelligent techniques including Fuzzy Adaptive Resonance Theory (Fuzzy ART), Support Vector Machine (SVM) and k-Nearest Neighbor (k-NN) to perform document clustering in order to support content-based publishing and retrieval over P2P networks. In this thesis, we first review the related research work. The architecture, publishing and retrieval processes, implementation and performance evaluation of the proposed iSearch-P2P system are then discussed.

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