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Swarm Intelligence and Evolutionary Computation: Overview and Analysis Read chapter Read first chapter

2015 | OriginalPaper | Chapter

Web Document Clustering by Using PSO-Based Cuckoo Search Clustering Algorithm

Authors : Moe Moe Zaw, Ei Ei Mon

Published in: Recent Advances in Swarm Intelligence and Evolutionary Computation

Publisher: Springer International Publishing

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Abstract

With the increasing amount of web information, web document clustering plays an important role in Information Retrieval. This paper presents a PSO-based Cuckoo Search Clustering Algorithm to combine the strengths of Cuckoo Search and Particle Swarm. The solutions of new cuckoos are based on the solutions of PSO. Among these solutions, the algorithm will replace some eggs on lack of fitness with successful solutions until an optimal solution emerges. The proposed hybrid algorithm is tested with a web document benchmark dataset and the results show that it performs well in web document clustering area.

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previous chapter Evaluation of Harmony Search and Differential Evolution Optimization Algorithms on Solving the Booster Station Optimization Problems in Water Distribution Networks
next chapter Geometrically Nonlinear Analysis of Trusses Using Particle Swarm Optimization
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Metadata
Title
Web Document Clustering by Using PSO-Based Cuckoo Search Clustering Algorithm
Authors
Moe Moe Zaw
Ei Ei Mon
Copyright Year
2015
Book
Recent Advances in Swarm Intelligence and Evolutionary Computation

Print ISBN: 978-3-319-13825-1

Electronic ISBN: 978-3-319-13826-8

Copyright Year: 2015

DOI
https://doi.org/10.1007/978-3-319-13826-8_14

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