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review on text clustering algorithms

Author(s):

Manpreet Kaur , Shri Guru Granth Sahib World University; Navpreet Kaur, Shri Guru Granth Sahib World University

Keywords:

Text clustering, Vector Space Model, Latent Semantic Analysis, K-means clustering algorithm, clustering optimization.

Abstract

A clustering algorithm finds a partition of a set of objects that fulfills some criterion based on these conditions. Clustering is an unsupervised method of learning. Most text clustering algorithms are based on the vector space model which has the advantages of simple concept ad convenient applications. While the Latent Semantic analysis method takes the relationship between words into account and supposed to be an improved model of VSM. K-Mean clustering algorithm has shortcoming, which depend on the initial clustering center and needs to fix the number of clusters in advance. Vector Space model has problems, such as high dimensional and sparse. This can be optimized using various optimization techniques such as Genetic algorithm, PSO, pollination Based optimization. Pollination based optimization is inspired by natural flower pollination.

Other Details

Paper ID: IJSRDV2I3075
Published in: Volume : 2, Issue : 3
Publication Date: 01/06/2014
Page(s): 210-213

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