A Survey on Application of Particle Swarm Optimization in Text Mining

Text Mining is the discovery of new previously unknown information, by automatically extracting information from a usually large amount of data set. Many algorithms have been developed in recent years for solving problems of numerical and combinatorial optimization problems. Most efficient among them are swarm intelligence algorithms. Clustering using PSO is being used as an alternative to more conventional clustering techniques. PSO is population-based stochastic search algorithms that impersonate the capability of swarm. Data clustering with PSO algorithms are being used to produce better outcomes in a wide variety of real-world data. In this paper, a brief survey on PSO application in data clustering is described.