THE PROPOSAL OF TWO BIO-INSPIRED ALGORITHMS FOR TEXT CLUSTERING

The Internet can be seen as a major repository of resources and information. The growing demand for information, along with the large amount of data available, has been stimulating the research of methods for text mining. This work aims at using feature selection and text clustering techniques based on a Particle Swarm Clustering (PSC) algorithm and on an Artificial Neural Network modeled as a competitive and constructive Antibody Network, called RABNET (Real-valued Antibody Network), to show that both techniques present relevant results when applied to text clustering problems.

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