Text document classification using swarm intelligence
A.L. Vizine, Leandro Nunes de Castro, Ricardo Gudwin · 2006
This paper presents an algorithm for the automatic grouping of PDF documents, and with potential application for Web document classification. The algorithm developed is based on an ant-clustering algorithm, which was inspired by the behavior of some ant species in the organization their nests. To apply the ant-clustering algorithm for text document classification, two modifications had to be introduced in the standard algorithm: 1) the use of a metric to evaluate the similarity degree of text data, instead of numeric data; and 2) the proposal of a cooling schedule for a user-defined parameter so as to improve the convergence properties of the algorithm. To illustrate the behavior of the modified algorithm, it was applied to sets of real-world documents taken from the IEEE WCCI -1998 CD.