High Dimensional Data Clustering Using Ant Based Algorithm
The Information Retrieval (IR) system is facing lot of challenges due to the widespread usage of computers for mass storage and the availability of tremendous information in World Wide Web. Clustering of documents available improves the efficiency of IR system. The problem of clustering has become a combinatorial optimization problem in IR system due to the exponential growth in information over WWW. In this paper, a hybrid algorithm that combines the basic Ant Colony Optimization with Tabu search has been proposed. The feasibility of the proposed algorithm is tested over a few standard benchmark datasets. The experimental results reveal that the proposed algorithm yields promising quality clusters compared to other ones produced by K-means algorithm.