Improving ant colony optimization algorithm for data clustering
Raj Gaurang Tiwari, M. N. Husain, Shivangi Gupta, Abhinav Srivastava · 2010
Data mining is a process that uses technology to bridge the gap between data and logical decision-making. The jargon itself offers a promising view of organized data manipulation for extracting valuable information and knowledge from high volume of data. Copious techniques are developed to fulfill this aspiration. This paper outlines an ant colony optimization algorithm which is used newly in data mining mostly aiming solve data-clustering and data-classification problems and developed from imitating the technique of real ants finding the shortest way from their nests and the food source. This paper embodies an application aiming to cluster a data set with ant colony optimization algorithm and to increase the working performance of ant colony optimization algorithm used for solving data-clustering problem. We also propose two new techniques and show the increase on the performance with the addition of these suggested techniques.