Application of data mining based on artificial immunity in marketing

Abstract

Facing fierce market competition, how to make the effective marketing strategy rapidly according to the market demand is of vital importance to the survival and development of enterprises. Data mining can discover and extract the latent predictable information from the large database and data warehouse. Using this technology, marketers may obtain potential associations among sales data, so that they can make a market analysis, adopt pertinent marketing strategy, reduce costs and raise profits. This paper proposes an algorithm of association rule mining based on artificial immunity. Practice proves that this algorithm is robustness, hidden parallelism and commonality. It can discover useful association rule from sales data rapidly and effectively, and provide forceful support for enterprises to make accurate marketing strategy. © 2008 International Federation for Information Processing.