290 Copyright © 2014, IGI Global. Copying or distributing in print or electronic forms without written permission of IGI Global is prohibited. Chapter 14 A New Approach for Suggesting Takeover Targets Based on Computational Intelligence and Information Retrieval Methods: A Case Study from the Indian Software Industry ABSTRACT In recent years researchers in financial management have shown considerable interest in predicting future takeover target companies in merger and acquisition (M&A) scenarios. However, most of these predictions are based upon multiple instances of previous takeovers. Now consider a company that is at the early stage of its acquisition spree and therefore has only limited data of possibly only a single previous takeover. Traditional studies on M&A, based upon statistical records of multiple previous takeovers, may not be suitable for suggesting future takeover targets for this company since the lack of history data strongly limits the applicability of statistical techniques. The challenge then is to extract as much knowledge as possible from the single/limited takeover history in order to guide this company during future takeover selections. Under such an extreme case, the authors present a new algorithmic approach for suggesting future takeover targets for acquiring companies based on solely one previous Satyakama Paul University of Johannesburg, South Africa Andreas Janecek University of Vienna, Austria Fernando Buarque de Lima Neto University of Pernambuco, Brazil Tshilidzi Marwala University of Johannesburg, South Africa DOI: 10.4018/978-1-4666-4991-0.ch014