A search tool using genetic algorithm

Abstract

In the current business scenario, with explosive growth of the amount of information resources available over the Internet and Intranets in any organization, the retrieval of the required information at the spot and time of requirement is very essential, for the effective performance of the organization, by reducing the process time and meeting customer satisfaction of meeting delivery schedule. When the number of document collection and users of the document go beyond an extent, an efficient search tool for the retrieving the information from the collection of documents becomes vital. Actual information retrieval means searching for keyword within documents. This study investigates the various stages of information retrieval, selection of best method for implementation at each stage and optimizing the solution using of genetic algorithm with different parameters. The method is tested with a training data of document collections, where more relevant documents are presented to users in the genetic modification. In this paper a new fitness function is presented in the genetic algorithm for appropriate information retrieval which is found to be efficient than other fitness functions. © 2011 Springer-Verlag.