An Innovative Information Retrieval Model Implementing Particle Swarm Optimization Technique

Abstract

The Internet has enormous information and it is growing rapidly. The vast amount of data creates challenges in relation to effective Information Retrieval (IR). The scope of the Information Retrieval System (IRS) is to provide the most relevant data for user query from large datasets. However the current IR system fails to provide the hidden and up to date data. This paper focused on soft computing techniques to overcome the above mentioned issues. Particle Swarm Optimization (PSO) is used to compute the fitness function to optimize the retrieval result. PSO has an efficient capability in global search and the implementation is easy to develop. The implementation result of the present study is feasible, that improves the retrieval effect and the accuracy of hidden data retrieval.