A PSO Strategy of Finding Relevant Web Documents using a New Similarity Measure

TL;DR

This paper introduces a novel similarity measure called SMDR for web document retrieval, combined with a bio-inspired PSO algorithm to improve accuracy and response time in web information retrieval systems, validated through experiments on CACM collections.

Contribution

It proposes a new similarity measure SMDR and integrates it with PSO to enhance web document retrieval effectiveness and efficiency.

Findings

Higher precision-recall rates achieved.

Improved accuracy, sensitivity, and F-measure.

Reduced response time of the retrieval system.

Abstract

In the world of the Internet and World Wide Web, which offers a tremendous amount of information, an increasing emphasis is being given to searching services and functionality. Currently, a majority of web portals offer their searching utilities, be it better or worse. These can search for the content within the sites, mainly text the textual content of documents. In this paper a novel similarity measure called SMDR (Similarity Measure for Documents Retrieval) is proposed to help retrieve more similar documents from the repository thus contributing considerably to the effectiveness of Web Information Retrieval (WIR) process. Bio-inspired PSO methodology is used with the intent to reduce the response time of the system and optimizes WIR process, hence contributes to the efficiency of the system. This paper also demonstrates a comparative study of the proposed system with the existing method in terms of accuracy, sensitivity, F-measure and specificity. Finally, extensive experiments are conducted on CACM collections. Better precision-recall rates are achieved than the existing system. Experimental results demonstrate the effectiveness and efficiency of the proposed system.