Correlation Coefficient Based Average Textual Similarity Model for Information Retrieval System in Wide Area Networks

In wide area networks, retrieving the relevant text is a challenging task for information retrieval because most of the information requests are text based. The focus of paper is on the similarity measurement, performance evaluation and design of information retrieval techniques using the four similarity functions i.e. Jaccard, Cosine, Dice and Overlap. The performance evaluation of these similarity functions has been done for the similarity between the documents retrieved by the search engine for the entered text using the vector space model. The correlation coefficient was applied for evaluating the performance of similarity functions. All the possible combination of similarity functions have been explored and textual similarity model has been proposed for the information retrieval system in wide area networks.