Information Retrieval using Jaccard Similarity Coefficient
||International Journal of Computer Trends and Technology (IJCTT)||
|© 2016 by IJCTT Journal|
|Year of Publication : 2016|
|Authors : Manoj Chahal|
|DOI : 10.14445/22312803/IJCTT-V36P124|
Manoj Chahal "Information Retrieval using Jaccard Similarity Coefficient". International Journal of Computer Trends and Technology (IJCTT) V36(3):140-143, June 2016. ISSN:2231-2803. www.ijcttjournal.org. Published by Seventh Sense Research Group.
Similarity measure define similarity between two or more documents. The retrieved documents are ranked based on the similarity of content of document to the user query. Jaccard similarity coefficient measure the degree of similarity between the retrieved documents. In this paper we retrieved information with the help of Jaccard similarity coefficient and analysis that information. All this is performed with the help of Genetic Algorithm. Due to exploring and exploiting nature of Genetic Algorithm it gives optimal result of our search. Genetic algorithm use Jaccard similarity coefficient to calculate similarity between documents. Value of jaccard similarity function lies between 0 &1 .it show the probability of similarity between the documents.
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Genetic Algorithm, Information Retrieval, Vector Space Model, Database, Jaccard Similarity Measure.