文章基本信息

标题：Information Retrieval using Jaccard Similarity Coefficient
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作者：Manoj Chahal
期刊名称：International Journal of Computer Trends and Technology
电子版ISSN：2231-2803
出版年度：2016
卷号：36
期号：3
页码：140-143
DOI：10.14445/22312803/IJCTT-V36P124
出版社：Seventh Sense Research Group
摘要：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.
关键词：Genetic Algorithm; Information Retrieval; Vector Space Model; Database; Jaccard SimilarityMeasure.