A new fuzzy logic based ranking function for efficient Information Retrieval system. Issue 3 (15th February 2015)

• Record Type: Journal Article
• Authors: Gupta, Yogesh; Saini, Ashish; Saxena, A.K.
• Is Part Of: Expert systems with applications. Volume 42:Issue 3(2015)
• Page Start: 1223
• Page End: 1234
• Publication Date: 2015-02-15
• Subjects: Expert systems (Computer science) -- Periodicals; Systèmes experts (Informatique) -- Périodiques; Electronic journals; 006.33
• DOI: 10.1016/j.eswa.2014.09.009
• Languages: English
• ISSNs: 0957-4174

Abstract

<abstract xml:lang="en" abstract-type="author-highlights" id="ab005"> <title id="st100">Highlights</title> <sec> <p id="sp0005"> <list id="l0005"> <list-item id="o0005"> <label></label> <p id="p0240">A fuzzy logic based ranking function is proposed to enhance Information Retrieval.</p> </list-item> <list-item id="o0010"> <label></label> <p id="p0245">It is based on Composite Fuzzy Inference System with 259 fuzzy rules.</p> </list-item> <list-item id="o0015"> <label></label> <p id="p0250">The performance is tested in terms of precision, recall and F-measure on <italic>CACM</italic> and <italic>CISI</italic>.</p> </list-item> <list-item id="o0020"> <label></label> <p id="p0255">The better results are obtained as compared to <italic>Okapi-BM25</italic> and Rubens' approach.</p> </list-item> <list-item id="o0025"> <label></label> <p id="p0260">A paired <italic>t-test</italic> is also conducted to perform statistical analysis.</p> </list-item> </list> </p> </sec> </abstract>