Paper Information

Journal:   INFORMATION SYSTEMS & SERVICES   summer-fall 2016 , Volume 5 , Number 3-4 (19-20) #f00628; Page(s) 33 To 42.
 
Paper: 

The Image retrieval recall and precision rate in the Bing, and Google image search engines

 
 
Author(s):  JALALI DIZAJI ALI*, KHALEGHI REZA, Taheri Seyyed Mahdi
 
* ALLAMEH TABATABAEI UNIVERSITY
 
Abstract: 
Purpose: The study purpose was to determine and compare the Recall and Precision of Bing and Google Image search engines for content based image retrieval. Methodology: The research used webometrics and comparative methods. Population includes images stored in the databases of Bing and Google search engines, and research sample includes 15 selective images searched in any of search engines. All the retrieved sources through the images by image content based image search were gathered, results’ Recall and Precision measures were calculated by relevance formula and their average percentage were obtained. Research hypotheses were tested by U Mann-Whitney test as well. Findings: Findings showed that the Google search engine functionality was higher with recall measure of % 88. 73 than recall rate (%20. 86) for Bing. But Bing search engine had higher precision (% 99. 86) than Google (%94. 80). Results: Hypotheses tests on recall and precision in two search engines’ image retrieval showed a significant difference for recall in favor of Google, indicating its better functionality than Bing but there was no significant difference between them concerning precision since both showed fair precision however Bing was relatively useful.
 
Keyword(s): Bing,Content-based retrieval,Google,Images,Precision,Recall,Search engines
 
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