Exploring and Comparing the Performance of Search Engines and Meta Search Engines in Retrieving Information in the Field of Information Sciences and Knowledge Studies

Document Type : Original Article

Authors

1 Department of knowledge and information science, University of Isfahan, Isfahan, Iran

2 Department of knowledge and information science, University of Isfahan, Isfahan, Iran.

Abstract

Purpose: the purpose of this study was to explore and compare the performance of search engines and meta search engines in information retrieval of information science and knowledge science.
Methodology: the research is applied one and in semi-experimental design. The statistical population consisted of all search engines and meta search engines active on the web divided into two categories of exploratory engines and exploratory meta search based on randomized sampling. In these two categories, seven search engines were selected based on purposeful sampling and five metasearch engines were also selected from www.searchenginewatch.com.
Findings: among the seven search engine searches, Google search engine obtained the highest precision in retrieving relevant information, and among the five metasearch engines metagofer was identified as having the most precision. Moreover, the Google search engine and Yandex have the most overlap, and gigablast search engine showed the lowest overlap with the other search engines.
Conclusion: search engines and metasearch engines have the same function in retrieving information related to the field of information Science and Knowledge Studies. The hypothesis of the research regarding the better performance in information retrieval has been rejected due the achieved results.  However, in relation with overlap issues metasearch engines are of higher preference.



Keywords

References

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Sciences and Techniques of Information Management
Volume 5, Issue 2 - Serial Number 15
September 2019
Pages 91-118

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