A Study on Effective Measurement of Search Results from Search Engines

Jin Zhang, Xin Cai, Taowen Le, Wei Fei, Feicheng Ma

Source Title: Journal of Global Information Management (JGIM)27(1)

ISSN: 1062-7375|EISSN: 1533-7995|EISBN13: 9781522563709|DOI: 10.4018/JGIM.2019010110

MLA

Zhang, Jin, et al. "A Study on Effective Measurement of Search Results from Search Engines." JGIM vol.27, no.1 2019: pp.196-221. http://doi.org/10.4018/JGIM.2019010110

APA

Zhang, J., Cai, X., Le, T., Fei, W., & Ma, F. (2019). A Study on Effective Measurement of Search Results from Search Engines. Journal of Global Information Management (JGIM), 27(1), 196-221. http://doi.org/10.4018/JGIM.2019010110

Chicago

Zhang, Jin, et al. "A Study on Effective Measurement of Search Results from Search Engines," Journal of Global Information Management (JGIM) 27, no.1: 196-221. http://doi.org/10.4018/JGIM.2019010110

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Abstract

This article describes how as internet technology continues to change and improve lives and societies worldwide, effective global information management becomes increasingly critical, and effective Internet information retrieval systems become more and more significant in providing Internet users worldwide with accurate and complete information. Search engine evaluation is an important research field as search engines directly determine the quality of information users' Internet searches. Relevance-decrease pattern/model plays an important role in search engine result evaluation. This research studies effective measurement of search results through investigating relevance-decrease patterns of search results from two popular search engines: Google and Bing. The findings can be applied to relevance-evaluation of search results from other information retrieval systems such as OPAC, can help make search engine evaluations more accurate and sound, and can provide global information management personnel with valuable insights.