Name
Title | ||
|---|---|---|
A comparative analysis of the search feature effectiveness of the major English and Chinese search engines. |
Abstract | ||
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Purpose The purpose of this paper to investigate the effectiveness of selected search features in the major English and Chinese search engines and compare the search engines' retrieval effectiveness. Design/approach/methodology - The search engines Google, Google China, and Baidu were selected for this study. Common search features such as title search, basic search, exact phrase search, PDF search, and URL search, were identified and used. Search results from using the five features in the search engines were collected and compared. One-way ANOVA and regression analysis were used to compare the retrieval effectiveness of the search engines. Findings - It was found that Google achieved the best retrieval performance with all five search features among the three search engines. Moreover Google achieved the best webpage ranking performance. Practical implications - The findings of this study improve the understanding of English and Chinese search engines and the differences between them in terms of search features, and can be used to assist users in choosing appropriate and effective search strategies when they search for information on the internet. Originality/value - The original contributions of this paper are that the Chinese and English search engines in both languages are compared for retrieval effectiveness. Five search features were evaluated, compared, and analysed in the two different language environments by using the discounted cumulative gain method. |
Year | DOI | Venue |
|---|---|---|
2013 | 10.1108/OIR-07-2011-0099 | ONLINE INFORMATION REVIEW |
Keywords | Field | DocType |
Search engines,Search feature,Retrieval effectiveness,Evaluation,Google,Google China,Baidu,Information retrieval | World Wide Web,Metasearch engine,Phrase search,Information retrieval,Google penalty,Computer science,Search engine optimization,Full text search,Search engine indexing,Search analytics,Spamdexing | Journal |
Volume | Issue | ISSN |
37.0 | 2.0 | 1468-4527 |
Citations | PageRank | References |
2 | 0.38 | 11 |
Authors | ||
3 | ||