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ERIC Number: EJ1210894
Record Type: Journal
Publication Date: 2019-Mar
Pages: 16
Abstractor: As Provided
ISSN: EISSN-1368-1613
Evaluating the Effectiveness of Web Search Engines on Results Diversification
Wu, Shengli; Zhang, Zhongmin; Xu, Chunlin
Information Research: An International Electronic Journal, v24 n1 Mar 2019
Introduction: Recently, the problem of diversification of search results has attracted a lot of attention in the information retrieval and Web search research community. For multi-faceted or ambiguous queries, a search engine is generally favoured if it is able to identify relevant documents on a wider range of different aspects. Method: We evaluate the performance of three major Web search engines: Google, Bing and Ask manually using 200 multi-faceted or ambiguous queries from TREC. Analysis: Both classical metrics and intent-aware metrics are used to evaluate search results. Results: Experimental results show that on average Bing and Google are comparable and Ask is slightly worse than the former two. However, Ask does very well in one subtype of queries -- ambiguous queries. The average performance of the three search engines is better than the average of the top two runs submitted to the TREC web diversity task in 2009-2012. Conclusions: Generally, all three Web search engines do well, this indicates that all of them must use state-of-the-art technology to support the diversification of search results.
Thomas D. Wilson. 9 Broomfield Road, Broomhill, Sheffield, S10 2SE, UK. Web site:
Publication Type: Journal Articles; Reports - Research
Education Level: N/A
Audience: N/A
Language: English
Sponsor: N/A
Authoring Institution: N/A