A technique for measuring the relative size and overlap of public Web search engines
WWW7 Proceedings of the seventh international conference on World Wide Web 7
Analysis of a very large web search engine query log
ACM SIGIR Forum
Scholarly use of Internet-based electronic resources
Journal of the American Society for Information Science and Technology
Measuring Search Engine Quality
Information Retrieval
U.S. versus European web searching trends
ACM SIGIR Forum
SIAM Journal on Discrete Mathematics
New measurements for search engine evaluation proposed and tested
Information Processing and Management: an International Journal
Methods for comparing rankings of search engine results
Computer Networks: The International Journal of Computer and Telecommunications Networking - Web dynamics
A study of results overlap and uniqueness among major web search engines
Information Processing and Management: an International Journal
Agreeing to disagree: search engines and their public interfaces
Proceedings of the 7th ACM/IEEE-CS joint conference on Digital libraries
Location approximation for local search services using natural language hints
International Journal of Geographical Information Science
Mapping world-class universities on the web
Information Processing and Management: an International Journal
A generic construct based workload model for web search
Information Processing and Management: an International Journal
Web search solved?: all result rankings the same?
CIKM '10 Proceedings of the 19th ACM international conference on Information and knowledge management
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The Web has become an information source for professional data gathering. Because of the vast amounts of information on almost all topics, one cannot systematically go over the whole set of results, and therefore must rely on the ordering of the results by the search engine. It is well known that search engines on the Web have low overlap in terms of coverage. In this study we measure how similar are the rankings of search engines on the overlapping results.We compare rankings of results for identical queries retrieved from several search engines. The method is based only on the set of URLs that appear in the answer sets of the engines being compared. For comparing the similarity of rankings of two search engines, the Spearman correlation coefficient is computed. When comparing more than two sets Kendall's W is used. These are well-known measures and the statistical significance of the results can be computed. The methods are demonstrated on a set of 15 queries that were submitted to four large Web search engines. The findings indicate that the large public search engines on the Web employ considerably different ranking algorithms.