Google, Bing and a new perspective on ranking similarity

Research output: Chapter in Book/Report/Conference proceedingConference contributionpeer-review

3 Citations (Scopus)


In this paper, we propose a framework to characterize and compare two search engine results. Typical user-queries are ambiguous and, consequentially, each search engine will compute ranks in different manners, attempting to answer them in the best possible way. Thus, each search engine will have its own bias. Given the importance of the first page results in Web Search Engines, in this paper we propose a framework to assess the information presented in the first page by measuring the information entropy and the correlations between two ranks. Employing the recently proposed Rank-Biased Overlap measure [2] we compare to which extent do Bing and Google rankings in fact differ. We also extend this measure and propose a measure for comparing the information entropy present in two ranks. The proposed measure is based on the correlation of two ranks and the application of Jensen-Shannon's divergence among two document sets. Our methodology starts with 40,000 user queries and crawls the search results for these queries on both search engines. The results allow us to determine the search engines correlations, crawling coverage, information overlap, and information entropy.

Original languageEnglish
Title of host publicationCIKM'11 - Proceedings of the 2011 ACM International Conference on Information and Knowledge Management
PublisherAssociation for Computing Machinery
Number of pages4
ISBN (Print)9781450307178
Publication statusPublished - 2011
Event20th ACM Conference on Information and Knowledge Management, CIKM'11 - Glasgow, United Kingdom
Duration: 24 Oct 201128 Oct 2011


Conference20th ACM Conference on Information and Knowledge Management, CIKM'11
Country/TerritoryUnited Kingdom


  • content aware rank similarity
  • jensen-shannon divergence
  • rank-biased overlap
  • search engines comparison


Dive into the research topics of 'Google, Bing and a new perspective on ranking similarity'. Together they form a unique fingerprint.

Cite this