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Assessing bias in search engines

Authors
Journal
Information Processing & Management
0306-4573
Publisher
Elsevier
Publication Date
Volume
38
Issue
1
Identifiers
DOI: 10.1016/s0306-4573(01)00020-6
Keywords
  • Bias
  • Search Engines
  • Retrieval Performance
  • System Measurement
Disciplines
  • Computer Science

Abstract

Abstract This paper deals with the measurement of bias in search engines on the World Wide Web. Bias is taken to mean the balance and representativeness of items in a collection retrieved from a database for a set of queries. This calls for assessing the degree to which the distribution of items in a collection deviates from the ideal. Ascertaining this ideal poses problems similar to those associated with determining relevance in the measurement of recall and precision. Instead of enlisting subject experts or users to determine such an ideal, a family of comparable search engines is used to approximate it for a set of queries. The distribution is obtained by computing the frequencies of occurrence of the uniform resource locators (URLs) in the collection retrieved by several search engines for the given queries. Bias is assessed by measuring the deviation from the ideal of the distribution produced by a particular search engine.

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