Name
Abstract | ||
|---|---|---|
This paper examines a real-time measure of bias in Web search engines. The measure captures the degree to which the distribution of URLs, retrieved in response to a query, deviates from an ideal or fair distribution for that query. This ideal is approximated by the distribution produced by a collection of search engines. Differences between bias and classical retrieval measures are highlighted by examining the possibilities for bias in four extreme cases of recall and precision. The results of experiments examining the influence on bias measurement of subject domains, search engines, and search terms are presented. Three general conclusions are drawn: (1) the performance of search engines can be distinguished with the aid of the bias measure; (2) bias values depend on the subject matter under consideration; (3) choice of search terms does not account for much of the variance in bias values. These conclusions underscore the need to develop "bias profiles" for search engines. |
Year | DOI | Venue |
|---|---|---|
2005 | 10.1016/j.ipm.2004.05.005 | Inf. Process. Manage. |
Keywords | Field | DocType |
search engines,bias measure,bias measurement,bias profile,search engine profiles,retrieval performance,search engine,real-time measure,statistical analysis of bias measure,web search engine,bias value,bias,search term,classical retrieval measure,fair distribution,search engine bias,statistical analysis,real time | Data mining,Search engine,Information retrieval,Computer science,Precision and recall,Selection bias,Statistical analysis | Journal |
Volume | Issue | ISSN |
41 | 5 | Information Processing and Management |
Citations | PageRank | References |
14 | 0.97 | 12 |
Authors | ||
2 | ||
Name | Order | Citations | PageRank |
|---|---|---|---|
| Abbe Mowshowitz | 1 | 563 | 124.43 |
| Akira Kawaguchi | 2 | 308 | 66.67 |