Identifying queries in the wild, wild Web

Jingjing Liu, Chang Liu, Jun Zhang, Ralf Bierig, Michael Cole

Research output: Chapter in Book/Report/Conference proceedingConference contribution

Abstract

Identifying user querying behavior is an important problem for information seeking and retrieval research. Query-related studies typically rely on server-side logs taken from a single search engine, but a comprehensive view of user querying behaviors requires analysis of data collected from the client-side for unrestricted searches. We developed three methods to identify querying behaviors and tested them on client-side logs collected in a lab experiment for realistic tasks and unrestricted searches on the entire Web. Results show that the best method was able to identify 97% of queries issued, with a precision of 92%. Although based on a relatively small number of search episodes, our methods, perhaps with minimal modifications, should be adequate for identification of queries in logs of unconstrained Web search.

Original languageEnglish (US)
Title of host publicationIIiX 2010 - Proceedings of the 2010 Information Interaction in Context Symposium
Pages317-320
Number of pages4
DOIs
StatePublished - 2010
Externally publishedYes
Event3rd Information Interaction in Context Symposium, IIiX'10 - New Brunswick, NJ, United States
Duration: Aug 18 2010Aug 21 2010

Publication series

NameIIiX 2010 - Proceedings of the 2010 Information Interaction in Context Symposium

Conference

Conference3rd Information Interaction in Context Symposium, IIiX'10
Country/TerritoryUnited States
CityNew Brunswick, NJ
Period8/18/108/21/10

Keywords

  • Query identification
  • Query log analysis
  • Unrestricted search
  • User studies
  • Web search logs

ASJC Scopus subject areas

  • Human-Computer Interaction
  • Information Systems

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