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Mining longitudinal web queries: Trends and patterns

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  • Peiling Wang
  • Michael W. Berry
  • Yiheng Yang

Abstract

This project analyzed 541,920 user queries submitted to and executed in an academic Website during a four‐year period (May 1997 to May 2001) using a relational database. The purpose of the study is three‐fold: (1) to understand Web users' query behavior; (2) to identify problems encountered by these Web users; (3) to develop appropriate techniques for optimization of query analysis and mining. The linguistic analyses focus on query structures, lexicon, and word associations using statistical measures such as Zipf distribution and mutual information. A data model with finest granularity is used for data storage and iterative analyses. Patterns and trends of querying behavior are identified and compared with previous studies.

Suggested Citation

  • Peiling Wang & Michael W. Berry & Yiheng Yang, 2003. "Mining longitudinal web queries: Trends and patterns," Journal of the American Society for Information Science and Technology, Association for Information Science & Technology, vol. 54(8), pages 743-758, June.
    • Handle: RePEc:bla:jamist:v:54:y:2003:i:8:p:743-758
    DOI: 10.1002/asi.10262
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    Cited by:

    1. Jennifer Ann Stevenson & Jin Zhang, 2015. "A temporal analysis of institutional repository research," Scientometrics, Springer;Akadémiai Kiadó, vol. 105(3), pages 1491-1525, December.
    2. Aurora González-Teruel & Gregorio González-Alcaide & Maite Barrios & María-Francisca Abad-García, 2015. "Mapping recent information behavior research: an analysis of co-authorship and co-citation networks," Scientometrics, Springer;Akadémiai Kiadó, vol. 103(2), pages 687-705, May.
    3. Jia Liu & Olivier Toubia, 2018. "A Semantic Approach for Estimating Consumer Content Preferences from Online Search Queries," Marketing Science, INFORMS, vol. 37(6), pages 930-952, November.

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