Mining longitudinal web queries: trends and patterns

  • Authors:

  • Peiling Wang;Michael W. Berry;Yiheng Yang

  • Affiliations:

  • School of Information Sciences, The University of Tennessee, Knoxville, Tennessee;Department of Computer Science, The University of Tennessee, Knoxville, Tennessee;Department of Computer Science, The University of Tennessee, Knoxville, Tennessee

  • Venue:
  • Journal of the American Society for Information Science and Technology
  • Year:
  • 2003

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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 data-base. 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.