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Trend and Behavior Detection from Web Queries

  • Peiling Wang
  • Jennifer Bownas
  • Michael W. Berry

Abstract

In this chapter, we demonstrate the type and nature of query characteristics that can be mined from web server logs. Based on a study of over half a million queries (spanning four academic years) to a university’s website, it is shown that the vocabulary (terms) generated from these queries do not have a well-defined Zipf distribution. However, some regularities in term frequency and ranking correlations suggest that piecewise polynomial data fits are reasonable for trend representations.

Keywords

Search Engine Word Pair Word Association Query Statement Behavior Detection 
These keywords were added by machine and not by the authors. This process is experimental and the keywords may be updated as the learning algorithm improves.

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Copyright information

© Springer Science+Business Media New York 2004

Authors and Affiliations

  • Peiling Wang
  • Jennifer Bownas
  • Michael W. Berry

There are no affiliations available

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