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Trend and Behavior Detection from Web Queries

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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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© 2004 Springer Science+Business Media New York

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Wang, P., Bownas, J., Berry, M.W. (2004). Trend and Behavior Detection from Web Queries. In: Berry, M.W. (eds) Survey of Text Mining. Springer, New York, NY. https://doi.org/10.1007/978-1-4757-4305-0_8

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  • DOI: https://doi.org/10.1007/978-1-4757-4305-0_8

  • Publisher Name: Springer, New York, NY

  • Print ISBN: 978-1-4419-3057-6

  • Online ISBN: 978-1-4757-4305-0

  • eBook Packages: Springer Book Archive