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Web usage mining at an academic health sciences library: an exploratory study.

Paul J Bracke1

  • 1Arizona Health Sciences Library, 1501 North Campbell Avenue, PO Box 245079, Tucson 85724-5079, USA. paul@ahsl.arizona.edu

Journal of the Medical Library Association : JMLA
|October 21, 2004
PubMed
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Multinomial logistic regression analysis can reveal patterns in academic health sciences library website usage. This method provides insights into user behavior, aiding in website design and future system development.

Area of Science:

  • Library and Information Science
  • Health Informatics
  • Data Mining

Background:

  • Academic health sciences libraries face challenges in understanding user engagement with digital resources.
  • Traditional web log analysis offers limited insights into user navigation patterns and resource preferences.

Purpose of the Study:

  • To explore the utility of multinomial logistic regression analysis for web usage mining in an academic health sciences library context.
  • To identify factors influencing user access patterns to database-driven resources.

Main Methods:

  • Collected six months of usage data for database-driven resource gateway pages.
  • Logged user network addresses, referring uniform resource locators (URLs), and accessed resource types.
  • Applied multinomial logistic regression to analyze the collected web usage data.

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Main Results:

  • Referring URLs significantly varied based on user location (on-campus vs. off-campus).
  • Resource access patterns were significantly influenced by the type of resource being accessed.
  • User network addresses and referring URLs provided valuable data for web usage mining.

Conclusions:

  • Multinomial logistic regression analysis offers a valuable method for web usage mining, complementing traditional web log analysis.
  • Findings can inform the design and optimization of academic library websites and digital resource interfaces.
  • This approach has potential for developing more sophisticated web systems in the future, balancing utility with privacy concerns.