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

This paper explores the potential of multinomial logistic regression analysis to perform Web usage mining for an academic health sciences library Website. Usage of database-driven resource gateway pages was logged for a six-month period, including information about users' network addresses, ref...

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Bibliographic Details
Published in:Journal of the Medical Library Association 2004-10, Vol.92 (4), p.421-428
Main Author: BRACKE, Paul J
Format: Article
Language:English
Subjects:
Academic libraries
Academic Medical Centers - standards
Data mining
Databases, Bibliographic - statistics & numerical data
Exact sciences and technology
Health care
Humans
Information and communication sciences
Information science. Documentation
Information Storage and Retrieval - statistics & numerical data
Information Storage and Retrieval - utilization
Internet - statistics & numerical data
Internet - utilization
Libraries, Medical - standards
Libraries, Medical - statistics & numerical data
Library and information science. General aspects
Library Services - statistics & numerical data
Library Services - utilization
Logistic Models
Medical libraries
Medicine
Online information retrieval
Regression analysis
Sciences and techniques of general use
Searching
United States
Use and user studies. Information needs
User surveys
Web site design
Web sites
World Wide Web
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Summary:This paper explores the potential of multinomial logistic regression analysis to perform Web usage mining for an academic health sciences library Website. Usage of database-driven resource gateway pages was logged for a six-month period, including information about users' network addresses, referring uniform resource locators (URLs), and types of resource accessed. It was found that referring URL did vary significantly by two factors: whether a user was on-campus and what type of resource was accessed. Although the data available for analysis are limited by the nature of the Web and concerns for privacy, this method demonstrates the potential for gaining insight into Web usage that supplements Web log analysis. It can be used to improve the design of static and dynamic Websites today and could be used in the design of more advanced Web systems in the future.
ISSN:1536-5050
1558-9439