Web usage mining at an academic health sciences library: an exploratory study.
OBJECTIVE
This paper explores the potential of multinomial logistic regression analysis to perform Web usage mining for an academic health sciences library Website.


METHODS
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.


RESULTS
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.


CONCLUSIONS
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.
Bracke
Paul J
PJ
Arizona Health Sciences Library, 1501 North Campbell Avenue, PO Box 245079, Tucson 85724-5079, USA. paul@ahsl.arizona.edu
D000046:Academic Medical Centers / Q000592:standards; D016206:Databases, Bibliographic / Q000706:statistics & numerical data; D006801:Humans; D016247:Information Storage and Retrieval / Q000706:statistics & numerical data*; D020407:Internet / Q000706:statistics & numerical data*; D007993:Libraries, Medical / Q000592:standards* / Q000706:statistics & numerical data; D007999:Library Services / Q000706:statistics & numerical data*; D016015:Logistic Models; D014481:United States