Use of classification models based on usage data for the selection of infobutton resources.


Journal Article

"Infobuttons" are information retrieval tools that predict the questions and the on-line information resources that a clinician may need in a particular context. The goal of this study was to employ infobutton usage data to produce classification models that predict the information resource that is most likely to be selected by a user in a given context.Data mining techniques were applied to a dataset with 13 attributes and 7,968 infobutton sessions conducted in a six-month period. Five classification models were generated and compared in terms of prediction performance.All classification models performed statistically better than the implementation currently in use at our institution. Two to five attributes were sufficient for the models to achieve their best performance.The application of data mining tools over infobutton usage data is a promising strategy to further improve the prediction capability of infobuttons.

Full Text

Duke Authors

Cited Authors

  • Del Fiol, G; Haug, PJ

Published Date

  • October 11, 2007

Published In

Start / End Page

  • 171 - 175

PubMed ID

  • 18693820

Pubmed Central ID

  • 18693820

Electronic International Standard Serial Number (EISSN)

  • 1942-597X


  • eng