In true 2.0 “practice what you preach” fashion – it’s available in a variety of formats!

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• Video of the report presentation
• Read the study’s wiki
• Good old fashioned PDF

Enhancing Search and Browse Using Automated Clustering of Subject Metadata by Kat Hagedorn, Suzanne Chapman, and David Newman. D-Lib Magazine
July/August 2007, Volume 13 Number 7/8.

Abstract:

…The University of Michigan and the University of California Irvine joined forces to test automatically enhancing metadata records using the Topic Modeling algorithm on the varied OAIster corpus. We created labels for the resulting clusters of metadata records, matched the clusters to an in-house classification system, and developed a prototype that would showcase methods for search and retrieval using the enhanced records. Results indicated that while the algorithm was somewhat time-intensive to run and using a local classification scheme had its drawbacks, precise clustering of records was achieved and the prototype interface proved that faceted classification could be powerful in helping end-users find resources.