Document clustering evaluation : Divergence from a random baseline

De Vries, Christopher M., Geva, Shlomo, & Trotman, Andrew (2012) Document clustering evaluation : Divergence from a random baseline. In Workshop "Information Retrieval 2012" (IR-2012), 12-14 September, 2012, Technical University of Dortmund, Dortmund, Germany.


Divergence from a random baseline is a technique for the evaluation of document clustering. It ensures cluster quality measures are performing work that prevents ineffective clusterings from giving high scores to clusterings that provide no useful result. These concepts are defined and analysed using intrinsic and extrinsic approaches to the evaluation of document cluster quality. This includes the classical clusters to categories approach and a novel approach that uses ad hoc information retrieval. The divergence from a random baseline approach is able to differentiate ineffective clusterings encountered in the INEX XML Mining track. It also appears to perform a normalisation similar to the Normalised Mutual Information (NMI) measure but it can be applied to any measure of cluster quality. When it is applied to the intrinsic measure of distortion as measured by RMSE, subtraction from a random baseline provides a clear optimum that is not apparent otherwise. This approach can be applied to any clustering evaluation. This paper describes its use in the context of document clustering evaluation.

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ID Code: 53371
Item Type: Conference Paper
Refereed: Yes
Additional URLs:
Keywords: document clustering, evaluation, collection selection, XML mining, clustering
Subjects: Australian and New Zealand Standard Research Classification > INFORMATION AND COMPUTING SCIENCES (080000) > ARTIFICIAL INTELLIGENCE AND IMAGE PROCESSING (080100) > Pattern Recognition and Data Mining (080109)
Australian and New Zealand Standard Research Classification > INFORMATION AND COMPUTING SCIENCES (080000) > LIBRARY AND INFORMATION STUDIES (080700) > Information Retrieval and Web Search (080704)
Divisions: Current > QUT Faculties and Divisions > Science & Engineering Faculty
Copyright Owner: Copyright 2012 Please consult the author.
Deposited On: 29 Aug 2012 01:12
Last Modified: 19 Jul 2017 15:05

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