Patent Classification Using Hybrid Classifier Systems

Abstract:

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Patents are distributed through hundreds of collections, divided up by general area. A hybrid classifier system thus can be a powerful solution to difficult patent classification problems. In this study, we present a system for classifying patent documents on a hybrid approach by combining multiple text classifiers (Naïve Bayes, KNN and Rocchio). Decisions made by various text classifiers can be combined by voting and sampling mechanisms in the system. A prototype system was developed and tested in a real world task. The results have indicated that the accuracy of the hybrid approach is more stable than that of any of the three individual text classifiers.

Info:

Periodical:

Edited by:

Yanwen Wu

Pages:

458-463

DOI:

10.4028/www.scientific.net/AMR.187.458

Citation:

S. H. Liu et al., "Patent Classification Using Hybrid Classifier Systems", Advanced Materials Research, Vol. 187, pp. 458-463, 2011

Online since:

February 2011

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Price:

$35.00

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