Year: 1996
Type: conference-paper
Abstract: Systems for text retrieval, routing, categorization and other IR tasks rely heavily on linear classifiers.We propose that two machine learning algorithms, the Widrow-Hoff and EG algorithms, be used in training linear text classifiers.In contrast to most IR methods, theoretical analysis provides performance guarantees and guidance on parameter settings for these algorithms.Experimental data is presented showing Widrow-Hoff and EG to be more effective than the widely used Rocchio algorithm on several categorization and routing tasks.
Authors: David D. Lewis, Robert E. Schapire, James P. Callan, Ron Papka
Institutions: AT&T (United States), University of Massachusetts Amherst
Language: English
Subfield: Artificial Intelligence
Field: Computer Science
Domain: Physical Sciences
Open Access status: bronze
OpenAlex ID: W2060216474