International Business Machines Corporation
INFER TEXT CLASSIFIERS FOR LARGE TEXT COLLECTIONS

Abstract:

An approach is provided in which the approach calculates at least one weighting factor based on a word frequency analysis of an unlabeled document against a set of word frequencies corresponding to a set of labeled documents. The approach computes an a posteriori classification probability of the unlabeled document based on the at least one weighting factor, and creates an inferred classifier based on the a posteriori classification probability. The approach classifies the unlabeled classifier using the inferred classifier.