Combining classifiers for word sense disambiguation based on Dempster-Shafer theory and OWA operators

摘要

In this paper, we discuss a framework for weighted combination of classifiers for word sense disambiguation (WSD). This framework is essentially based on Dempster-Shafer theory of evidence [G. Shafer, A Mathematical Theory of Evidence, Princeton University Press, Princeton, 1976] and ordered weighted averaging (OWA) operators [R.R. Yager, On ordered weighted averaging aggregation operators in multicriteria decision making, IEEE Transactions on Systems, Man, and Cybernetics 18 (1988) 183-190] We first determine various kinds of features which could provide complemen-tarily linguistic information for the context, and then combine these sources of information based on Dempster's rule of combination and OWA operators for identifying the meaning of a polysemous word. We experimentally design a set of individual classifiers, each of which corresponds to a distinct representation type of context considered in the WSD literature, and then the discussed combination strategies are tested and compared on English lexical samples of Senseval-2 and Senseval-3.