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

@article{citeulike:2786162, abstract = {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 complementarily 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.}, author = {Le, Cuong A. and Huynh, Van-Nam and Shimazu, Akira and Nakamori, Yoshiteru }, citeulike-article-id = {2786162}, doi = {10.1016/j.datak.2007.03.013}, journal = {Data \& Knowledge Engineering}, keywords = {computational-lexical-semantics, distributional-similarity}, month = {November}, number = {2}, pages = {381--396}, posted-at = {2008-05-12 03:03:33}, priority = {5}, title = {Combining classifiers for word sense disambiguation based on Dempster-Shafer theory and OWA operators}, url = {http://dx.doi.org/10.1016/j.datak.2007.03.013}, volume = {63}, year = {2007} }

TY - JOUR ID - citeulike:2786162 L3 - citeulike-article-id:2786162 TI - Combining classifiers for word sense disambiguation based on Dempster-Shafer theory and OWA operators JF - Data & Knowledge Engineering VL - 63 IS - 2 SP - 381 EP - 396 N2 - 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 complementarily 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. KW - computational-lexical-semantics KW - distributional-similarity AU - Le, Cuong AU - Huynh, Van-Nam AU - Shimazu, Akira AU - Nakamori, Yoshiteru PY - 2007/11// UR - http://dx.doi.org/10.1016/j.datak.2007.03.013 ER -