We describe a memory-based classification architecture for word sense disambiguation and our experience with its application to the SENSEVAL evaluation task ...
Abstract. We describe a memory-based classification architecture for word sense disambigua and its application to the SENSEVAL evaluation task.
Abstract. We describe a memory-based classi cation architecture for word sense disambiguation and its application to the senseval evaluation task.
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We describe a memory-based classification architecture for word sense disambiguation and its application to the SENSEVAL evaluationtask.
Is Three the Optimal Context Window for Memory-Based Word Sense Disambiguation?. In Proceedings of the Second Student Research Workshop associated with RANLP ...
We describe a memory-based classification architecture for word sense disambiguation and its application to the SENSEVAL evaluationtask.
Aug 6, 2022 · Existing WSD methods usually focus on learning the semantic interactions between a special ambiguous word and the glosses of its candidate ...
A memory based approach to word sense disambiguation in Bengali using k-NN method. Abstract: Word Sense Disambiguation (WSD) is an important and challenging ...
Abstract. We focus on the problem of efficiently retrieving knowledge from large memories given ambiguous cues. First, we analyse the word sense ...
Original language, English. Title of host publication, Proceedings of Computational Linguistics in the Netherlands CLIN '98.