词义消歧使用WSD特有的WordNet的多义词

Udaya Raj Dhungana, S. Shakya, K. Baral, Bharat Sharma
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引用次数: 27

摘要

本文提出了一种新的WordNet模型,该模型基于线索词对多义词的正确意义进行消歧。一个多义词和一个单义词所对应的词被称为线索词。传统的WordNet将名词、动词、形容词和副词组织成一组同义词,称为同义词集,每组同义词集表达一个不同的概念。与WordNet的结构相比,我们开发了一种新的WordNet模型,该模型基于线索词对多义词的不同意义和单义词进行组织。使用基于知识的词义消歧(WSD)算法,对一个多义词的每个意义以及单个意义的线索词进行消歧,从而在给定的上下文中消除该多义词的正确意义。提示词可以是名词、动词、形容词或副词。
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Word Sense Disambiguation using WSD specific WordNet of polysemy words
This paper presents a new model of WordNet that is used to disambiguate the correct sense of polysemy word based on the clue words. The related words for each sense of a polysemy word as well as single sense word are referred to as the clue words. The conventional WordNet organises nouns, verbs, adjectives and adverbs together into sets of synonyms called synsets each expressing a different concept. In contrast to the structure of WordNet, we developed a new model of WordNet that organizes the different senses of polysemy words as well as the single sense words based on the clue words. These clue words for each sense of a polysemy word as well as for single sense word are used to disambiguate the correct meaning of the polysemy word in the given context using knowledge-based Word Sense Disambiguation (WSD) algorithms. The clue word can be a noun, verb, adjective or adverb.
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