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A Semantic Lexicon-Based Approach for Sense Disambiguation and Its WWW Application

机译:基于语义词典的语义歧义消除方法及其在万维网中的应用

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This work proposes a basic framework for resolving sense disambiguation through the use of Semantic Lexicon, a machine readable dictionary managing both word senses and lexico-semantic relations. More specifically, polysemous ambiguity characterizing Web documents is discussed. The adopted Semantic Lexicon is WordNet, a lexical knowledge-base of English words widely adopted in many research studies referring to knowledge discovery. The proposed approach extends recent works on knowledge discovery by focusing on the sense disambiguation aspect. By exploiting the structure of WordNet database, lexico-semantic features are used to resolve the inherent sense ambiguity of written text with particular reference to HTML resources. The obtained results may be extended to generic hypertextual repositories as well. Experiments show that polysemy reduction can be used to hint about the meaning of specific senses in given contexts.
机译:这项工作提出了一个通过使用语义词典来解决歧义消除的基本框架,语义词典是一种同时管理词义和词汇语义关系的机器可读词典。更具体地说,讨论了表征Web文档的多义性歧义。所采用的语义词典是WordNet,它是英语单词的词汇知识库,在许多有关知识发现的研究中被广泛采用。所提出的方法通过专注于感消除歧义方面扩展了有关知识发现的最新工作。通过利用WordNet数据库的结构,词汇语义功能被用于解决书面文本固有的含糊不清的语义,尤其是对HTML资源的引用。获得的结果也可以扩展到通用超文本存储库。实验表明,多义性减少可以用来暗示特定情境在给定上下文中的含义。

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