首页> 外文会议>OOIS 2002 Workshops on Advances in Object-Oriented Information Systems, Sep 2, 2002, Montpellier, France >Guessing Hierarchies and Symbols for Word Meanings through Hyperonyms and Conceptual Vectors
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Guessing Hierarchies and Symbols for Word Meanings through Hyperonyms and Conceptual Vectors

机译:通过同义词和概念向量猜测词义的层次和符号

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摘要

The NLP team of LIRMM currently works on lexical disambiguation and thematic text analysis [Lafourcade, 2001], We built a system, with automated learning capabilities, based on conceptual vectors for meaning representation. Vectors are supposed to encode ideas associated to words or expressions. In the framework of knowledge and lexical meaning representation, we devise some conceptual vectors based strategies to automatically construct hierarchical taxonomies and validate (or invalidate) hyperonymy (or superordinate) relations among terms. Conceptual vectors are used through the thematic distance for decision making and link quality assessment.
机译:LIRMM的NLP团队目前致力于词汇歧义消除和主题文本分析[Lafourcade,2001]。我们基于用于概念表示的概念向量构建了一个具有自动学习功能的系统。向量应该被编码为与单词或表达相关的思想。在知识和词汇含义表示的框架中,我们设计了一些基于概念向量的策略来自动构建层次分类法,并验证(或无效)术语之间的同义(或上位)关系。通过主题距离使用概念向量进行决策和链接质量评估。

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