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A Noun-Predicate Bigram-Based Similarity Measure for Lexical Relations

机译:基于名词谓词双词组的词汇关系相似性度量

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摘要

The method outlined in this paper demonstrates that the information-theoretic similarity measure and noun-predicate bigrams are effective methods for creating lists of semantically-related words for lexical database work. Our experiments revealed that instead of serious syntactic analysis, bigrams and morpho-syntactic information sufficed for the feature-based similarity measure. We contend that our method would be even more appreciated if it applied to a raw newswire corpus in which unlisted words in existing dictionaries, such as recently-created words, proper nouns, and syllabic abbreviations, are prevailing.
机译:本文概述的方法表明,信息理论相似性度量和名词谓词二元组是创建用于语义数据库工作的语义相关单词列表的有效方法。我们的实验表明,基于特征相似度度量的二元语法和词法语法信息可以代替严肃的语法分析。我们认为,如果将其方法应用于原始新闻专线语料库,其中现有字典中未列出的字词(例如最近创建的字词,专有名词和音节缩写)盛行,则将受到更多的赞赏。

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