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An Unsupervised Approach to Word Sense Disambiguation Based on Hownet

机译：基于知网的无监督词义消歧方法

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摘要

Word Sense Disambigutaion is still considered one of the most challenging problemes in natural language processing .Ever since the field's inception ,WSD has been perceived as one of the central problems in NLP. This paper presents an unsupervised approach which is used as dictionary based on hownet and cilin,constructing context vector by means of secondorder context,clustering by k-means and disambiguates by calculating the similarity. Our experiments are based on the extraction of term and average accuracy is 85.13% and 84.67% for several ambiguous words in open test by this method.
机译：词义歧义仍然被认为是自然语言处理中最具挑战性的问题之一。自从该领域成立以来，WSD被认为是NLP的核心问题之一。本文提出了一种无监督的方法，该方法被用作基于hownet和cilin的字典，通过二阶上下文构造上下文向量，通过k均值进行聚类，并通过计算相似度来消除歧义。我们的实验是基于术语的提取，通过这种方法在公开测试中几个歧义词的平均准确度分别为85.13％和84.67％。

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