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Information Retrieval Based on Word Semantic Clustering

机译:基于词语义聚类的信息检索

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摘要

Information retrieval is an important topic in the modern age. With the advance of Internet, it is more and more easy to retrieve other people's writings or publications. However, how to retrieve desirable information efficiently is a challenging work. Traditional methods like vector space model or bag-of-words are short of providing a good solution due to the incapability of handling the semantics of words satisfactorily. In this paper, we propose a new method for information retrieval. We use Word2vec to transform the words into word vectors which are able to represent the semantic relationship among different words. By considering the semantic of words and clustering the word vectors into concepts, information retrieval can be done effectively.
机译:信息检索是现代的重要课题。随着Internet的发展,检索他人的著作或出版物变得越来越容易。但是,如何有效地检索所需的信息是一项具有挑战性的工作。由于无法令人满意地处理单词的语义,传统的方法(例如向量空间模型或单词袋)无法提供良好的解决方案。在本文中,我们提出了一种新的信息检索方法。我们使用Word2vec将单词转换为能够代表不同单词之间语义关系的单词向量。通过考虑单词的语义并将单词向量聚类为概念,可以有效地进行信息检索。

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