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Research on Weighted Complex Network Based Keywords Extraction

机译:基于加权复杂网络的关键词提取研究

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Based on the complex network theory, this paper constructs a weighted lexical network to extract keywords from the text automatically. The current related researches mainly focus on the measures of nodes' contribution to the whole network, while this paper lays emphasis on the construction of lexical network. By introducing linguistic knowledge, we center on reasonable selection of nodes, proper description of relationships between words, enhancement of node attributes, and etc. Experiments indicate that the lexical network constructed by our approach achieves preferable effect on accuracy, recall and F-value-when selecting the top three results, the three indices increase by 6.67%, 3.96% and 4.97% on average than the classic TF-IDF method respectively.
机译:基于复杂网络理论,本文构建了一个加权词法网络来自动从文本中提取关键词。当前的相关研究主要集中在节点对整个网络的贡献的度量上,而本文着重于词汇网络的构建。通过引入语言知识,我们集中在节点的合理选择,单词之间关系的正确描述,节点属性的增强等方面。实验表明,通过我们的方法构建的词法网络在准确性,召回率和F值选择前三个结果时,三个指数分别比传统的TF-IDF方法平均增加6.67%,3.96%和4.97%。

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