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Chinese Automatic Text Summarization Based on Keyword Extraction

机译:基于关键字提取的中国自动文本摘要

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摘要

In order to over the shortcoming of the incomprehensive of summarization, a new lexical-chain-based keywords extraction and automatic summarization algorithm from Chinese texts based on the unknown word recognition using co-occurrence of neighbor words is proposed in this paper, and an algorithm for constructing lexical chains based on Hownet knowledge database is given in the method, lexical chains are firstly constructing by calculating the semantic similarity between terms, then keywords are extracted and the importance of each sentence is calculated according to the lexical chain's intensity, the terms' entropy and position. The experimental results show that the summarization generated by the improved algorithm gets better performance than other methods both in recall and precision.
机译:为了在本文中提出了一种基于新的基于词汇链的基于词文的关键词提取和自动摘要算法,基于使用邻近单词的未知字识别,以及算法为了构建基于Hownet知识数据库的词汇链,在该方法中给出了词汇链首先通过计算术语之间的语义相似性来构造,然后提取关键字并且根据词汇链的强度计算每个句子的重要性熵和位置。实验结果表明,由改进的算法产生的总结比召回和精度都具有比其他方法更好。

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