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| Extracting Keywords Based on Removed Network Word Nodes |
An Wang,Yijun Gu( ),Kunming Li,Wenzheng Li |
| College of Information Technology and Cyber Security, People’s Public Security University of China, Beijing 102600, China |
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Abstract [Objective] This study modifies the TextRank algorithm with a method of removing word nodes, aiming to improve the results of keyword extraction from Chinese documents. [Methods] We proposed an updated RemoveRank algorithm to collect Chinese keywords and alternately carried out the sorting and removing steps. Based on the complex network structure characteristics of word graph, we used the removal queue as the sorting results for word nodes to extract keywords. [Results] We examined the proposed method on dataset with marked keywords from Southern Weekend. The new algorithm had better performance than the traditional methods. When the number of extracted keywords were 3, 5, and 7, their F values were 4%, 6%, and 5% higher than those of the TextRank. [Limitations] Our word graph did not include the weight of edges. [Conclusions] The RemoveRank method could effectively extract keywords from Chinese documents with the appropriate sliding window values.
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Received: 31 January 2019
Published: 18 December 2019
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Corresponding Authors:
Yijun Gu
E-mail: guyijun@ppsuc.edu.cn
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