Research on Cross Language Text Keyword Extraction Based on Information Entropy and TextRank

被引：0
|
作者：
Zhang, Xiaoyu [1 ]
Wang, Yongbin [1 ]
Wu, Lin [1 ]
机构：
[1] Commun Univ China, Internet Informat Res Inst, Beijing 100024, Peoples R China
来源：
PROCEEDINGS OF 2019 IEEE 3RD INFORMATION TECHNOLOGY, NETWORKING, ELECTRONIC AND AUTOMATION CONTROL CONFERENCE (ITNEC 2019) | 2019年
关键词：
component; information entropy; TextRank; keyword extraction; Cross language keyword extraction;
D O I：
10.1109/itnec.2019.8728993
中图分类号：
TP [自动化技术、计算机技术];
学科分类号：
0812 ;
摘要：
In order to extract keywords from cross-language documents as accurately as possible, especially for the language whose keyword extraction technology is not mature, a text keyword extraction method based on information entropy and TextRank is proposed to extract the accurate keywords from the translated Chinese documents. This method determines the basic importance of words according to the information entropy of words, and then uses the information entropy of words to vote iteratively through the TextRank algorithm. This method solves the problem that TextRank algorithm easily extracts frequent non key words as keywords. The experimental results show that the proposed method can extract keywords more accurately than TextRank in the processing of cross-lingual bilingual translated documents.
引用
收藏
页码：16 / 19
页数：4
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