Combination of Unsupervised Keyphrase Extraction Algorithms

被引：4

作者：

Zhu, Zede ^{[1
]}

Li, Miao ^{[1
]}

Chen, Lei ^{[1
]}

Yang, Zhenxin ^{[1
]}

Chen, Sheng ^{[1
]}

机构：

[1] Chinese Acad Sci, Inst Intelligent Machines, Hefei, Peoples R China

来源：

2013 INTERNATIONAL CONFERENCE ON ASIAN LANGUAGE PROCESSING (IALP 2013) | 2013年

基金：

中国国家自然科学基金;

关键词：

information extraction; keyphrase extraction; unsupervised learning; combination method;

D O I：

10.1109/IALP.2013.14

中图分类号：

TP18 [人工智能理论];

学科分类号：

081104 ; 0812 ; 0835 ; 1405 ;

摘要：

Keyphrase extraction plays a significant role in many language processing tasks such as text summarization, text categorization and information retrieval. However, none study combines several approaches to improve the performance of keyphrase extraction. This paper first implements three representative unsupervised algorithms TfIdf, TextRank and ExpandRank, and then proposes a generalized framework using serial, parallel and voting methods on combining these algorithms for comprehensive analysis of keyphrase extraction. Experimental results, carried out on an evaluation dataset including 1040 abstracts from Chinese thesis, demonstrate the remarkable performance of some combination approaches.

引用

页码：33 / 36

页数：4

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