Automatic Keyphrase Extraction using Graph-based Methods

被引：10

作者：

Mothe, Josiane ^{[1
]}

Ramiandrisoa, Faneva ^{[2
]}

Rasolomanana, Michael ^{[3
]}

机构：

[1] Univ Toulouse, EPSE, CNRS, IRIT,UMR5505, Toulouse, France

[2] Univ Toulouse, CNRS, IRIT, UMR5505, Toulouse, France

[3] Univ Antananarivo, Antananarivo, Madagascar

来源：

33RD ANNUAL ACM SYMPOSIUM ON APPLIED COMPUTING | 2018年

关键词：

Information systems; Information retrieval; Automatic keyphrase extraction; Graph-based methods; Word-embedding; Word2Vec; CENTRALITY;

D O I：

10.1145/3167132.3167392

中图分类号：

TP301 [理论、方法];

学科分类号：

081202 ;

摘要：

This paper analyses various unsupervised automatic keyphrase extraction methods based on graphs as well as the impact of word embedding. Evaluation is made on three datasets. We show that there is no differences when using word embedding and when not using it.

引用

页码：728 / 730

页数：3

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