Keyphrase Extraction Using PageRank and Word Features

被引：0

作者：

Le, Huong T. ^{[1
]}

Bui, Que X. ^{[1
]}

机构：

[1] Hanoi Univ Sci & Technol, Sch Informat & Commun Technol, Hanoi, Vietnam

来源：

2021 RIVF INTERNATIONAL CONFERENCE ON COMPUTING AND COMMUNICATION TECHNOLOGIES (RIVF 2021) | 2021年

关键词：

keyphrase extraction; unsupervised learning; PageRank; word embedding; word features;

D O I：

10.1109/RIVF51545.2021.9642124

中图分类号：

TP [自动化技术、计算机技术];

学科分类号：

0812 ;

摘要：

Keyphrase extraction is a fundamental task in natural language processing. Its purpose is to generate a set of keyphrases representing the main idea of the input document. Keyphrase extraction can be used in several applications such as recommendation systems, plagiarism checking, text summarization, and text retrieval. In this paper, we propose an approach using PageRank and word features to compute keyphrases' scores. Experimental results on SemEval 2010 dataset show that our method provides promising results compared to existing works in this field.

引用

页码：257 / 261

页数：5

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