A Systematic Literature Review of Keyphrases Extraction Approaches
Dublin Core
Title
A Systematic Literature Review of Keyphrases Extraction Approaches
Subject
Keyphrases extraction
Systematic literature review
Text mining
Natural language processing
Description
The keyphrases of a document are the textual units that characterize its content such as the topics it addresses, its ideas, their field, etc. Thousands of books, articles and web pages are published every day. Manually extracting keyphrases is a tedious task and takes a lot of time. Automatic keyphrases extraction is an area of text mining that aims to identify the most useful and important phrases that give meaning to the content of a document. Keyphrases can be used in many Natural Language Processing (NLP) applications, such as text summarization, text clustering and text classification. This article provides a Systematic Literature Review (SLR) to investigate, analyze, and discuss existing relevant contributions and efforts that use new concepts and tools to improve keyphrase extraction. We have studied the supervised and unsupervised approaches to extracting keyphrases published in the period 2015-2022. We have also identified the steps most commonly used by the different approaches. Additionally, we looked at the criteria that should be evaluated to improve the accuracy of keyphrases extraction. Each selected approach was evaluated for its ability to extract keyphrases. Our findings highlight the importance of keyphrase extraction, and provide researchers and practitioners with information about proposed solutions and their limitations, which contributes to extract keyphrases in a powerful and meaningful way effective.
Creator
Ajallouda, Lahbib
Fagroud, Fatima Zahra
Zellou, Ahmed
Benlahmar, El habib
Source
International Journal of Interactive Mobile Technologies (iJIM); Vol. 16 No. 16 (2022); pp. 31-58
1865-7923
Publisher
International Association of Online Engineering (IAOE), Vienna, Austria
Date
2022-08-31
Rights
Copyright (c) 2022 Lahbib AJALLOUDA, Phd Student Fatima Zahra Fagroud, Dr. Ahmed Zellou, Dr. El habib Benlahmar
https://creativecommons.org/licenses/by/4.0
Relation
Format
application/pdf
Language
eng
Type
info:eu-repo/semantics/article
info:eu-repo/semantics/publishedVersion
Peer-reviewed Article
Identifier
Citation
Lahbib Ajallouda et al., A Systematic Literature Review of Keyphrases Extraction Approaches, International Association of Online Engineering (IAOE), Vienna, Austria, 2022, accessed November 6, 2024, https://igi.indrastra.com/items/show/2364