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

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