文章基本信息

标题：A SYSTEMATIC LITERATURE REVIEW OF AUTOMATIC KEYWORD EXTRACTION ALGORITHMS: TEXTRANK AND RAKE
本地全文：下载
作者：MANAR YAHYA ; DERAR ELEYAN ; AMNA ELEYAN 等
期刊名称：Journal of Theoretical and Applied Information Technology
印刷版ISSN：1992-8645
电子版ISSN：1817-3195
出版年度：2021
卷号：99
期号：20
语种：English
出版社：Journal of Theoretical and Applied
摘要：There are various techniques available in text mining for text summarization which will provide the concise meaningful text from the original text document. Keywords give the summary of the text and help to understand the information described in the text document. Traditional approaches to extract useful Keywords from a text depends on human effort heavily, and because of the difficult manual extraction and consuming much time, the Automatic Keyword Extraction algorithm has been used to extract a keyword efficiently that reduces the scope for human errors and saves time. TextRank and RAKE are approaches based on unsupervised techniques to extract the keywords from the text. This research systematically identifies peer-reviewed literature that discusses to utilize TextRank and RAKE algorithms for automatic keyword extraction from texts and presents a comparison between these keyword extraction approaches. Also, this systematic review presents the latest applications which use keyword extraction approaches.
关键词：Text Summarization;Automatic Keyword Extraction;TextRank;RAKE;Unsupervised Approa