Abubakar Bichi, Abdulkadir and Samsudin, Ruhaidah and Hassan, Rohayanti and Almekhlafi, Khalil (2021) A review of graph-based extractive text summarization models. Lecture Notes on Data Engineering and Communications Technologies, 72 (NA). pp. 439-448. ISSN 2367-4512
Full text not available from this repository.
Official URL: http://dx.doi.org/10.1007/978-3-030-70713-2_41
Abstract
The amount of text data is continuously increasing both at online and offline storage, that makes is difficult for people to read across and find the desired information within a possible available time. This necessitate the use of technique such as automatic text summarization. A text summary is the briefer form of the original text, in which the principal document message is preserved. Many approaches and algorithms have been proposed for automatic text summarization including, supervised machine learning, clustering, graph-based and lexical chain, among others. This paper presents a review of various graph-based automatic text summarization models.
Item Type: | Article |
---|---|
Uncontrolled Keywords: | Graph approaches, Natural languages processing, Text mining |
Subjects: | Q Science > QA Mathematics > QA75 Electronic computers. Computer science |
Divisions: | Computing |
ID Code: | 100257 |
Deposited By: | Widya Wahid |
Deposited On: | 29 Mar 2023 07:06 |
Last Modified: | 29 Mar 2023 07:06 |
Repository Staff Only: item control page