Open AccessNeutrosophic Logic-Based Document Summarization
Author(s) -
O. G. El Barbary,
Radwan Abu-Gdairi
Publication year - 2021
Publication title -
journal of mathematics
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 0.252
H-Index - 13
eISSN - 2314-4785
pISSN - 2314-4629
DOI - 10.1155/2021/9938693
Subject(s) - automatic summarization , feature (linguistics) , word (group theory) , variety (cybernetics) , sentence , computer science , information retrieval , the internet , filter (signal processing) , multi document summarization , artificial intelligence , natural language processing , world wide web , mathematics , linguistics , philosophy , geometry , computer vision
Nowadays, rich quantity of information is offered on the Net which makes it hard for the clients to detect necessary information. Programmed techniques are desirable to effectively filter and search useful data from the Net. The purpose of purported text summarization is to get satisfied content handling with information variety. The main factor of document summarization is to extract benefit feature. In this paper, we extract word feature in three group called important words. Also, we extract sentence feature depending on the extracted words. With increasing knowledge on the Internet, it turns out to be an extremely time-consuming, exhausting, and boring mission to read the whole content and papers and get the relevant information on precise topics