Abstract
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
Highlights
By increasing the knowledge on the Internet, it turns out to be an extremely time-consuming and boring mission to read whole content and papers and get the relevant information on precise topics
We use the distance between two Neutrosophic sets [21, 22] to create a summary with related and closely-related sentences
Works e aim of our work is to study another method of text summarization based on neutrosophic sets. e benefit of using neutrosophic sets is that they are used as a good mathematical tool for document summarization via distance between two neutrosophic sets
Summary
By increasing the knowledge on the Internet, it turns out to be an extremely time-consuming and boring mission to read whole content and papers and get the relevant information on precise topics. Content summarization is recognized as a key for this matter as it generates programmed briefing of the data. The theory of neutrosophic logic and sets has been introduced. Florentin [1, 2] presented the neutrosophic logic It is a decision in which each proposition is valued to have three grades such as a grade of truth (T), a grade of indeterminacy (I), and a grade of falsity (F). We propose neutrosophic logic centered multidocument summarization procedure to debrief vital sentences to create nonredundant summary.
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