Industrial Quality Prediction System through Data Mining Algorithm
Volume-3 | Issue-2
Comparative Analysis an Early Fault Diagnosis Approaches in Rotating Machinery by Convolution Neural Network
Volume-3 | Issue-2
Nakagami-m Fading Detection with Eigen Value Spectrum Algorithms
Volume-3 | Issue-2
Abstractive Summarization System
Volume-3 | Issue-4
Design of Adaptive Estimator for Nonlinear control system in Noisy Domain
Volume-3 | Issue-3
Automated Nanopackaging using Cellulose Fibers Composition with Feasibility in SEM Environment
Volume-3 | Issue-2
Comparative Analysis of Temperature Measurement Methods based on Degree of Agreement
Volume-3 | Issue-3
Transistor Sizing using Hybrid Reinforcement Learning and Graph Convolution Neural Network Algorithm
Volume-3 | Issue-3
A Review on Meshing Techniques in Biomedicine
Volume-3 | Issue-4
EL DAPP - An Electricity Meter Tracking Decentralized Application
Volume-2 | Issue-1
SMART STREET SYSTEM WITH IOT BASED STREET LIGHT OPERATION AND PARKING APPLICATION
Volume-1 | Issue-1
ENERGY AND POWER EFFICIENT SYSTEM ON CHIP WITH NANOSHEET FET
Volume-1 | Issue-1
Abstractive Summarization System
Volume-3 | Issue-4
A Review on Meshing Techniques in Biomedicine
Volume-3 | Issue-4
MIMO BASED HIGH SPEED OPTICAL FIBER COMMUNICATION SYSTEM
Volume-1 | Issue-2
Industrial Quality Prediction System through Data Mining Algorithm
Volume-3 | Issue-2
Comparative Analysis of Temperature Measurement Methods based on Degree of Agreement
Volume-3 | Issue-3
Transistor Sizing using Hybrid Reinforcement Learning and Graph Convolution Neural Network Algorithm
Volume-3 | Issue-3
VIRTUAL REALITY SIMULATION AS THERAPY FOR POSTTRAUMATIC STRESS DISORDER (PTSD)
Volume-1 | Issue-1
Comparative Analysis an Early Fault Diagnosis Approaches in Rotating Machinery by Convolution Neural Network
Volume-3 | Issue-2
Volume - 3 | Issue - 4 | december 2021
Published
27 April, 2022
The World Wide Web has evolved into one of the world's most extensive information and knowledge repositories. Despite their ease of access, the great majority of such individual publications are extremely difficult to analyse or evaluate. Text summaries assist users in achieving such information-seeking goals by providing rapid access to the highlights or important features of a document collection. Abstractive summarization attempts to reduce a given text to its core components based on the user's preference for brevity. To summarise, there are two approaches: extraction and abstraction. Statistical techniques are used for extracting most important sentences from a corpus. Abstraction entails reformulating material based on the type of summary. This approach makes use of more adaptive language processing technology. Despite the fact that abstraction yields better summaries, extraction remains the favoured strategy and is widely employed in research. A number of approaches, including cosine, can be used to calculate the measure of resemblance between articles. Sentences' statistical & linguistic features are utilised to determine their importance. An abstractive summary is used to absorb the fundamental concepts of a material and then summarise them into plain English.
KeywordsText summarising Natural Language Processing (NLP) Extractive Summary and Abstractive Summary
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