Single Document Extractive Text Summarization Using Neural Networks and Genetic Algorithm

2018 ◽  
pp. 338-358 ◽  
Author(s):  
Niladri Chatterjee ◽  
Gautam Jain ◽  
Gurkirat Singh Bajwa
Keyword(s):  
Genetic Algorithm ◽  
Neural Networks ◽  
Text Summarization

Unsupervised neural networks for automatic Arabic text summarization using document clustering and topic modeling

2021 ◽  
Vol 172 ◽  
pp. 114652
Author(s):  
Nabil Alami ◽  
Mohammed Meknassi ◽  
Noureddine En-nahnahi ◽  
Yassine El Adlouni ◽  
Ouafae Ammor
Keyword(s):  
Neural Networks ◽  
Topic Modeling ◽  
Document Clustering ◽  
Text Summarization ◽  
Arabic Text ◽  
Arabic Text Summarization ◽  
Unsupervised Neural Networks

scholarly journals Nonlinear Time-Series Analysis of Pulsation of Post-AGB Stars by Genetic Algorithm/Neural Network Hybrid Systems

2000 ◽  
Vol 176 ◽  
pp. 135-136
Author(s):  
Toshiki Aikawa
Keyword(s):  
Neural Network ◽  
Genetic Algorithm ◽  
Neural Networks ◽  
Time Series ◽  
Artificial Neural Networks ◽  
Hybrid System ◽  
Nonlinear Time Series ◽  
Photometric Data ◽  
Nonlinear Time Series Analysis ◽  
Agb Stars

AbstractSome pulsating post-AGB stars have been observed with an Automatic Photometry Telescope (APT) and a considerable amount of precise photometric data has been accumulated for these stars. The datasets, however, are still sparse, and this is a problem for applying nonlinear time series: for instance, modeling of attractors by the artificial neural networks (NN) to the datasets. We propose the optimization of data interpolations with the genetic algorithm (GA) and the hybrid system combined with NN. We apply this system to the Mackey–Glass equation, and attempt an analysis of the photometric data of post-AGB variables.

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