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Whale-optimized LSTM networks for enhanced automatic text summarization.

Bharathi Mohan Gurusamy1, Prasanna Kumar Rangarajan1, Ali Altalbe2,3

  • 1Department of Computer Science and Engineering, Amrita School of Computing, Amrita Vishwa Vidyapeetham, Chennai, India.

Frontiers in Artificial Intelligence
|September 13, 2024
PubMed
Summary
This summary is machine-generated.

This study introduces an Optimized Auto Encoded Long Short-Term Memory Network (OAELSTM) with Whale Optimization Algorithm (WOA) for better automatic text summarization. The OAELSTM model generates more coherent and informative summaries than existing methods.

Keywords:
Auto EncodedLSTMWhale Optimization Algorithmoptimizationsummarization

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Area of Science:

  • Natural Language Processing
  • Artificial Intelligence
  • Machine Learning

Background:

  • Current automatic text summarization methods often fail to preserve contextual integrity and capture nuanced sentence relationships.
  • Existing models frequently produce generic or disjointed summaries, losing essential information.

Purpose of the Study:

  • To introduce a novel approach for automatic text summarization using an Optimized Auto Encoded Long Short-Term Memory Network (OAELSTM).
  • To enhance the OAELSTM model's performance and efficiency through the Whale Optimization Algorithm (WOA).
  • To improve the coherence, informativeness, and contextual integrity of generated summaries.

Main Methods:

  • Implementation of a deep LSTM network integrated with autoencoder mechanisms for key phrase and concept extraction.
  • Fine-tuning of OAELSTM model parameters using the Whale Optimization Algorithm (WOA).
  • Evaluation on benchmark datasets such as CNN/Daily Mail and Gigaword.

Main Results:

  • The OAELSTM model demonstrated superior performance compared to existing summarization approaches.
  • Achieved a ROUGE Score of 0.456, an accuracy rate of 84.47%, and a specificity score of 0.3244.
  • The model processed data efficiently within a time of 4,341.95 seconds.

Conclusions:

  • The OAELSTM model, enhanced by WOA, offers a significant advancement in automatic text summarization.
  • The proposed method effectively generates informative and coherent summaries while maintaining contextual integrity.
  • The model's performance metrics indicate its potential for practical application in natural language processing tasks.