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All Journal International Journal of Electrical and Computer Engineering
Srinivasan, Parthasarathy
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Computer Science & IT Electrical & Electronics Engineering

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A hybrid approach for text summarization using semantic latent Dirichlet allocation and sentence concept mapping with transformer Gurusamy, Bharathi Mohan; Rengarajan, Prasanna Kumar; Srinivasan, Parthasarathy
International Journal of Electrical and Computer Engineering (IJECE) Vol 13, No 6: December 2023
Publisher : Institute of Advanced Engineering and Science

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.11591/ijece.v13i6.pp6663-6672

Abstract

Automatic text summarization generates a summary that contains sentences reflecting the essential and relevant information of the original documents. Extractive summarization requires semantic understanding, while abstractive summarization requires a better intermediate text representation. This paper proposes a hybrid approach for generating text summaries that combine extractive and abstractive methods. To improve the semantic understanding of the model, we propose two novel extractive methods: semantic latent Dirichlet allocation (semantic LDA) and sentence concept mapping. We then generate an intermediate summary by applying our proposed sentence ranking algorithm over the sentence concept mapping. This intermediate summary is input to a transformer-based abstractive model fine-tuned with a multi-head attention mechanism. Our experimental results demonstrate that the proposed hybrid model generates coherent summaries using the intermediate extractive summary covering semantics. As we increase the concepts and number of words in the summary the rouge scores are improved for precision and F1 scores in our proposed model.
Co-Authors Gurusamy, Bharathi Mohan Rengarajan, Prasanna Kumar