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Abstractive text summarization employing ontology-based knowledge-aware multi-focus conditional generative adversarial network (OKAM-CGAN) with hybrid pre-processing methodology

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Abstract

Over the past few years, the explainable artificial intelligence (XAI) model receives a broad desire for investigation. The natural language processing (NLP) commune is reaching the fundamental change too – constructing a set of paradigms, which describe the preference on a few chief jobs devoid of influencing the execution. Abstractive Text Summarization (ATS) remains the job of building summary sentences by fusing factualities out of disparate source sentences and compressing them into a smaller portrayal when sustaining data content and comprehensive sense. This remains extremely arduous and long-drawn-out for people to physically summarize huge text documents. This study proffers Ontology-based Knowledge Aware Multi-focus Conditional Generative Adversarial Network (OKAM-CGAN) for novel documents. This could build novel sentences by analyzing many finer pieces than sentences, especially, semantic phrases. The proffered OKAM-CGAN comprises 3 prime portions – ontology aware knowledge-based document representation module, multitask and multi-focus learning unit, and an adversarial network unit. Experiential assessment is performed by correlating with advanced methodologies like RNN-W, CopyNet, GCU, Seq2Seq, and KESG concerning ROUGE scores. Consequently, it is observed that the proffered OKAM-CGAN attains 42.1% of ROUGE-L, 40% of accuracy, 45%of precision, and 53% of recall for the CNN/Daily Mail database and 45% of ROUGE-L, 4% of accuracy, 54% of precision, and 57% of recall for the Edmunds database.

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Data availability

Data sharing not applicable to this article as no datasets were generated or analyzed during the current study’.

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Authors and Affiliations

  1. Department of Computer Science and Engineering, Saveetha School of Engineering, Saveetha Institute of Medical and Technical Sciences, SaveethaUniversity, Chennai, Tamilnadu, 602105, India

    Nafees Muneera M & Sriramya P

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  1. Nafees Muneera M
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  2. Sriramya P
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Correspondence to Nafees Muneera M.

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M, N.M., P, S. Abstractive text summarization employing ontology-based knowledge-aware multi-focus conditional generative adversarial network (OKAM-CGAN) with hybrid pre-processing methodology. Multimed Tools Appl 82, 23305–23331 (2023). https://doi.org/10.1007/s11042-022-14155-6

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