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A Text Summarization Hybrid Approach Using CNN and the Firefly Algorithm

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Abstract

Automatic text summarization is more significant due to the rapid expansion of textual content on the web and in many archives, such as scientific papers, news items, legal documents, etc. Text summarization manually means it will consume more effort, time, cost, and not possible with the massive volume of textual content. This work proposes a hybrid CNN and Firefly algorithm to extract relevant information from a huge amount of data. The outcome of hybrid algorithm CNN and FbTS out performs than other approaches. Thus, this paper creates the summary with non-redundant sentences and also gives flow to read the summary.

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Authors and Affiliations

  1. Department of Computer Applications, Madurai Kamaraj University, Madurai, Tamil Nadu, India

    G. Prathap & R. Rathinasabapathy

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  1. G. Prathap
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  2. R. Rathinasabapathy
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Correspondence to G. Prathap.

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This article is part of the topical collection “Industrial IoT and Cyber-Physical Systems” guest edited by Arun K Somani, Seeram Ramakrishnan, Anil Chaudhary and Mehul Mahrishi.

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Prathap, G., Rathinasabapathy, R. A Text Summarization Hybrid Approach Using CNN and the Firefly Algorithm. SN COMPUT. SCI. 5, 119 (2024). https://doi.org/10.1007/s42979-023-02421-9

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