In the age of information, the huge amount of data that is produced every day will remain unusual for humans unless it is made available with new tools and technologies. Abstractive Text Summarization [ATS] tries to get the most essential content of a text corpus and compress it to a shorter text while keeping its meaning and maintaining its semantic and grammatical correctness. Increases in the volume of textual data available online exponentially raise new difficulties in terms of both accuracy and speed in locating relevant information. Summarization is a useful technique for making more effective use of the vast amounts of information available to us on the Internet and in other archives. Summarization of text refers to reducing the intricacy of expressions for a summary without changing their meaning. Expert manual summary is an arduous and time-consuming task. A large quantity of knowledge would be too overwhelming for anyone to obtain, read, and apply. Therefore, in this context, it is both necessary and helpful to generate summaries.
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Dr. Shruti A. Thakur is an assistant professor in computer science at G. H. Raisoni College of Engineering, Nagpur, with 12+ years of experience. She holds a Ph.D. and specializes in AI, machine learning, and NLP, with research contributions in deep learning-based text summarization and multiple Scopus-indexed publications.
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Taschenbuch. Zustand: Neu. AI-Powered Abstractive Text Summarization for Large-Scale Data Process | Shruti Thakur (u. a.) | Taschenbuch | Englisch | 2026 | LAP LAMBERT Academic Publishing | EAN 9786209993992 | Verantwortliche Person für die EU: SIA OmniScriptum Publishing, Brivibas Gatve 197, 1039 RIGA, LETTLAND, customerservice[at]vdm-vsg[dot]de | Anbieter: preigu. Bestandsnummer des Verkäufers 135461134
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