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Anaphora resolved abstractive text summarization (AR-ATS) system

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Abstract

Many people in this world are fond of reading, and text format is regarded as the official way of communication. This has resulted in an increased production of text data in a highly exponential way. consequently, people were looking for a way where they need not have to spend much time in reading the entire information provided by articles, books and so on. Moreover, people are compelled to read entire newspapers or desired articles in a short span of time in the middle of their busy schedules. So, people were looking for a simplified strategy of “Read less, get more content”. Summarization of books,0 articles and newspapers reduces the time taken to understand the content present in them. Abstractive text summarization involves summarizing the given text by reorganizing the whole text using syntactic and semantic text analysis. It includes the capability of synthesizing a compressed form of the original sentences or it may constitute novel sentences with the same semantic sense, which may not be present in the original source document. This system focusses on the different algorithms that have been developed to deal with the challenging problem of Anaphora Resolved Abstractive Text Summarization. It produces an abstractive summary that has mismatches between anaphors and their antecedents. The problem of the mapping of events with their source is addressed by the AR-ATS method, which resolves several types of anaphora that are present in prominent and common text document. Anaphora resolution involves mapping the anaphors with their antecedents which allows the semantic analysis more effective and thereby increases the efficiency of the summary produced by the method. Then the anaphora resolved words are semantically analyzed and create a flawless summary of the text document with complete analysis of the events and their sources. The whole system was successfully evaluated by various benchmark datasets, and it was shown that algorithms mentioned earlier are efficient for abstractive summarization of text.

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Authors and Affiliations

  1. Department of Computer Science and Engineering, College of Engineering, Anna University, Chennai, India

    N. Moratanch & S. Chitrakala

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  1. N. Moratanch
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  2. S. Chitrakala
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Moratanch, N., Chitrakala, S. Anaphora resolved abstractive text summarization (AR-ATS) system. Multimed Tools Appl 82, 4569–4597 (2023). https://doi.org/10.1007/s11042-022-13299-9

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  • DOI: https://doi.org/10.1007/s11042-022-13299-9

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