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From Extractive to Abstractive Summarization: A Journey (Paperback, 1st ed. 2019)
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From Extractive to Abstractive Summarization: A Journey (Paperback, 1st ed. 2019)
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This book describes recent advances in text summarization,
identifies remaining gaps and challenges, and proposes ways to
overcome them. It begins with one of the most frequently discussed
topics in text summarization - 'sentence extraction' -, examines
the effectiveness of current techniques in domain-specific text
summarization, and proposes several improvements. In turn, the book
describes the application of summarization in the legal and
scientific domains, describing two new corpora that consist of more
than 100 thousand court judgments and more than 20 thousand
scientific articles, with the corresponding manually written
summaries. The availability of these large-scale corpora opens up
the possibility of using the now popular data-driven approaches
based on deep learning. The book then highlights the effectiveness
of neural sentence extraction approaches, which perform just as
well as rule-based approaches, but without the need for any manual
annotation. As a next step, multiple techniques for creating
ensembles of sentence extractors - which deliver better and more
robust summaries - are proposed. In closing, the book presents a
neural network-based model for sentence compression. Overall the
book takes readers on a journey that begins with simple sentence
extraction and ends in abstractive summarization, while also
covering key topics like ensemble techniques and domain-specific
summarization, which have not been explored in detail prior to
this.
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