Abstract
In this chapter, we examine some of the existing techniques for sentence extraction and sentence compression. We also discuss the existing approaches for creating ensembles of these systems. We point out specific cases where the existing techniques would not work and what needs to be done to handle such cases. We discuss various existing approaches for extractive summarisation in such a way as to maximise the representation from several different categories of extractive techniques. In contrast to the extractive techniques, ensemble techniques for summarisation are fewer, but at the same time warrant a detailed discussion in order to present our arguments. We discuss all the existing ensemble approaches, their strengths and weaknesses. For abstractive summarisation/sentence compression we classify the approaches into two major groups: those dependent on linguistic resources and the ones that are completely data-driven. We end the chapter with an overview of domain-specific summarisation approaches, specifically related to legal and scientific articles.
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Adapted/Translated by permission from Elsevier: Elsevier, Information processing and management, Vol 54/2, pages no. 145–158, Effective aggregation of various summarization techniques, Parth Mehta and Prasenjit Majumder, Copyright (2018).
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Mehta, P., Majumder, P. (2019). Related Work. In: From Extractive to Abstractive Summarization: A Journey. Springer, Singapore. https://doi.org/10.1007/978-981-13-8934-4_2
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