Abstract
In this chapter we present an overview of the work that we discussed throughout the book and point out to some open questions and possible research directions. We proposed several techniques that can improve or compliment the existing sentence extraction systems. We introduced two new corpus consisting of Legal and scientific articles that can be used for evaluating sentence compression and abstractive summarisation systems. We then proposed a attention model-based sentence extraction technique that is capable of identifying key information from the documents, without requiring any manually labelled data. We showed that such techniques that use large number of pseudo-labelled data can easily outperform the systems that use domain knowledge and manual annotations.
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Mehta, P., Majumder, P. (2019). Conclusion. In: From Extractive to Abstractive Summarization: A Journey. Springer, Singapore. https://doi.org/10.1007/978-981-13-8934-4_8
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DOI: https://doi.org/10.1007/978-981-13-8934-4_8
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