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A Discourse-Informed Approach for Cost-Effective Extractive Summarization.

, and . SLSP, volume 12379 of Lecture Notes in Computer Science, page 109-121. Springer, (2020)

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Statistical language modelling for automatic story generation., , and . J. Intell. Fuzzy Syst., 34 (5): 3069-3079 (2018)HeadlineStanceChecker: Exploiting summarization to detect headline disinformation., , , , and . J. Web Semant., (2021)Exploring Summarization to Enhance Headline Stance Detection., , , , and . NLDB, volume 12801 of Lecture Notes in Computer Science, page 243-254. Springer, (2021)A Discourse-Informed Approach for Cost-Effective Extractive Summarization., and . SLSP, volume 12379 of Lecture Notes in Computer Science, page 109-121. Springer, (2020)Leveraging Machine Learning to Explain the Nature of Written Genres., , , and . IEEE Access, (2021)Tackling the Challenge of Computational Identification of Characters in Fictional Narratives., , and . ICCC, page 122-129. IEEE, (2019)The University of Alicante at MultiLing 2015: approach, results and further insights., , and . SIGDIAL Conference, page 250-259. The Association for Computer Linguistics, (2015)Exploring Flexibility in Natural Language Generation Through Discursive Analysis of New Textual Genres., and . FETLT, volume 10341 of Lecture Notes in Computer Science, page 98-109. Springer, (2016)Analysing the Integration of Semantic Web Features for Document Planning across Genres., and . WebNLG, page 67-70. Association for Computational Linguistics, (2016)A Study on Flexibility in Natural Language Generation Through a Statistical Approach to Story Generation., , and . NLDB, volume 10260 of Lecture Notes in Computer Science, page 492-498. Springer, (2017)