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Abstract / Description of output
Sentence compression holds promise for many applications ranging from summarisation to subtitle generation and subtitle generation. The task is typically performed on isolated sentences without taking the surrounding context into account, even though most applications would operate over entire documents. In this paper we present a discourse informed model which is capable of producing document compressions that are coherent and informative. Our model is inspired by theories of local coherence and formulated within the framework of Integer
Linear Programming. Experimental results show significant improvements over a state-of-the-art discourse agnostic approach.
Linear Programming. Experimental results show significant improvements over a state-of-the-art discourse agnostic approach.
Original language | English |
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Title of host publication | Proceedings of the 2007 Joint Conference on Empirical Methods in Natural Language Processing and Computational Natural Language Learning |
Publisher | Association for Computational Linguistics |
Pages | 1-11 |
Number of pages | 11 |
Publication status | Published - 2007 |
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