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dc.contributor.supervisor Chali, Yllias
dc.contributor.author Mahmud, Asif
dc.contributor.author University of Lethbridge. Faculty of Arts and Science
dc.date.accessioned 2020-01-17T16:56:36Z
dc.date.available 2020-01-17T16:56:36Z
dc.date.issued 2020
dc.identifier.uri https://hdl.handle.net/10133/5664
dc.description.abstract Query-based summarization problem is an interesting problem in the text summarization field. On the other hand, the reinforcement learning technique is popular for robotics and becoming accessible for the text summarization problem in the last couple of years (Narayan et al., 2018). The lack of significant works using reinforcement learning to solve the query-based summarization problem inspired us to use this technique. While doing so, We also introduce a different approach for sentence ranking and clustering to avoid redundancy in summaries. We propose an unsupervised extractive summarization method, which provides state-of-the-art results on some metrics. We develop two abstractive multi-document summarization models using the reinforcement learning technique and the transformer model (Vaswani et al., 2017). We consider the importance of information coverage and diversity under a fixed sentence limit for our summarization models. We have done several experiments for our proposed models, which bring significant results across different evaluation metrics. en_US
dc.language.iso en_US en_US
dc.publisher Lethbridge, Alta. : University of Lethbridge, Dept. of Mathematics and Computer Science en_US
dc.relation.ispartofseries Thesis (University of Lethbridge. Faculty of Arts and Science) en_US
dc.subject Software engineering en_US
dc.subject Systems engineering en_US
dc.subject Text data mining en_US
dc.subject Natural language processing
dc.subject Natural language generation (Computer science)
dc.title Query-based summarization using reinforcement learning and transformer model en_US
dc.type Thesis en_US
dc.publisher.faculty Arts and Science en_US
dc.publisher.department Department of Mathematics and Computer Schience en_US
dc.degree.level Masters en_US
dc.proquest.subject Computer science [0984] en_US
dc.proquest.subject Computer engineering [0464] en_US
dc.proquestyes Yes en_US


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