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Iterative Edit-based Unsupervised Sentence Simplification

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dc.contributor.authorKumar, Dhruv
dc.date.accessioned2020-07-28T18:59:00Z
dc.date.available2020-07-28T18:59:00Z
dc.date.issued2020-07-28
dc.date.submitted2020-07-24
dc.description.abstractWe present a new iterative approach towards unsupervised edit-based sentence simplification. Our approach is guided by a scoring function to select simplified sentences generated after iteratively performing word and phrase-level edits on the complex sentence. The scoring function measures different aspects of simplification: fluency, simplicity, and preservation of meaning. As a result, unlike past approaches, our method is controllable and interpretable and does not require a parallel training set since it is unsupervised. At the same time, using the Newsela and WikiLarge datasets, we experimentally show that our solution is nearly as effective as state-of-the-art supervised approaches.en
dc.identifier.urihttp://hdl.handle.net/10012/16084
dc.language.isoenen
dc.pendingfalse
dc.publisherUniversity of Waterlooen
dc.relation.urihttps://github.com/ddhruvkr/Edit-Unsup-TSen
dc.subjectNatural Language Processingen
dc.subjectMachine Learningen
dc.subjectText Simplificationen
dc.titleIterative Edit-based Unsupervised Sentence Simplificationen
dc.typeMaster Thesisen
uws-etd.degreeMaster of Mathematicsen
uws-etd.degree.departmentDavid R. Cheriton School of Computer Scienceen
uws-etd.degree.disciplineComputer Scienceen
uws-etd.degree.grantorUniversity of Waterlooen
uws.contributor.advisorGolab, Lukasz
uws.contributor.affiliation1Faculty of Mathematicsen
uws.peerReviewStatusUnrevieweden
uws.published.cityWaterlooen
uws.published.countryCanadaen
uws.published.provinceOntarioen
uws.scholarLevelGraduateen
uws.typeOfResourceTexten

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