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Constructing Tunable Sentence Simplification Models using Deep Learning

Zhao, Sanqiang (2021) Constructing Tunable Sentence Simplification Models using Deep Learning. Doctoral Dissertation, University of Pittsburgh. (Unpublished)

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Abstract

Sentence simplification aims to reduce the complexity of a sentence while retaining its original meaning so that certain individuals can read and understand it. Substitution, Dropping, Reordering, and Splitting are widely accepted as four important operations. Recent approaches view the simplification process as a monolingual text-to-text translation, where the translation model learns the operations automatically from examples of complex-simplified sentence pairs extracted from online resources. In the current literature, the two publicly available resources commonly used are Wikipedia and Newsela. However, both resources are limited in several ways, and only contribute to certain operations.

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Details

Item Type: University of Pittsburgh ETD
Status: Unpublished
Creators/Authors:
CreatorsEmailPitt UsernameORCID
Zhao, Sanqiangsaz31@pitt.edusaz310000-0002-6910-7637
Contributors:
ContributionContributors NameEmailPitt UsernameORCID
AuthorZhao, Sanqiangsaz31@pitt.edusaz310000-0002-6910-7637
Committee ChairHe, Daqingdah44@pitt.edudah44UNSPECIFIED
Committee MemberXu, Weiweixu@cse.ohio-state.eduUNSPECIFIEDUNSPECIFIED
Committee MemberMunro, Paulpwm@pitt.eduUNSPECIFIEDUNSPECIFIED
Committee MemberPelechrinis, Konstantinoskpele@pitt.eduUNSPECIFIEDUNSPECIFIED
ETD Committee:
TitleMemberEmail AddressPitt UsernameORCID
Committee ChairHe, Daqingdah44@pitt.edu
Committee MemberXu, Weiwei.xu@cc.gatech.edu
Committee MemberMunro, Paulpwm@pitt.edu
Committee MemberPelechrinis, Konstantinoskpele@pitt.edu
Date: 15 April 2021
Date Type: Publication
Defense Date: 23 March 2021
Approval Date: 7 June 2021
Submission Date: 26 April 2021
Access Restriction: No restriction; Release the ETD for access worldwide immediately.
Number of Pages: 144
Institution: University of Pittsburgh
Schools and Programs: School of Computing and Information > Information Science
Degree: PhD - Doctor of Philosophy
Thesis Type: Doctoral Dissertation
Refereed: No
Uncontrolled Keywords: sentence simplification, controllable generation
Date Deposited: 07 Jun 2021 20:49
Last Modified: 07 Jun 2021 20:49
URI: http://d-scholarship.pitt.edu/id/eprint/40638

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