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Joint Knowledge-based Topic Level Attention for a Convolutional Sequence Text Summarization System using Natural Language Representation

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thesis
posted on 2022-04-14, 05:28 authored by Shirin KhanamShirin Khanam

A Thesis Submitted in Total Fulfillment of the Requirements for the Degree of Doctor of Philosophy to the Department of Computer Science and Information Technology, School of Engineering and Mathematical Science, College of Science, Health and Engineering, La Trobe University, Victoria, Australia.

History

School

  • School of Engineering and Mathematical Sciences

Center or Department

Department of Computer Science and Information Technology

Thesis type

  • Ph. D.

Awarding institution

La Trobe University

Year Awarded

2021

Rights Statement

This thesis contains third party copyright material which has been reproduced here with permission. Any further use requires permission of the copyright owner. The thesis author retains all proprietary rights (such as copyright and patent rights) over all other content of this thesis, and has granted La Trobe University permission to reproduce and communicate this version of the thesis. The author has declared that any third party copyright material contained within the thesis made available here is reproduced and communicated with permission. If you believe that any material has been made available without permission of the copyright owner please contact us with the details.

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    Keywords

    thesisdeep learningknowledge basenatural language representationtopic modelconceptabstractive text summarizationconvolutional modelattention modelNatural Language ProcessingConceptual Modelling

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