NJM-Vis : applying and interpreting neural network joint models in natural language processing applications

UBC Theses and Dissertations

Featured Collection

UBC Theses and Dissertations

NJM-Vis : applying and interpreting neural network joint models in natural language processing applications Johnson, David

Abstract

Neural joint models have been shown to outperform non-joint models on several NLP and Vision tasks and constitute a thriving area of research in AI and ML. Although several researchers have worked on enhancing the interpretability of single-task neural models, in this thesis we present what is, to the best of our knowledge, the first interface to support the interpretation of results produced by joint models, focusing in particular on NLP settings. Our interface is intended to enhance interpretability of these models for both NLP practitioners and domain experts (e.g., linguists).

Item Metadata

Title	NJM-Vis : applying and interpreting neural network joint models in natural language processing applications
Creator	Johnson, David
Publisher	University of British Columbia
Date Issued	2019
Description	Neural joint models have been shown to outperform non-joint models on several NLP and Vision tasks and constitute a thriving area of research in AI and ML. Although several researchers have worked on enhancing the interpretability of single-task neural models, in this thesis we present what is, to the best of our knowledge, the first interface to support the interpretation of results produced by joint models, focusing in particular on NLP settings. Our interface is intended to enhance interpretability of these models for both NLP practitioners and domain experts (e.g., linguists).
Genre	Thesis/Dissertation
Type	Text
Language	eng
Date Available	2019-10-08
Provider	Vancouver : University of British Columbia Library
Rights	Attribution-NonCommercial-NoDerivatives 4.0 International
DOI	10.14288/1.0383321
URI	http://hdl.handle.net/2429/71864
Degree	Master of Science - MSc
Program	Computer Science
Affiliation	Science, Faculty of; Computer Science, Department of
Degree Grantor	University of British Columbia
Graduation Date	2019-11
Campus	UBCV
Scholarly Level	Graduate
Rights URI	http://creativecommons.org/licenses/by-nc-nd/4.0/
Aggregated Source Repository	DSpace

Open Collections

UBC Theses and Dissertations

UBC Theses and Dissertations

NJM-Vis : applying and interpreting neural network joint models in natural language processing applications Johnson, David

Abstract

Item Metadata

Item Media

Item Citations and Data

Permanent URL (DOI):

Rights