NEURAL FINE-GRAINED SENTIMENT ANALYSIS WITH UNSUPERVISED AND TRANSFER LEARNING APPROACHES
Ph.D
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Format: | Theses and Dissertations |
Language: | English |
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2020
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Online Access: | https://scholarbank.nus.edu.sg/handle/10635/166277 |
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sg-nus-scholar.10635-1662772021-02-19T09:11:19Z NEURAL FINE-GRAINED SENTIMENT ANALYSIS WITH UNSUPERVISED AND TRANSFER LEARNING APPROACHES HE RUIDAN COMPUTER SCIENCE Lee Wee Sun DANIEL DAHLMEIER Ng Hwee Tou NLP, fine-grained sentiment analysis Ph.D DOCTOR OF PHILOSOPHY (SOC) 2020-03-31T18:00:53Z 2020-03-31T18:00:53Z 2019-10-21 Thesis HE RUIDAN (2019-10-21). NEURAL FINE-GRAINED SENTIMENT ANALYSIS WITH UNSUPERVISED AND TRANSFER LEARNING APPROACHES. ScholarBank@NUS Repository. https://scholarbank.nus.edu.sg/handle/10635/166277 en |
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National University of Singapore |
building |
NUS Library |
continent |
Asia |
country |
Singapore Singapore |
content_provider |
NUS Library |
collection |
ScholarBank@NUS |
language |
English |
topic |
NLP, fine-grained sentiment analysis |
spellingShingle |
NLP, fine-grained sentiment analysis HE RUIDAN NEURAL FINE-GRAINED SENTIMENT ANALYSIS WITH UNSUPERVISED AND TRANSFER LEARNING APPROACHES |
description |
Ph.D |
author2 |
COMPUTER SCIENCE |
author_facet |
COMPUTER SCIENCE HE RUIDAN |
format |
Theses and Dissertations |
author |
HE RUIDAN |
author_sort |
HE RUIDAN |
title |
NEURAL FINE-GRAINED SENTIMENT ANALYSIS WITH UNSUPERVISED AND TRANSFER LEARNING APPROACHES |
title_short |
NEURAL FINE-GRAINED SENTIMENT ANALYSIS WITH UNSUPERVISED AND TRANSFER LEARNING APPROACHES |
title_full |
NEURAL FINE-GRAINED SENTIMENT ANALYSIS WITH UNSUPERVISED AND TRANSFER LEARNING APPROACHES |
title_fullStr |
NEURAL FINE-GRAINED SENTIMENT ANALYSIS WITH UNSUPERVISED AND TRANSFER LEARNING APPROACHES |
title_full_unstemmed |
NEURAL FINE-GRAINED SENTIMENT ANALYSIS WITH UNSUPERVISED AND TRANSFER LEARNING APPROACHES |
title_sort |
neural fine-grained sentiment analysis with unsupervised and transfer learning approaches |
publishDate |
2020 |
url |
https://scholarbank.nus.edu.sg/handle/10635/166277 |
_version_ |
1693115972243685376 |