Aspect-based sentiment analysis using SemEval and Amazon datasets
This thesis report is submitted in partial fulfilment of the requirements for the degree of Bachelor of Science in Computer Science and Engineering, 2017.
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BRAC University
2018
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| Accés en línia: | http://hdl.handle.net/10361/9542 |
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10361-95422022-01-26T10:05:00Z Aspect-based sentiment analysis using SemEval and Amazon datasets Hasib, Tamanna Rahin, Saima Ahmed Mostakim, Moin Department of Computer Science and Engineering, BRAC University Sentiment analysis SemEval Amazon dataset Dependency parsing Word vectors Opinion mining This thesis report is submitted in partial fulfilment of the requirements for the degree of Bachelor of Science in Computer Science and Engineering, 2017. Cataloged from PDF version of thesis report. Includes bibliographical references (pages 35-37). Sentiment analysis has become one of the most important tools in natural language processing, since it opens many possibilities to understand people’s opinions on different topics. Aspect-based sentiment analysis aims to take this a step further and find out, what exactly someone is talking about, and if he likes or dislikes it. Real world examples of perfect areas for this topic are the millions of available customer reviews in online shops. There have been multiple approaches to tackle this problem, using machine learning, deep learning and neural networks. However, currently the number of labelled reviews for training classifiers is very small. Therefore, we undertook multiple steps to research ways of improving ABSA performance on small datasets, by comparing recurrent and feed-forward neural networks and incorporating additional input data that was generated using different readily available NLP tools. Tamanna Hasib Saima Ahmed Rahin B. Computer Science and Engineering 2018-02-22T09:44:21Z 2018-02-22T09:44:21Z 2017 2017 Thesis ID 17141017 ID 13301117 http://hdl.handle.net/10361/9542 en BRAC University thesis reports are protected by copyright. They may be viewed from this source for any purpose, but reproduction or distribution in any format is prohibited without written permission. 37 pages application/pdf BRAC University |
| institution |
Brac University |
| collection |
Institutional Repository |
| language |
English |
| topic |
Sentiment analysis SemEval Amazon dataset Dependency parsing Word vectors Opinion mining |
| spellingShingle |
Sentiment analysis SemEval Amazon dataset Dependency parsing Word vectors Opinion mining Hasib, Tamanna Rahin, Saima Ahmed Aspect-based sentiment analysis using SemEval and Amazon datasets |
| description |
This thesis report is submitted in partial fulfilment of the requirements for the degree of Bachelor of Science in Computer Science and Engineering, 2017. |
| author2 |
Mostakim, Moin |
| author_facet |
Mostakim, Moin Hasib, Tamanna Rahin, Saima Ahmed |
| format |
Thesis |
| author |
Hasib, Tamanna Rahin, Saima Ahmed |
| author_sort |
Hasib, Tamanna |
| title |
Aspect-based sentiment analysis using SemEval and Amazon datasets |
| title_short |
Aspect-based sentiment analysis using SemEval and Amazon datasets |
| title_full |
Aspect-based sentiment analysis using SemEval and Amazon datasets |
| title_fullStr |
Aspect-based sentiment analysis using SemEval and Amazon datasets |
| title_full_unstemmed |
Aspect-based sentiment analysis using SemEval and Amazon datasets |
| title_sort |
aspect-based sentiment analysis using semeval and amazon datasets |
| publisher |
BRAC University |
| publishDate |
2018 |
| url |
http://hdl.handle.net/10361/9542 |
| work_keys_str_mv |
AT hasibtamanna aspectbasedsentimentanalysisusingsemevalandamazondatasets AT rahinsaimaahmed aspectbasedsentimentanalysisusingsemevalandamazondatasets |
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1814307181492699136 |