Automatic document summarization
The information available online has been increasing exponentially and it is not going to slow down. The ability to extract information efficiently out from these huge data becomes crucial and necessary. As a result, document summarization as a part of Natural Language Processing (NLP), gains its at...
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| Format: | Final Year Project |
| Language: | English |
| Published: |
2019
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| Online Access: | http://hdl.handle.net/10356/77813 |
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| Institution: | Nanyang Technological University |
| Language: | English |
| Summary: | The information available online has been increasing exponentially and it is not going to slow down. The ability to extract information efficiently out from these huge data becomes crucial and necessary. As a result, document summarization as a part of Natural Language Processing (NLP), gains its attention by the machine learning community.
This project aims to explore the latest breakthrough by Google, BERT, as part of the research and how to use part of its feature and enhance our summarization system. This report will explain some of the technique behind the building of BERT and concentrates on the feature, encoding, that this project used. This report will also include the setup and the parameter and algorithm used for this project in order for continuation of this project for future reference. |
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