Can machines learn questions?
Analyzing information is crucial for businesses these days with many looking to reviews and feedbacks for areas of improvement. There is a need to sort the information gathered so that it can be processed easily and therefore an automatic document classifier is built. The two algorithms used to buil...
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sg-ntu-dr.10356-753092023-07-07T15:58:14Z Can machines learn questions? Soo, Alvin Andy Khong Wai Hoong School of Electrical and Electronic Engineering DRNTU::Engineering::Electrical and electronic engineering Analyzing information is crucial for businesses these days with many looking to reviews and feedbacks for areas of improvement. There is a need to sort the information gathered so that it can be processed easily and therefore an automatic document classifier is built. The two algorithms used to build the classifier are Latent Dirichlet Allocation and Extreme Learning Machine. To ensure the highest performance of the classifier, the dataset is pre-processed in different ways and tested to check its performance. Text pre-processing includes removal of common stop words, punctuation and numerical numbers. Through the different tests and experiments, the parameters that performed the best can be chosen and used to work on other datasets for further testing. Bachelor of Engineering 2018-05-30T08:35:21Z 2018-05-30T08:35:21Z 2018 Final Year Project (FYP) http://hdl.handle.net/10356/75309 en Nanyang Technological University 58 p. application/pdf |
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DRNTU::Engineering::Electrical and electronic engineering Soo, Alvin Can machines learn questions? |
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Analyzing information is crucial for businesses these days with many looking to reviews and feedbacks for areas of improvement. There is a need to sort the information gathered so that it can be processed easily and therefore an automatic document classifier is built. The two algorithms used to build the classifier are Latent Dirichlet Allocation and Extreme Learning Machine. To ensure the highest performance of the classifier, the dataset is pre-processed in different ways and tested to check its performance. Text pre-processing includes removal of common stop words, punctuation and numerical numbers. Through the different tests and experiments, the parameters that performed the best can be chosen and used to work on other datasets for further testing. |
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Andy Khong Wai Hoong |
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Andy Khong Wai Hoong Soo, Alvin |
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Final Year Project |
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Soo, Alvin |
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Soo, Alvin |
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Can machines learn questions? |
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Can machines learn questions? |
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Can machines learn questions? |
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Can machines learn questions? |
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Can machines learn questions? |
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can machines learn questions? |
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2018 |
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http://hdl.handle.net/10356/75309 |
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