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Thesis Proposal Announcement: A comparative study of document representation methods

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  • Fri, 01/18/2019 - 2:30pm - 4:30pm




A comparative study of document representation methods

 

MSc Thesis Proposal by:

Ziyang Tian
Date:  Friday, January 18th, 2018
Time:  2:30 pm – 4:30 pm
Location: 3105, Lambton Tower
 
Abstract: 
Representation learning is crucial for downstream machine learning tasks such as classification. This thesis conducts a comparative study of document representation methods, in particular the comparison between traditional TF-IDF based-methods, dimensionality reduction methods based on matrix factorization, and more recent neural network based methods. The methods will be evaluated extensively on text data from different areas with different document length. We also propose a new representation method that improves the TF/IDF method.
 

Thesis Committee:

Internal Reader: Dr. Alioune Ngom

External Reader: Dr. Behnam Shahrrava

Advisor: Dr. Jianguo Lu

 



Christine Weisener
cweisen@uwindsor.ca
(519)253-3000 ext.3716