Vietnamese text classification using NLP techniques

Please use this identifier to cite or link to this item: http://thuvienso.dut.udn.vn/handle/DUT/591

DC Field	Value	Language
dc.contributor.advisor	Nguyễn, Văn Nguyên, ThS
dc.contributor.author	Nguyễn, Nhật Tùng
dc.date.accessioned	2024-11-05T08:45:33Z	-
dc.date.available	2024-11-05T08:45:33Z	-
dc.date.issued	2022
dc.identifier.uri	http://thuvienso.dut.udn.vn/handle/DUT/591	-
dc.description	DA.TI.22.439; 59 tr	vi
dc.description.abstract	In this thesis, I have provided a solution for automated text classification of Vietnamese text using NLP techniques using 4 different machine learning models. After experimenting, it is showed that Support Vector Machine and Multilayer Perceptron models perform best and equally well with approximately 94% accuracy. Logistic Regression model performs a little worse with 92% accuracy. Multinomial Naïve Bayes performs worst of 4 models with 87% accuracy	vi
dc.language.iso	en	vi
dc.publisher	Trường Đại học Bách Khoa-Đại học Đà Nẵng	vi
dc.subject	Công nghệ phần mềm	vi
dc.subject	Text classification	vi
dc.subject	NLP techniques	vi
dc.title	Vietnamese text classification using NLP techniques	vi
dc.type	Đồ án	vi
item.cerifentitytype	Publications	-
item.languageiso639-1	en	-
item.openairetype	Đồ án	-
item.fulltext	Có toàn văn	-
item.openairecristype	http://purl.org/coar/resource_type/c_18cf	-
item.grantfulltext	restricted	-
Appears in Collections:	Khoa Công nghệ Thông tin - Công nghệ phần mềm

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