TY  - CONF
ID  - SisLab1545
UR  - https://eprints.uet.vnu.edu.vn/eprints/id/eprint/1545/
A1  - Pham, Thi Ngan
A1  - Phan, Thi Thom
A1  - Nguyen, Phuoc Thao
A1  - Ha, Quang Thuy
Y1  - 2016/03/26/
N2  - In recent years, Multi-Label Classification (MLC) has become an important task in the field of Supervised Learning. The MLC tasks are omnipresent in real-world problems in which an instance could belong to different classes simultaneously. In this paper, we presented a method for MLC using the hidden topic method to enrich the data features and using mutual information for feature selection. Our experiments on classifying user reviews about one thousand Vietnamese hotels showed the efficacy of the proposed approach.
TI  - Hidden Topic Models for Multi-Label Review Classification: An Experimental Study
M2  - Hanoi
AV  - public
T2  - SW4PHD: the 2016 Scientific Workshop for PhD Students
ER  -