eprintid: 1545
rev_number: 8
eprint_status: archive
userid: 243
dir: disk0/00/00/15/45
datestamp: 2016-05-23 03:11:11
lastmod: 2016-05-23 03:12:00
status_changed: 2016-05-23 03:11:11
type: conference_item
metadata_visibility: show
creators_name: Pham, Thi Ngan
creators_name: Phan, Thi Thom
creators_name: Nguyen, Phuoc Thao
creators_name: Ha, Quang Thuy
creators_id: thuyhq@vnu.edu.vn
title: Hidden Topic Models for Multi-Label Review Classification: An Experimental Study
ispublished: pub
subjects: IT
divisions: fac_fit
abstract: 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.
date: 2016-03-26
date_type: published
full_text_status: public
pres_type: poster
event_title: SW4PHD: the 2016 Scientific Workshop for PhD Students
event_location: Hanoi
event_dates: 26 March 2016
event_type: workshop
refereed: FALSE
citation:   Pham, Thi Ngan and Phan, Thi Thom and Nguyen, Phuoc Thao and Ha, Quang Thuy  (2016) Hidden Topic Models for Multi-Label Review Classification: An Experimental Study.  In: SW4PHD: the 2016 Scientific Workshop for PhD Students, 26 March 2016, Hanoi.     
document_url: https://eprints.uet.vnu.edu.vn/eprints/id/eprint/1545/1/NCS%20Ph%E1%BA%A1m%20Th%E1%BB%8B%20Ng%C3%A2n%20-%20QH2012%20-%20poster.pdf