eprintid: 2750
rev_number: 9
eprint_status: archive
userid: 286
dir: disk0/00/00/27/50
datestamp: 2017-12-11 09:40:22
lastmod: 2017-12-12 07:56:18
status_changed: 2017-12-11 09:40:22
type: conference_item
metadata_visibility: show
creators_name: Ha, Quang Thuy
creators_name: Pham, Thi Ngan
creators_name: Nguyen, Van Quang
creators_name: Vuong, Thi Hong
creators_name: Tran, Minh Tuoi
creators_name: Nguyen, Thi Cham
creators_name: Nguyen, Tri Thanh
creators_id: thuyhq@vnu.edu.vn
creators_id: hongvt_57@vnu.edu.vn
creators_id: nthicham@hpmu.edu.vn
creators_id: ntthanh@vnu.edu.vn
title: A New Lifelong Topic Modeling Method and Its Application to Vietnamese Text Multi-label Classification
ispublished: pub
subjects: IT
divisions: fac_fit
abstract: Lifelong machine learning is emerging in recent years thanks to its ability to use past knowledge for current problem. Lifelong topic modeling algorithms, such as LTM and AMC, are proposed and they are very useful. However, these algorithms focus on learning bias on the topic level not the domain level. This paper proposes a lifelong topic modeling method, which focuses on learning bias on the domain level based on a proposed domain closeness measure, and an application framework for multi-label classification on Vietnamese texts. Experimental results on three previously solved Vietnamese texts, and five different current Vietnamese text datasets in combination with different topic set sizes showed that our proposed method is better than AMC method for all cases
date: 2018
date_type: published
full_text_status: none
pres_type: paper
event_title: 10th Asian Conference on Intelligent Information and Database Systems (ACIIDS)
event_dates: 2018
event_type: conference
refereed: TRUE
citation:   Ha, Quang Thuy and Pham, Thi Ngan and Nguyen, Van Quang and Vuong, Thi Hong and Tran, Minh Tuoi and Nguyen, Thi Cham and Nguyen, Tri Thanh  (2018) A New Lifelong Topic Modeling Method and Its Application to Vietnamese Text Multi-label Classification.  In: 10th Asian Conference on Intelligent Information and Database Systems (ACIIDS), 2018.