eprintid: 3407
rev_number: 8
eprint_status: archive
userid: 405
dir: disk0/00/00/34/07
datestamp: 2019-01-07 02:30:02
lastmod: 2019-01-07 02:30:02
status_changed: 2019-01-07 02:30:02
type: conference_item
metadata_visibility: show
creators_name: Bui, Van Tan
creators_name: Nguyen, Phuong Thai
creators_id: tanbv.it@gmail.com
creators_id: thainp@vnu.edu.vn
title: Enhancing Performance of Lexical Entailment Recognition for Vietnamese based on Exploiting Lexical Structure Features
ispublished: pub
subjects: IT
divisions: fac_fit
abstract: The lexical entailment recognition problem
aims to identify the is-a relation between words. The
problem has recently been receiving research attention
in the natural language processing field. In this study,
we propose a novel method (VLER) for this problem
on Vietnamese. For this purpose, we first exploit such
lexical structure information of words as a feature, then
combine this feature with vectors representation of words
such as a unique feature for recognizing the relation.
Moreover, we applied a number of methods based on word
embedding and supervised learning, experimental results
showed that our method achieves the best performance in
the hypernymy detection task than other methods in terms
of accuracy.
date: 2018-11-15
date_type: published
full_text_status: public
pres_type: paper
event_title: 2018 10th International Conference on Knowledge and Systems Engineering (KSE) (KSE'18)
event_location: Ho Chi Minh city, Vietnam
event_dates: 1-3 November 2018
event_type: conference
refereed: TRUE
citation:   Bui, Van Tan and Nguyen, Phuong Thai  (2018) Enhancing Performance of Lexical Entailment Recognition for Vietnamese based on Exploiting Lexical Structure Features.  In: 2018 10th International Conference on Knowledge and Systems Engineering (KSE) (KSE'18), 1-3 November 2018, Ho Chi Minh city, Vietnam.     
document_url: https://eprints.uet.vnu.edu.vn/eprints/id/eprint/3407/1/KSE%202018%20%284%29.pdf