eprintid: 3642
rev_number: 6
eprint_status: archive
userid: 290
dir: disk0/00/00/36/42
datestamp: 2019-11-27 16:02:53
lastmod: 2019-11-27 16:02:53
status_changed: 2019-11-27 16:02:53
type: conference_item
metadata_visibility: show
creators_name: Luong, Thai Le
creators_name: Tran, Nhu Thuat
creators_name: Phan, Xuan Hieu
creators_id: thuattn@vnu.edu.vn
creators_id: hieupx@vnu.edu.vn
title: Improving Intent Extraction Using Ensemble Neural Network
ispublished: pub
subjects: IT
divisions: fac_fit
abstract: User intent extraction from social media texts is aimed at identifying user intent keyword and its related information. This topic has attracted a lot of researches since its various applications in online marketing, e-commerce and business services. One of such studies is to model this problem as a sequence labeling task and apply state-of-the-art sequential tagging models such as BiLSTM [12] and BiLSTM-CRFs [12]. In this paper, we take a further step to enhance intent extraction results based on tri-training [23] and ensemble learning [2]. Specifically, we simultaneously use three BiLSTM-CRFs models, each of them is different from others by the type of word embeddings, and apply majority voting scheme over their predicted labels when decoding final labels. Extensive experiments on data from three domains Real Estate, Tourism and Transportation show that our proposed methods enjoy a better performance compared to single model based approach.
date: 2019-09-25
date_type: published
full_text_status: none
pres_type: paper
pagerange: 58-63
event_title: The 19th International Symposium on Communications and Information Technologies (ISCIT 2019)
event_location: Ho Chi Minh City, Vietnam
event_dates: 25-27/09/2019
event_type: conference
refereed: TRUE
citation:   Luong, Thai Le and Tran, Nhu Thuat and Phan, Xuan Hieu  (2019) Improving Intent Extraction Using Ensemble Neural Network.  In: The 19th International Symposium on Communications and Information Technologies (ISCIT 2019), 25-27/09/2019, Ho Chi Minh City, Vietnam.