eprintid: 1461
rev_number: 5
eprint_status: archive
userid: 4
dir: disk0/00/00/14/61
datestamp: 2015-12-28 02:59:23
lastmod: 2015-12-28 02:59:23
status_changed: 2015-12-28 02:59:23
type: conference_item
metadata_visibility: show
creators_name: Pham, Duc Hong
creators_name: Le, Anh Cuong
creators_name: Le, Thi Kim Chung
creators_id: cuongla@vnu.edu.vn
title: A Least Square based Model for Rating Aspects and Identifying Important Aspects on Review Text Data
ispublished: pub
subjects: IT
keywords: data mining;least squares approximations;natural language processing;text analysis;cleanliness;hotel services;knowledge mining;least square based model;location;natural language processing;opinion mining;rating product aspects;review text data;room;sentiment analysis;service;value;Algorithm design and analysis;Computer science;Dictionaries;Hidden Markov models;Mathematical model;Prediction algorithms;Training
abstract: Opinion mining and sentiment analysis has been one of the attracting topics of knowledge mining and natural language processing in recent years. The problem of rating aspects from textual reviews is an important task in this field. In this paper we propose a new method for rating product aspects as well as for identifying important aspects in general. Our proposed model is based on the least square method. The experiments are carried out on the data collected from hotel services with the aspects including the cleanliness, location, service, room, and value. We have obtained more accurate results than some well-known previous studies.
date: 2015-09
date_type: published
full_text_status: none
pres_type: paper
pagerange: 265-270
event_title: NICS: 2nd National Foundation for Science and Technology Development Conference on Information and Computer Science
event_location: Ho Chi Minh city, Vietnam
event_dates: 16-18 September 2015
event_type: conference
refereed: TRUE
citation:   Pham, Duc Hong and Le, Anh Cuong and Le, Thi Kim Chung  (2015) A Least Square based Model for Rating Aspects and Identifying Important Aspects on Review Text Data.  In: NICS: 2nd National Foundation for Science and Technology Development Conference on Information and Computer Science, 16-18 September 2015, Ho Chi Minh city, Vietnam.