eprintid: 1543
rev_number: 8
eprint_status: archive
userid: 243
dir: disk0/00/00/15/43
datestamp: 2016-05-23 03:13:39
lastmod: 2016-05-23 03:14:15
status_changed: 2016-05-23 03:13:39
type: conference_item
metadata_visibility: show
creators_name: Pham, Duc Hong
creators_name: Le, Anh Cuong
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
divisions: fac_fit
abstract: In recent years, opinion mining and sentiment analysis has been one of the attracting topics of knowledge mining and natural language processing. 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 and the QR decomposition technique.   In  our  experiment, we use a dataset of 594810 reviews  of 3775 hotels  collected  from the  very famous website  in tourism  tripadvisor.com with five common  aspects  including  cleanliness, location, service,  room and value. Experimental result shows that our proposed method outperforms some well known studies for the same problem.
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, Duc Hong and Le, Anh Cuong  (2016) A Least Square based Model for Rating Aspects and Identifying Important Aspects on Review Text Data.  In: SW4PHD: the 2016 Scientific Workshop for PhD Students, 26 March 2016, Hanoi.     
document_url: https://eprints.uet.vnu.edu.vn/eprints/id/eprint/1543/1/Poster-PhamDucHong-GuiLai.pdf