relation: https://eprints.uet.vnu.edu.vn/eprints/id/eprint/1543/
title: A Least Square based Model for Rating Aspects and Identifying Important Aspects on Review Text Data
creator: Pham, Duc Hong
creator: Le, Anh Cuong
subject: Information Technology (IT)
description: 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
type: Conference or Workshop Item
type: NonPeerReviewed
format: application/pdf
language: en
identifier: https://eprints.uet.vnu.edu.vn/eprints/id/eprint/1543/1/Poster-PhamDucHong-GuiLai.pdf
identifier:   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.