eprintid: 4491
rev_number: 2
eprint_status: archive
userid: 1
dir: disk0/00/00/44/91
datestamp: 2023-11-09 16:16:10
lastmod: 2023-11-09 16:16:10
status_changed: 2023-11-09 15:58:33
type: article
metadata_visibility: show
creators_name: Khan, K.
creators_name: Baharudin, B.
creators_name: Khan, A.
creators_name: Ullah, A.
title: Mining opinion components from unstructured reviews: A review
ispublished: pub
note: cited By 108
abstract: Opinion mining is an interesting area of research because of its applications in various fields. Collecting opinions of people about products and about social and political events and problems through the Web is becoming increasingly popular every day. The opinions of users are helpful for the public and for stakeholders when making certain decisions. Opinion mining is a way to retrieve information through search engines, Web blogs and social networks. Because of the huge number of reviews in the form of unstructured text, it is impossible to summarize the information manually. Accordingly, efficient computational methods are needed for mining and summarizing the reviews from corpuses and Web documents. This study presents a systematic literature survey regarding the computational techniques, models and algorithms for mining opinion components from unstructured reviews. © 2014 King Saud University.
date: 2014
publisher: King Saud bin Abdulaziz University
official_url: https://www.scopus.com/inward/record.uri?eid=2-s2.0-85006190166&doi=10.1016%2fj.jksuci.2014.03.009&partnerID=40&md5=6f887c67edbb1f24f5e63f9309094322
id_number: 10.1016/j.jksuci.2014.03.009
full_text_status: none
publication: Journal of King Saud University - Computer and Information Sciences
volume: 26
number: 3
pagerange: 258-275
refereed: TRUE
issn: 13191578
citation:   Khan, K. and Baharudin, B. and Khan, A. and Ullah, A.  (2014) Mining opinion components from unstructured reviews: A review.  Journal of King Saud University - Computer and Information Sciences, 26 (3).  pp. 258-275.  ISSN 13191578