Feature Extraction from Product Reviews using Feature Similarity and Polarity

Files in This Item:
 File SizeFormat
Downloaducd-csi-2009-09.pdf625.3 kBAdobe PDF
Title: Feature Extraction from Product Reviews using Feature Similarity and Polarity
Authors: Lopez Fernandez, AlejandraVeale, TonyMajumder, Prasenjit
Permanent link: http://hdl.handle.net/10197/12383
Date: Oct-2009
Online since: 2021-08-09T11:13:34Z
Abstract: Research on developing techniques to access user generated content, and specifically user reviews on different products, came in the focus of the information research community in recent past. In particular, this paper addresses the problem of extracting the features from user comments of a particular product, taking advantage of a corpus with a semistructured format: pros, cons and summary. In this paper we propose a technique to extract a set of features based on user generated pros and cons for a particular product. Then using this set we test a feature similarity function to obtain new features from reviews (both from the pros/cons and from the free text summary) of the same and other products. Our experimental results have shown interesting conclusions.
Type of material: Technical Report
Publisher: University College Dublin. School of Computer Science and Informatics
Series/Report no.: UCD CSI Technical Reports; ucd-csi-2009-09
Copyright (published version): 2009 the Authors
Keywords: Feature extractionOpinion miningFeature similarity function
Other versions: https://web.archive.org/web/20080226040105/http:/csiweb.ucd.ie/Research/TechnicalReports.html
Language: en
Status of Item: Not peer reviewed
This item is made available under a Creative Commons License: https://creativecommons.org/licenses/by-nc-nd/3.0/ie/
Appears in Collections:Computer Science and Informatics Technical Reports

Show full item record

Page view(s)

54
Last Week
2
Last month
checked on Sep 27, 2021

Download(s)

12
checked on Sep 27, 2021

Google ScholarTM

Check


If you are a publisher or author and have copyright concerns for any item, please email research.repository@ucd.ie and the item will be withdrawn immediately. The author or person responsible for depositing the article will be contacted within one business day.