An Approach For Automatic Analysis Of Online Store Product And Services Reviews
Snezhana Sulova ()
Izvestiya, 2016, issue 4, 455-467
Abstract:
One of the advantages of e-commerce systems is that they enable customers and merchants to become acquainted with product and services reviews. Currently in the most popular online stores there are hundreds and even thousands of reviews for certain goods, which contain valuable information about the quality of t he offered assortment. This is the reason to look for ways for their computer processing. The article proposes an approach for automated analysis of customer reviews, based on natural language processing technology and application of methods of machine learning. À model for analysis and its implementation with the software product RapidMiner are proposed.
Keywords: data mining; web mining; opinion mining; sentiment analysis; Support Vector Machines; Naive Bayes; e-commerce; RapidMiner (search for similar items in EconPapers)
JEL-codes: C88 (search for similar items in EconPapers)
Date: 2016
References: Add references at CitEc
Citations: View citations in EconPapers (1) Track citations by RSS feed
Downloads: (external link)
http://journal.ue-varna.bg/uploads/20170209015130_1020793383589c73e237487.pdf
Related works:
This item may be available elsewhere in EconPapers: Search for items with the same title.
Export reference: BibTeX
RIS (EndNote, ProCite, RefMan)
HTML/Text
Persistent link: https://EconPapers.repec.org/RePEc:vrn:journl:y:2016:i:4:p:455-467
Access Statistics for this article
Izvestiya is currently edited by Zhivko Parushev
More articles in Izvestiya from Varna University of Economics Contact information at EDIRC.
Bibliographic data for series maintained by Rositsa Zarkova ().