期刊名称：International Journal of Education and Management Engineering(IJEME)
印刷版ISSN：2305-3623
电子版ISSN：2305-8463
出版年度：2018
卷号：8
期号：1
页码：11-21
DOI：10.5815/ijeme.2018.01.02
出版社：MECS Publisher
摘要：Today E-commerce websites provide customers with the needed product information by giving various kinds of services to choose from. One such service is to allow the customer to read the end user online reviews. Online reviews contain features which are useful for the analysis in opinion mining. Converting these unstructured reviews into useful information require extracting the product features from them. Natural Language Processing (NLP) based technique extracts various kinds of product features including the low frequency features. Topic Modeling based approach also identifies specific product features from the online reviews. The effective number of product features is made available to the customer when these two approaches are combined. This results in the expanded product feature set so that the customer makes wise decisions without having to compromise on the feature set.
