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Mining consumer reviews to generate ratings of different product attributes while producing feature-based review-summary
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Kangale, Akshay, Kumar, S. Krishna, Naeem, Mohd Arshad, Williams, M. A. (Mark A.) and Tiwari, M. K. (2015) Mining consumer reviews to generate ratings of different product attributes while producing feature-based review-summary. International Journal Of Systems Science, 47 (3). pp. 3272-3286. doi:10.1080/00207721.2015.11166 ISSN 0020-7721.
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Official URL: http://dx.doi.org/10.1080/00207721.2015.11166
Abstract
With the massive growth of the internet, product reviews increasingly serve as an important source of information for customers to make choices online. Customers depend on these reviews to understand users’ experience and manufacturers rely on this user-generated content to capture user sentiments about their product. Therefore, it is in the best interest of both customers and manufacturers to have a portal where they can read a complete comprehensive summary of these reviews in minimum time. With this in mind, we arrived at our first objective which is to generate a feature-based review-summary. Our second objective is to develop a predictive model to predict the next week’s product sales based on numerical review ratings and textual features embedded in the reviews. When it comes to product features, every user has different priorities for different features. To capture this aspect of decision making, we have designed a new mechanism to generate a numerical rating for every feature of the product individually. The data has been collected from well-known commercial website for two different products. The validation of the model is carried out using a crowd-sourcing technique.
Item Type: | Journal Article | ||||||||
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Subjects: | H Social Sciences > HA Statistics H Social Sciences > HF Commerce H Social Sciences > HG Finance Q Science > QA Mathematics |
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Divisions: | Faculty of Science, Engineering and Medicine > Engineering > WMG (Formerly the Warwick Manufacturing Group) | ||||||||
Library of Congress Subject Headings (LCSH): | Natural language processing (Computer science) , Crowd funding , Logistic regression analysis , Data mining--Mathematical models, Consumers' preferences, Consumer satisfaction | ||||||||
Journal or Publication Title: | International Journal Of Systems Science | ||||||||
Publisher: | Taylor and Francis Online | ||||||||
ISSN: | 0020-7721 | ||||||||
Official Date: | 7 December 2015 | ||||||||
Dates: |
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Volume: | 47 | ||||||||
Number: | 3 | ||||||||
Page Range: | pp. 3272-3286 | ||||||||
DOI: | 10.1080/00207721.2015.11166 | ||||||||
Status: | Peer Reviewed | ||||||||
Publication Status: | Published | ||||||||
Access rights to Published version: | Restricted or Subscription Access | ||||||||
Date of first compliant deposit: | 1 June 2016 | ||||||||
Date of first compliant Open Access: | 7 December 2016 | ||||||||
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