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Title:
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KNOWLEDGE DISCOVERY FROM ONLINE CUSTOMER REVIEWS TOWARDS PRODUCT IMPROVEMENT |
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Author(s):
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Esmaeil Nikumanesh, Mahdi Bohlouli, Madjid Fathi |
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ISBN:
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978-989-8533-56-2 |
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Editors:
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Hans Weghorn |
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Year:
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2016 |
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Edition:
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Single |
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Keywords:
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Business Analytics, Online Customer Review, Knowledge Discovery, Sentiment Analysis, Social Media Analysis, Product Improvement |
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Type:
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Short Paper |
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First Page:
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211 |
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Last Page:
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214 |
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Language:
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English |
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Cover:
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Full Contents:
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click to dowload 
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Paper Abstract:
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Online customer reviews provide further product use information which could result in improving the quality of products next generation. Such reviews frequently cover pros and cons of using as well as potential errors of products/services from customers perspective, providing a rich data source for companies to analyze customers wishes and opinion, which could result in the customer friendly market analysis and production. In this research, we propose a model for mining online product reviews with the aim of product quality improvement. As a short paper, the conception, modeling and scientific background of proposed approach is covered in this publication. |
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