Integration of opinion into customer analysis model

Yaakub, M.R., Li, Y., Algarni, A., & Peng, B. (2012) Integration of opinion into customer analysis model. In Boissier, Olivier & Benatallah, Boualem (Eds.) The 2012 IEEE/WIC/ACM International Joint Conference on Web Intelligence and Intelligent Agent Technology Workshops, IEEE Computer Society Conference Publishing Services (CPS), Macau, China, pp. 164-168.

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As e-commerce is becoming more and more popular, the number of customer reviews that a product receives grows rapidly. In order to enhance customer satisfaction and their shopping experiences, it has become important to analysis customers reviews to extract opinions on the products that they buy. Thus, Opinion Mining is getting more important than before especially in doing analysis and forecasting about customers’ behavior for businesses purpose. The right decision in producing new products or services based on data about customers’ characteristics means profit for organization/company. This paper proposes a new architecture for Opinion Mining, which uses a multidimensional model to integrate customers’ characteristics and their comments about products (or services). The key step to achieve this objective is to transfer comments (opinions) to a fact table that includes several dimensions, such as, customers, products, time and locations. This research presents a comprehensive way to calculate customers’ orientation for all possible products’ attributes.

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ID Code: 58385
Item Type: Conference Paper
Refereed: Yes
Keywords: Opinion Mining, Data Cube, OLAP
ISBN: 9780769548807
Subjects: Australian and New Zealand Standard Research Classification > INFORMATION AND COMPUTING SCIENCES (080000) > ARTIFICIAL INTELLIGENCE AND IMAGE PROCESSING (080100) > Pattern Recognition and Data Mining (080109)
Divisions: Current > Schools > School of Electrical Engineering & Computer Science
Current > QUT Faculties and Divisions > Science & Engineering Faculty
Copyright Owner: Copyright 2012 IEEE, Inc.
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Deposited On: 19 Mar 2013 01:21
Last Modified: 12 May 2013 02:12

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