Integration of opinion into customer analysis model

Yaakub, Mohd Ridzwan, Li, Yuefeng, & Feng, Yanming (2011) Integration of opinion into customer analysis model. In Guerrero, Juan (Ed.) Proceedings of the 2011 IEEE International Conference on e-Business Engineering, IEEE Computer Society Conference Publishing Services, China, pp. 90-95.

View at publisher


Nowadays, 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. A use case study is also presented in this paper to show the advantages of using OLAP and data cubes to analyze costumers’ opinions.

Impact and interest:

2 citations in Scopus
Search Google Scholar™

Citation counts are sourced monthly from Scopus and Web of Science® citation databases.

These databases contain citations from different subsets of available publications and different time periods and thus the citation count from each is usually different. Some works are not in either database and no count is displayed. Scopus includes citations from articles published in 1996 onwards, and Web of Science® generally from 1980 onwards.

Citations counts from the Google Scholar™ indexing service can be viewed at the linked Google Scholar™ search.

ID Code: 49116
Item Type: Conference Paper
Refereed: Yes
Keywords: Opinion mining, Data cubes, OLAP, Multidimensional, Structured data, Unstructured data
DOI: 10.1109/ICEBE.2011.53
ISBN: 9780769545189
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)
Australian and New Zealand Standard Research Classification > INFORMATION AND COMPUTING SCIENCES (080000) > DISTRIBUTED COMPUTING (080500) > Web Technologies (excl. Web Search) (080505)
Divisions: Current > Schools > School of Electrical Engineering & Computer Science
Current > QUT Faculties and Divisions > Science & Engineering Faculty
Copyright Owner: Copyright 2011 IEEE
Copyright Statement:

Abstracting is permitted with credit to the source. Libraries may photocopy beyond the limits of US copyright law, for private use of patrons, those articles in this volume that carry a code at the bottom of the first page, provided that the per-copy fee indicated in the code is paid through the Copyright Clearance Centre, 222 Rosewood Drive, Danvers, MA 01923.

Other copying, reprint, or republication requests should be addressed to: IEEE Copyrights Manager, IEEE Service Centre, 445 Hoes Lane, PO Box 133, Piscataway, NJ 08855-1331.

Deposited On: 12 Mar 2012 23:43
Last Modified: 24 Oct 2013 05:10

Export: EndNote | Dublin Core | BibTeX

Repository Staff Only: item control page