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Issue title: Special Section: Collective intelligence in information systems
Guest editors: Ngoc Thanh Nguyen, Edward Szczerbicki, Bogdan Trawiński and Van Du Nguyen
Article type: Research Article
Authors: Anh, Kieu Que; * | Nagai, Yukari | Le Minh, Nguyen
Affiliations: Japan Advanced Institute of Science and Technology, Japan
Correspondence: [*] Corresponding author. Kieu Que Anh, Japan Advanced Institute of Science and Technology, Japan. E-mail: [email protected].
Abstract: With the development of social networks and online shopping sites, we can easily obtain valuable feedback from users. The crucial question is how to utilize customer feedback for supporting the development of product design in the early phases. For product design, understanding user needs or user requirements would help designers design a better product for users. Therefore, user requirements is considered as an important role in product design. This paper proposes a framework for assessing user requirements from websites to support designers. They key idea is to extract user requirements from online customer reviews and represent them into an appropriate form for designers. We show that a support system consisting of feature aspect extraction, opinion summarization, and sentiment classification would be an useful tool for product design. Experimental results on a the data collected from the Amazon website show that supporting of opinion extraction techniques would be useful for designers in product design.
Keywords: Opinion mining, product design, sentiment classification, users requirements (URs)
DOI: 10.3233/JIFS-179352
Journal: Journal of Intelligent & Fuzzy Systems, vol. 37, no. 6, pp. 7441-7451, 2019
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