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With the rapid expansion of Web 2.0, more and more people express their views and comments about products online. To understand and satisfy customer requirements, designers need to find out helpful information from online reviews and design a new one as fast as possible. It's an important phase to identify customer requirements in product development process. However, popular products can get hundreds of reviews, designers often spend a lot of time on identifying customer needs. Therefore, to meet customer requirements and speed up product development process, this research proposes a data-driven design method which combines text mining and Kansei engineering. Text mining is dedicated to capture and analyze the key words from customer reviews. Kansei engineering aims to translate customer needs into the product development domain. According to the result of Kansei Engineering, a CAD model will be generated to visualize prototype. Moreover, a case study of bike is provided to demonstrate the practical viability of proposed method. Under the trend of data-driven design, this is the first study that integrates text mining and Kansei engineering in product development process.
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