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Knowledge Learning of Replacement Judgment Using Word-of-mouth Data
Yuko Taniguchi1, Ryo Tanaka2, Daisuke Kobayakawa3
1University of Tsukuba, 3-29-1 Ootsuka Bunkyo-ku, Tokyo, 112-0012, Japan.
Abstract:
The pandemic caused by COVID-19 has also affected the camera industry, and various events have been cancelled. In addition, the recent improvement in the performance of cameras installed in smartphones has reduced the demand for replacement cameras, as it is easy to take pictures without carrying a camera. For customers, online word-of-mouth is what they refer to when purchasing a product. This data is important not only for customers, but also for companies. In this research, we will use online word-of-mouth data and focus not only on numerical data but also on textual data and use text mining to learn knowledge about the decision to replace a camera.
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