Context-aware customer needs Identification by linguistic pattern mining based on online product reviews

In the age of digital economy, customers actively share their experiences and issues about products via online product reviews. Mining potential improvement ideas from customer needs could provide valuable insights into new functionality expected by markets. Numerous studies have attempted to identify using these reviews, but they paid less attention customer’s specific context in which was used. This study provides a novel approach for identifying based on both information functions target products. The are derived reviews through linguistic pattern mining, whereby determined combination extracted semantic embedding method clustering approach. A case Amazon-Echo series conducted verify applicability proposed Consequently, we identified 1430 different needs, be used as an input improving design. is one first attempts integrate needs. can useful idea creation process future planning add empirical perspective e-commerce industry.