Accurate and prompt answering framework based on customer reviews and question-answer pairs.

As e-commerce markets have gradually expanded, online shopping malls have provided various services aiming to secure competitiveness. A service for providing an accurate and prompt response when a customer writes an inquiry regarding a product represents a space directly connected to the customer and plays an important role, as it is directly related to product sales. However, the current online shopping mall answering service has disadvantages, e.g., it takes time for an administrator to write an answer directly, or to provide an answer within a set of answers. In this paper, we propose an answer framework for solving this problem, based on customer reviews. When a user writes a query, the framework provides an appropriate answer in real time through the system's question-and-answer pairs and customer reviews. The framework's performance is verified through a qualitative evaluation. In addition, it is confirmed that a customized model for reflecting the characteristics of each shopping mall can be created by using additional information from the collected data. The proposed framework is expected to support customers' online shopping through more reliable and efficient information retrieval, and to reduce shopping mall operation and maintenance costs. • We proposed an answer framework using Q&A pairs and customer reviews. • We obtained high performance in customer reviews category classification. • We provided customer reviews suitable for users' inquiries along with Q&A data. • A qualitative evaluation was conducted on the system output for any input query. • We provided a customized model framework for the Q&A system. [ABSTRACT FROM AUTHOR]