ISA: An Intelligent Shopping Assistant
This addresses the need for improved in-store shopping assistance for consumers, but it is incremental as it combines existing technologies into a new application.
The paper tackles the problem of enhancing shopping experiences in physical stores by developing ISA, a mobile-based intelligent assistant that uses computer vision, speech, and natural language processing to help users with product queries and recommendations, achieving good performance in its NLP engines.
Despite the growth of e-commerce, brick-and-mortar stores are still the preferred destinations for many people. In this paper, we present ISA, a mobile-based intelligent shopping assistant that is designed to improve shopping experience in physical stores. ISA assists users by leveraging advanced techniques in computer vision, speech processing, and natural language processing. An in-store user only needs to take a picture or scan the barcode of the product of interest, and then the user can talk to the assistant about the product. The assistant can also guide the user through the purchase process or recommend other similar products to the user. We take a data-driven approach in building the engines of ISA's natural language processing component, and the engines achieve good performance.