AliMe MKG: A Multi-modal Knowledge Graph for Live-streaming E-commerce
This work addresses the need for better product information access in live-streaming e-commerce for customers, but it is incremental as it applies existing multi-modal knowledge graph techniques to a new domain.
The authors tackled the problem of helping customers understand products during live-streaming e-commerce without leaving the broadcast, by proposing AliMe MKG, a multi-modal knowledge graph that provides cognitive product profiles, and built an online assistant for search, exhibition, and question answering, which has been deployed in the Taobao app and serves hundreds of thousands of customers daily.
Live streaming is becoming an increasingly popular trend of sales in E-commerce. The core of live-streaming sales is to encourage customers to purchase in an online broadcasting room. To enable customers to better understand a product without jumping out, we propose AliMe MKG, a multi-modal knowledge graph that aims at providing a cognitive profile for products, through which customers are able to seek information about and understand a product. Based on the MKG, we build an online live assistant that highlights product search, product exhibition and question answering, allowing customers to skim over item list, view item details, and ask item-related questions. Our system has been launched online in the Taobao app, and currently serves hundreds of thousands of customers per day.