AliMe MKG: A Multi-modal Knowledge Graph for Live-streaming E-commerce

TL;DR

AliMe MKG is a multi-modal knowledge graph designed to enhance live-streaming e-commerce by providing detailed product information and an interactive assistant, improving customer understanding and engagement.

Contribution

The paper introduces AliMe MKG, a novel multi-modal knowledge graph tailored for live-streaming e-commerce, enabling better product understanding and customer interaction.

Findings

System launched on Taobao app serving hundreds of thousands daily

Enhanced customer engagement through product search and question answering

Improved product understanding via multi-modal knowledge integration

Abstract

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.