AutoKnow: Self-Driving Knowledge Collection for Products of Thousands of
  Types
  Can one build a knowledge graph (KG) for all products in the world? Knowledge
graphs have firmly established themselves as valuable sources of information
for search and question answering, and it is natural to wonder if a KG can
contain information about products offered at online retail sites. There have
been several successful examples of generic KGs, but organizing information
about products poses many additional challenges, including sparsity and noise
of structured data for products, complexity of the domain with millions of
product types and thousands of attributes, heterogeneity across large number of
categories, as well as large and constantly growing number of products. We
describe AutoKnow, our automatic (self-driving) system that addresses these
challenges. The system includes a suite of novel techniques for taxonomy
construction, product property identification, knowledge extraction, anomaly
detection, and synonym discovery. AutoKnow is (a) automatic, requiring little
human intervention, (b) multi-scalable, scalable in multiple dimensions (many
domains, many products, and many attributes), and (c) integrative, exploiting
rich customer behavior logs. AutoKnow has been operational in collecting
product knowledge for over 11K product types.
