RESOURCE-EFFICIENT GENERATION OF A KNOWLEDGE GRAPH

摘要

A technique is described for generating a knowledge graph that links names associated with a first subject matter category (C1) (such as brands) with names associated with a second subject matter category (C2) (such as products). In one implementation, the technique relies on two similarly-constituted processing pipelines, a first processing pipeline for processing the C1 names, and a second processing pipeline for processing the C2 names. Each processing pipeline includes three main stages, including a name-generation stage, a verification stage, and an augmentation stage. The generation stage uses a voting strategy to form an initial set of seed names. The verification stage removes noisy seed names. And the augmentation stage expands each verified name to include related terms. A final edge-forming stage identifies relationships between the expanded C1 names and the expanded C2 names using a voting strategy.