Engineering Knowledge Graph from Patent Database
This provides a scalable resource for inference and reasoning in engineering tasks, but it is incremental as it builds on existing knowledge graph extraction techniques.
The authors tackled the problem of constructing a large-scale engineering knowledge graph from patent databases by extracting facts using syntactic and lexical rules, resulting in a graph with greater size and coverage compared to previous methods.
We propose a large, scalable engineering knowledge graph, comprising sets of (entity, relationship, entity) triples that are real-world engineering facts found in the patent database. We apply a set of rules based on the syntactic and lexical properties of claims in a patent document to extract facts. We aggregate these facts within each patent document and integrate the aggregated sets of facts across the patent database to obtain the engineering knowledge graph. Such a knowledge graph is expected to support inference, reasoning, and recalling in various engineering tasks. The knowledge graph has a greater size and coverage in comparison with the previously used knowledge graphs and semantic networks in the engineering literature.