Siddharth Lakshmi, Lucienne Blessing, Kristin Wood, Jianxi Luo (2022) Engineering Knowledge Graph from Patent Database. Journal of Computing and Information Science in Engineering, 22(2): 021008. Preprint | Dataset

We propose a large, scalable engineering knowledge graph, comprising sets of real-world engineering “facts” as < entity, relationship, entity > triples that are 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 an 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.