mlsanityData to 7 Oct 2026

Engineering Knowledge Graph from Patent Database

arXiv 2106.06739 ↗First posted 12 Jun 2021cs.IR cs.AI cs.CLcited by 18

Not on the map. Why?

Abstract (arXiv)

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.

Key facts. Cited by 18 papers in the map (data through 7 Oct 2026). Builds on 7 of its 76 references that are in the map. First posted on arXiv 12 Jun 2021.

Builds on

7 of 76 references.

References · 7

  1. 2013Efficient Estimation of Word Representations in Vector Spacecited by 4,346
  2. 2016ConceptNet 5.5: An Open Multilingual Graph of General Knowledgecited by 1,065
  3. 2019Estimating Node Importance in Knowledge Graphs Using Graph Neural Networkscited by 43
  4. 2021Data-Driven Design-by-Analogy: State of the Art and Future Directionscited by 18
  5. 2019TechNet: Technology Semantic Network Based on Patent Datacited by 14
  6. 2020Semantic Networks for Engineering Design: A Surveycited by 6
  7. 2020Design Knowledge Representation with Technology Semantic Networkcited by 5

Built on by

Cited by year (2026 to 7 Oct)

Citing papers per year: 2021: 3; 2022: 3; 2023: 5; 2024: 5; 2025: 1; 2026: 1.

18 papers.

Sort:

By area:

  1. 2022Generative Transformers for Design Concept Generationcited by 21
  2. 2024Natural Language Processing in the Patent Domain: A Surveycited by 20
  3. 2021Natural Language Processing in-and-for Design Researchcited by 15
  4. 2022Biologically Inspired Design Concept Generation Using Generative Pre-Trained Transformerscited by 13
  5. 2021Deep Learning for Technical Document Classificationcited by 11
  6. 2023Toward Artificial Empathy for Human-Centered Design: A Frameworkcited by 6
  7. 2023Opportunities for Large Language Models and Discourse in Engineering Designcited by 6
  8. 2021Patent Data for Engineering Design: A Critical Review and Future Directionscited by 5
  9. 2023Retrieval Augmented Generation using Engineering Design Knowledgecited by 5
  10. 2022Material Prediction for Design Automation Using Graph Representation Learningcited by 3
  11. 2023The Innovation Paradox: Concept Space Expansion with Diminishing Originality and the Promise of Creative AIcited by 2
  12. 2024Building A Knowledge Graph to Enrich ChatGPT Responses in Manufacturing Service Discoverycited by 2
6 more
  1. 2024Beyond Scaling: Predicting Patent Approval with Domain-specific Fine-grained Claim Dependency Graphcited by 2
  2. 2024A Few-Shot Approach for Relation Extraction Domain Adaptation using Large Language Modelscited by 1
  3. 2023Linguistic and Structural Basis of Engineering Design Knowledgecited by 0
  4. 2024Tripl`etoile: Extraction of Knowledge from Microblogging Textcited by 0
  5. 2025A Hybrid Ai Framework For Strategic Patent Portfolio Pruning: Integrating Learning To-Rank And Market Need Analysis For Technology Transfer Optimizationcited by 0
  6. 2026From Regulatory Approvals to Patents: Cross-Domain Linking for Cardiovascular Device Traceabilitycited by 0