Abstract
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.
Issue Section:
Research Papers
References
1.
Singhal
, A.
, 2012
, Introducing the Knowledge Graph: Things, not Strings, https://blog.google/products/search/introducing-knowledge-graph-things-not/, Accessed March 1, 2021.2.
Paulheim
, H.
, 2017
, “Knowledge Graph Refinement: A Survey of Approaches and Evaluation Methods
,” Semant. Web
, 8
(3
), pp. 489
–508
. 3.
Ehrlinger
, L.
, and Wöß
, W.
, 2016
, “Towards a Definition of Knowledge Graphs
,” Semantics (Posters, Demos, SuCCESS)
, 48
(1
), pp. 1
–4
.4.
Chen
, X.
, Jia
, S.
, and Xiang
, Y.
, 2020
, “A Review: Knowledge Reasoning Over Knowledge Graph
,” Expert Syst. Appl.
, 141
(1
), p. 112948
. 5.
Siddharth
, L.
, and Sarkar
, P.
, 2018
, “A Multiple-Domain Matrix Support to Capture Rationale for Engineering Design Changes
,” ASME J. Comput. Inf. Sci. Eng.
, 18
(2
), p. 021014
. 6.
Siddharth
, L.
, and Sarkar
, P.
, 2017
, “A Methodology for Predicting the Effect of Engineering Design Changes
,” Procedia CIRP
, 60
(1
), pp. 452
–457
. 7.
Aurisicchio
, M.
, Bracewell
, R.
, and Hooey
, B. L.
, 2016
, “Rationale Mapping and Functional Modelling Enhanced Root Cause Analysis
,” Saf. Sci.
, 85
(1
), pp. 241
–257
. 8.
Siddharth
, L.
, Chakrabarti
, A.
, and Ranganath
, R.
, 2019
, “Modeling and Structuring Design Rationale to Enable Knowledge Reuse
,” Syst. Eng.
, 23
(3
), pp. 294
–311
. 9.
Siddharth
, L.
, and Chakrabarti
, A.
, 2018
, “Evaluating the Impact of Idea-Inspire 4.0 on Analogical Transfer of Concepts
,” Artif. Intell. Eng. Des. Anal. Manuf.
, 32
(4
), pp. 431
–448
. 10.
Browning
, T. R.
, 2001
, “Applying the Design Structure Matrix to System Decomposition and Integration Problems: A Review and New Directions
,” IEEE Trans. Eng. Manage.
, 48
(3
), pp. 292
–306
. 11.
Siddharth
, L.
, Chakrabarti
, A.
, and Venkataraman
, S.
, 2018
, “Representing Complex Analogues Using a Function Model to Support Conceptual Design
,” Volume 1B: 38th Computers and Information in Engineering Conference
, Quebec City, Canada
, Aug. 26–29
, p. V01BT02A039, No. 51739.12.
Chakrabarti
, A.
, Siddharth
, L.
, Dinakar
, M.
, Panda
, M.
, Palegar
, N.
, and Keshwani
, S.
, 2017
, “Idea-Inspire 3.0 – A Tool for Analogical Design
,” International Conference on Research into Design (ICoRD'17)
, Guwahati, India
, Jan. 9–11
, Vol. 2, pp. 475
–485
.13.
Siddharth
, L.
, Madhusudanan
, N.
, and Chakrabarti
, A.
, 2019
, “Toward Automatically Assessing the Novelty of Engineering Design Solutions
,” ASME J. Comput. Inf. Sci. Eng.
, 20
(1
), p. 011001
. 14.
Han
, J.
, Shi
, F.
, Chen
, L.
, and Childs
, P. R. N.
, 2018
, “The Combinator—A Computer-Based Tool for Creative Idea Generation Based on a Simulation Approach
,” Des. Sci.
, 4
(1
), p. e11
. 15.
Chen
, T.-J.
, and Krishnamurthy
, V. R.
, 2020
, “Investigating a Mixed-Initiative Workflow for Digital Mind-Mapping
,” ASME J. Mech. Des.
, 142
(10
), p. 101404
. 16.
Camburn
, B.
, He
, Y.
, Raviselvam
, S.
, Luo
, J.
, and Wood
, K.
, 2020
, “Machine Learning-Based Design Concept Evaluation
,” ASME J. Mech. Des.
, 142
(3
), p. 031113
. 17.
Noh
, H.
, Jo
, Y.
, and Lee
, S.
, 2015
, “Keyword Selection and Processing Strategy for Applying Text Mining to Patent Analysis
,” Expert Syst. Appl.
, 42
(9
), pp. 4348
–4360
. 18.
Luo
, J.
, Sarica
, S.
, and Wood
, K. L.
, 2021
, “Guiding Data-Driven Design Ideation by Knowledge Distance
,” Knowl.-Based Syst.
, 218
(1
), pp. 106873
. 19.
Soo
, V.-W.
, Lin
, S.-Y.
, Yang
, S.-Y.
, Lin
, S.-N.
, and Cheng
, S.-L.
, 2006
, “A Cooperative Multi-Agent Platform for Invention Based on Patent Document Analysis and Ontology
,” Expert Syst. Appl.
, 31
(4
), pp. 766
–775
. 20.
Korobkin
, D.
, Fomenkov
, S.
, Kravets
, A.
, Kolesnikov
, S.
, and Dykov
, M.
, 2015
, “Three-Steps Methodology for Patents Prior-Art Retrieval and Structured Physical Knowledge Extracting
,” Commun. Comput. Inf.
, 535
(1
), pp. 124
–136
. 21.
Chen
, P.
, Lu
, Y.
, Zheng
, V. W.
, Chen
, X.
, and Yang
, B.
, 2018
, “KnowEdu: A System to Construct Knowledge Graph for Education
,” IEEE Access
, 6
(1
), pp. 31553
–31563
. 22.
Bordes
, A.
, Usunier
, N.
, Garcia-Duran
, A.
, Weston
, J.
, and Yakhnenko
, O.
, 2013
, “Translating Embeddings for Modeling Multi-Relational Data,” Advances in Neural Information Processing Systems 26
, C. J. C.
Burges
, L.
Bottou
, M.
Welling
, Z.
Ghahramani
, and K. Q.
Weinberger
, eds., Curran Associates, Inc.
, pp. 2787
–2795
. http://papers.nips.cc/paper/5071-translating-embeddings-for-modeling-multi-relational-data.pdf23.
Park
, N.
, Kan
, A.
, Dong
, X. L.
, Zhao
, T.
, and Faloutsos
, C.
, 2019
, “Estimating Node Importance in Knowledge Graphs Using Graph Neural Networks
,” Proceedings of the 25th ACM SIGKDD International Conference on Knowledge Discovery & Data Mining
, New York
, Aug. 4–8
, pp. 596
–606
.24.
Lehmann
, J.
, Isele
, R.
, Jakob
, M.
, Jentzsch
, A.
, Kontokostas
, D.
, Mendes
, P. N.
, Hellmann
, S.
, Morsey
, M.
, van Kleef
, P.
, Auer
, S.
, and Bizer
, C.
, 2015
, “DBpedia—A Large-Scale, Multilingual Knowledge Base Extracted From Wikipedia
,” Semant. Web
, 6
(2
), pp. 167
–195
. 25.
Speer
, R.
, Chin
, J.
, and Havasi
, C.
, 2017
, “ConceptNet 5.5: An Open Multilingual Graph of General Knowledge
,” AAAI, Vol. 31, No. 1, https://ojs.aaai.org/index.php/AAAI/article/view/11164, Accessed February 23, 2021.26.
Jiang
, J. J.
, and Conrath
, D. W.
, 1997
, “Semantic Similarity Based on Corpus Statistics and Lexical Taxonomy
,” arXiv preprint cmp-lg/9709008.27.
Chiu
, I.
, and Shu
, L.
, 2007
, “Biomimetic Design Through Natural Language Analysis to Facilitate Cross-Domain Information Retrieval
,” Artif Intell Eng Des Anal Manuf AI EDAM
, 21
(1
), pp. 45
–59
. 28.
Linsey
, J.
, Markman
, A.
, and Wood
, K.
, 2012
, “Design by Analogy: A Study of the WordTree Method for Problem Re-Representation
,” ASME J. Mech. Des.
, 134
(4
), p. 041009
. 29.
Kan
, J. W. T.
, and Gero
, J. S.
, Feb. 2018
, “Characterizing Innovative Processes in Design Spaces Through Measuring the Information Entropy of Empirical Data From Protocol Studies
,” Artif. Intell. Eng. Des. Anal. Manuf.
, 32
(1
), pp. 32
–43
. 30.
Georgiev
, G. V.
, and Georgiev
, D. D.
, 2018
, “Enhancing User Creativity: Semantic Measures for Idea Generation
,” Knowl.-Based Syst.
, 151
(1
), pp. 1
–15
. 31.
He
, Y.
, Camburn
, B.
, Liu
, H.
, Luo
, J.
, Yang
, M.
, and Wood
, K. L.
, 2019
, “Mining and Representing the Concept Space of Existing Ideas for Directed Ideation
,” ASME J. Mech. Des.
, 141
(12
), p. 121101
. 32.
Goucher-Lambert
, K.
, and Cagan
, J.
, 2019
, “Crowdsourcing Inspiration: Using Crowd Generated Inspirational Stimuli to Support Designer Ideation
,” Des. Stud.
, 61
(1
), pp. 1
–29
. 33.
Han
, J.
, Shi
, F.
, Chen
, L.
, and Childs
, P. R. N.
, 2018
, “A Computational Tool for Creative Idea Generation Based on Analogical Reasoning and Ontology
,” Artif. Intell. Eng. Des. Anal. Manuf.
, 32
(4
), pp. 462
–477
. 34.
Yamamoto
, E.
, Taura
, T.
, Ohashi
, S.
, and Yamamoto
, M.
, 2010
, “A Method for Function Dividing in Conceptual Design by Focusing on Linguistic Hierarchal Relations
,” ASME J. Comput. Inf. Sci. Eng.
, 10
(3
), p. 031004
. 35.
Pantel
, P.
, and Pennacchiotti
, M.
, 2008
, “Espresso: Leveraging Generic Patterns for Automatically Harvesting Semantic Relations
,” Proceedings of the 21st International Conference on Computational Linguistics and the 44th Annual Meeting of the Association for Computational Linguistics
, Sydney, Australia
, July 17–18
, pp. 113
–120
. 36.
Park
, S.-M.
, Kim
, Y.-G.
, and Baik
, D.-K.
, 2016
, “Sentiment Root Cause Analysis Based on Fuzzy Formal Concept Analysis and Fuzzy Cognitive Map
,” ASME J. Comput. Inf. Sci. Eng.
, 16
(3
), p. 031004
. 37.
Wu
, Z.
, and Palmer
, M.
, 1994
, “Verbs Semantics
and Lexical Selection,” Proceedings of the 32nd Annual Meeting on Association for Computational Linguistics
, Stroudsburg, PA
, June 27–30
, pp. 133
–138
. 38.
Li
, X.
, Chen
, C.-H.
, Zheng
, P.
, Wang
, Z.
, Jiang
, Z.
, and Jiang
, Z.
, 2020
, “A Knowledge Graph-Aided Concept-Knowledge Approach for Evolutionary Smart Product-Service System Development
,” ASME J. Mech. Des.
, 142
(10
), p. 101403
. 39.
Hatchuel
, A.
, Le Masson
, P.
, and Weil
, B.
, 2011
, “Teaching Innovative Design Reasoning: How Concept-Knowledge Theory Can Help Overcome Fixation Effects
,” Artif. Intell. Eng. Des. Anal. Manuf.
, 25
(1
), pp. 77
–92
. 40.
Cheong
, H.
, Li
, W.
, Cheung
, A.
, Nogueira
, A.
, and Iorio
, F.
, 2017
, “Automated Extraction of Function Knowledge From Text
,” ASME J. Mech. Des.
, 139
(11
), p. 111407
. 41.
Mikolov
, T.
, Chen
, K.
, Corrado
, G.
, and Dean
, J.
, 2013
, “Efficient Estimation of Word Representations in Vector Space,” arXiv preprint arXiv:1301.3781.42.
Cascini
, G.
, and Russo
, D.
, 2006
, “Computer-Aided Analysis of Patents and Search for TRIZ Contradictions
,” Int. J. Prod. Dev.
, 4
(1–2
), pp. 52
–67
.43.
Murphy
, J.
, Fu
, K.
, Otto
, K.
, Yang
, M.
, Jensen
, D.
, and Wood
, K.
, 2014
, “Function Based Design-by-Analogy: A Functional Vector Approach to Analogical Search
,” ASME J. Mech. Des.
, 136
(10
), p. 101102
. 44.
Song
, B.
, Luo
, J.
, and Wood
, K.
, 2019
, “Data-Driven Platform Design: Patent Data and Function Network Analysis
,” ASME J. Mech. Des.
, 141
(2)
), p. 021101
. 45.
Song
, B.
, and Luo
, J.
, 2017
, “Mining Patent Precedents for Data-Driven Design: The Case of Spherical Rolling Robots
,” ASME J. Mech. Des.
, 139
(11
), p. 111420
. 46.
Song
, H.
, and Fu
, K.
, 2019
, “Design-by-Analogy: Exploring for Analogical Inspiration With Behavior, Material, and Component-Based Structural Representation of Patent Databases
,” ASME J. Comput. Inf. Sci. Eng.
, 19
(2)
), p. 021014
. 47.
Jiang
, S.
, Luo
, J.
, Ruiz-Pava
, G.
, Hu
, J.
, and Magee
, C. L.
, 2021
, “Deriving Design Feature Vectors for Patent Images Using Convolutional Neural Networks
,” ASME J. Mech. Des.
, 143
(6
), p. 061405
. 48.
Hirtz
, J.
, Stone
, R.
, McAdams
, D.
, Szykman
, S.
, and Wood
, K.
, 2002
, “A Functional Basis for Engineering Design: Reconciling and Evolving Previous Efforts
,” Res. Eng. Des.
, 13
(2
), pp. 65
–82
. 49.
Tseng
, Y.-H.
, Lin
, C.-J.
, and Lin
, Y.-I.
, 2007
, “Text Mining Techniques for Patent Analysis
,” Inf. Process. Manag.
, 43
(5
), pp. 1216
–1247
. 50.
Fantoni
, G.
, Apreda
, R.
, Dell’Orletta
, F.
, and Monge
, M.
, 2013
, “Automatic Extraction of Function–Behaviour–State Information From Patents
,” Adv. Eng. Inform.
, 27
(3
), pp. 317
–334
. 51.
Bonaccorsi
, A.
, and Fantoni
, G.
, 2007
, “Expanding the Functional Ontology in Conceptual Design
,” DS 42: Proceedings of ICED 2007, the 16th International Conference on Engineering Design
, Vol. 28
, Paris, France
, July 7
, pp. 723
–724
.52.
Mao
, X.
, and Sen
, C.
, 2020
, “Semantic and Qualitative Physics-Based Reasoning on Plain-English Flow Terms for Generating Function Model Alternatives
,” ASME J. Comput. Inf. Sci. Eng.
, 20
(4
), p. 041006
. 53.
Mao
, X.
, and Sen
, C.
, 2018
, “Physics-Based Semantic Reasoning
for Function Model Decomposition,” Volume 1A: 38th Computers and Information in Engineering Conference
, Quebec City Convention Center, Quebec City, Canada
, Aug. 26
. 54.
Sarica
, S.
, Luo
, J.
, and Wood
, K. L.
, 2020
, “TechNet: Technology Semantic Network Based on Patent Data
,” Expert Syst. Appl.
, 142
(1
), p. 112995
. 55.
Mayfield
, J.
, and Finin
, T.
, 2012
, “Evaluating the Quality of a Knowledge Base Populated From Text
,” Proceedings of the Joint Workshop on Automatic Knowledge Base Construction and Web-Scale Knowledge Extraction
, Montréal, Canada
, June
, pp. 68
–73
.56.
Havasi
, C.
, Speer
, R.
, and Alonso
, J.
, 2007
, “ConceptNet: A Lexical Resource for Common Sense Knowledge
,” Int. Conf. Recent Adv. Nat. Lang. Process. RANLP
, 309
(1
), pp. 269
–280
. 57.
Mukherjee
, S.
, and Joshi
, S.
, 2013
, “Sentiment Aggregation Using ConceptNet Ontology
,” Proceedings of the Sixth International Joint Conference on Natural Language Processing
, Nagoya, Japan
, October
, pp. 570
–578
.58.
Agarwal
, B.
, Poria
, S.
, Mittal
, N.
, Gelbukh
, A.
, and Hussain
, A.
, 2015
, “Concept-Level Sentiment Analysis With Dependency-Based Semantic Parsing: A Novel Approach
,” Cogn. Comput.
, 7
(4
), pp. 487
–499
. 59.
Jamrozik
, A.
, and Gentner
, D.
, 2020
, “Relational Labeling Unlocks Inert Knowledge
,” Cognition
, 196
(1
), p. 104146
. 60.
Sarica
, S.
, Song
, B.
, Luo
, J.
, and Wood
, K. L.
, 2021
, “Idea Generation With Technology Semantic Network
,” Artif. Intell. Eng. Des. Anal. Manuf.
, FirstView, pp. 1
–19
. 61.
Pennington
, J.
, Socher
, R.
, and Manning
, C.
, 2014
, “Glove: Global Vectors for Word Representation
,” Proceedings of the 2014 Conference on Empirical Methods in Natural Language Processing (EMNLP)
, Doha, Qatar
, October
, pp. 1532
–1543
.62.
Shi
, F.
, Chen
, L.
, Han
, J.
, and Childs
, P.
, 2017
, “A Data-Driven Text Mining and Semantic Network Analysis for Design Information Retrieval
,” ASME J. Mech. Des.
, 139
(11
), p. 111402
. 63.
Lu
, R.
, Jin
, X.
, Zhang
, S.
, Qiu
, M.
, and Wu
, X.
, 2019
, “A Study on Big Knowledge and Its Engineering Issues
,” IEEE Trans. Knowl. Data Eng.
, 31
(9
), pp. 1630
–1644
. 64.
Altshuller
, G.
, Shulyak
, L.
, and Rodman
, S.
, 1999
, The Innovation Algorithm: TRIZ, Systematic Innovation and Technical Creativity
, Technical Innovation Center, Inc.
, Worcester, MA
.65.
Vincent
, J. F.
, Bogatyreva
, O.
, Pahl
, A.-K.
, Bogatyrev
, N.
, and Bowyer
, A.
, 2005
, “Putting Biology Into TRIZ: A Database of Biological Effects
,” Creat. Innov. Manag.
, 14
(1
), pp. 66
–72
. 66.
Cascini
, G.
, and Rissone
, P.
, 2004
, “Plastics Design: Integrating TRIZ Creativity and Semantic Knowledge Portals
,” J. Eng. Des.
, 15
(4
), pp. 405
–424
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