Abstract
Patent data have long been used for engineering design research because of its large and expanding size and widely varying massive amount of design information contained in patents. Recent advances in artificial intelligence and data science present unprecedented opportunities to develop data-driven design methods and tools, as well as advance design science, using the patent database. Herein, we survey and categorize the patent-for-design literature based on its contributions to design theories, methods, tools, and strategies, as well as the types of patent data and data-driven methods used in respective studies. Our review highlights promising future research directions in patent data-driven design research and practice.
Issue Section:
Special Section: Data Wrangling to Support Research on Engineering Design and Manufacturing
References
1.
Altshuller
, G. S.
, and Rafael
, B. S.
, 1956
, “Psychology of Inventive Creativity
,” Issues Psychol.
, 6
, pp. 37
–49
.2.
Fuge
, M.
, Tee
, K.
, Agogino
, A.
, and Maton
, N.
, 2014
, “Analysis of Collaborative Design Networks: A Case Study of OpenIDEO
,” ASME J. Comput. Inf. Sci. Eng.
, 14
(2
), p. 021009
. 3.
Bohm
, M. R.
, Vucovich
, J. P.
, and Stone
, R. B.
, 2008
, “Using a Design Repository to Drive Concept Generation
,” ASME J. Comput. Inf. Sci. Eng.
, 8
(1
), p. 014502
. 4.
Siddharth
, L.
, Blessing
, L. T. M.
, Wood
, K. L.
, and Luo
, J.
, 2022
, “Engineering Knowledge Graph From Patent Database
,” ASME J. Comput. Inf. Sci. Eng.
, 22
(2
), p. 021008
. 5.
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
. 6.
Sarica
, S.
, Song
, B.
, Luo
, J.
, and Wood
, K. L.
, 2021
, “Idea Generation With Technology Semantic Network
,” Artif. Intell. Eng. Des. Anal. Manuf.
, 35
(3
), pp. 265
–283
. 7.
Luo
, J.
, Sarica
, S.
, and Wood
, K. L.
, 2021
, “Guiding Data-Driven Design Ideation by Knowledge Distance
,” Knowl. Based Syst.
, 218
, p. 106873
. 8.
Song
, H.
, Evans
, J.
, and Fu
, K.
, 2020
, “An Exploration-Based Approach to Computationally Supported Design-by-Analogy Using D3
,” Artif. Intell. Eng. Des. Anal. Manuf.
, 34
(4
), pp. 444
–457
. 9.
Liu
, L.
, Li
, Y.
, Xiong
, Y.
, and Cavallucci
, D.
, 2020
, “A New Function-Based Patent Knowledge Retrieval Tool for Conceptual Design of Innovative Products
,” Comput. Ind.
, 115
, p. 103154
. 10.
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
. 11.
Atherton
, M.
, Jiang
, P.
, Harrison
, D.
, and Malizia
, A.
, 2018
, “Design for Invention: Annotation of Functional Geometry Interaction for Representing Novel Working Principles
,” Res. Eng. Des.
, 29
(2
), pp. 245
–262
. 12.
Jiang
, P.
, Atherton
, M.
, Sorce
, S.
, Harrison
, D.
, and Malizia
, A.
, 2018
, “Design for Invention: A Framework for Identifying Emerging Design–Prior Art Conflict
,” J. Eng. Des.
, 29
(10
), pp. 596
–615
. 13.
Jiang
, S.
, Hu
, J.
, Magee
, C. L.
, and Luo
, J.
, 2022
, “Deep Learning for Technical Document Classification
,” IEEE Trans. Eng. Manage.
, pp. 1
–17
. 14.
Fu
, K.
, Cagan
, J.
, Kotovsky
, K.
, and Wood
, K.
, 2013
, “Discovering Structure in Design Databases Through Functional and Surface Based Mapping
,” ASME J. Mech. Des.
, 135
(3
), p. 031006
. 15.
Song
, B.
, Yan
, B.
, Triulzi
, G.
, Alstott
, J.
, and Luo
, J.
, 2019
, “Overlay Technology Space Map for Analyzing Design Knowledge Base of a Technology Domain: The Case of Hybrid Electric Vehicles
,” Res. Eng. Des.
, 30
(3
), pp. 405
–423
. 16.
Luo
, J.
, and Wood
, K. L.
, 2017
, “The Growing Complexity in Invention Process
,” Res. Eng. Des.
, 28
(4
), pp. 421
–435
. 17.
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
. 18.
Alstott
, J.
, Triulzi
, G.
, Yan
, B.
, and Luo
, J.
, 2017
, “Inventors’ Explorations Across Technology Domains
,” Des. Sci.
, 3
(e20
), pp. 1
–29
. 19.
Smojver
, V.
, Štorga
, M.
, and Potočki
, E.
, 2016
, “An Extended Methodology for the Assessment of Technical Invention Evolution
,” International Design Conference (DESIGN2016)
, Dubrovnik, Croatia
, May 16–19
, pp. 1135
–1144
.20.
Ishii
, T.
, Parque
, V.
, Miura
, S.
, and Miyashita
, T.
, 2017
, “Definition and Support of Differentiation and Integration in Mechanical Structure Using S-Curve Theory and Wavelet Transform
,” International Conference on Engineering Design (ICED17)
, Vancouver, Canada
, Aug. 21–25
, pp. 355
–364
.21.
Chan
, T.
, Mihm
, J.
, and Sosa
, M.
, 2012
, “A Structured Approach to Identify Styles in Design
,” ASME International Design Engineering Technical Conferences and Computers and Information in Engineering Conference (IDETC/CIE 2012)
, Chicago, IL
, Aug. 12–15
, pp. 541
–550
.22.
Sarica
, S.
, Luo
, J.
, and Wood
, K. L.
, 2020
, “TechNet: Technology Semantic Network Based on Patent Data
,” Expert Syst. Appl.
, 142
, p. 112995
. 23.
Russo
, D.
, Montecchi
, T.
, and Liu
, Y.
, 2012
, “Functional-Based Search for Patent Technology Transfer
,” ASME International Design Engineering Technical Conferences and Computers and Information in Engineering Conference (IDETC/CIE 2012)
, Chicago, IL, Aug
. 12–15, pp. 529
–539
.24.
Sarica
, S.
, Song
, B.
, Low
, E.
, and Luo
, J.
, 2019
, “Engineering Knowledge Graph for Keyword Discovery in Patent Search
,” International Conference on Engineering Design (ICED19)
, The Netherlands
, Aug. 5–8
, pp. 2249
–2258
.25.
Fu
, K.
, Chan
, J.
, Schunn
, C.
, Cagan
, J.
, and Kotovsky
, K.
, 2013
, “Expert Representation of Design Repository Space: A Comparison to and Validation of Algorithmic Output
,” Des. Stud.
, 34
(6
), pp. 729
–762
. 26.
Hagedorn
, T. J.
, Grosse
, I. R.
, and Krishnamurty
, S.
, 2015
, “A Concept Ideation Framework for Medical Device Design
,” J. Biomed. Inform.
, 55
, pp. 218
–230
. 27.
Li
, M.
, Ming
, X.
, Zheng
, M.
, Xu
, Z.
, and He
, L.
, 2013
, “A Framework of Product Innovative Design Process Based on TRIZ and Patent Circumvention
,” J. Eng. Des.
, 24
(12
), pp. 830
–848
. 28.
Van Wie
, M.
, Bryant
, C. R.
, Bohm
, M. R.
, McAdams
, D. A.
, and Stone
, R. B.
, 2005
, “A Model of Function-Based Representations
,” Artif. Intell. Eng. Des. Anal. Manuf.
, 19
(2
), pp. 89
–111
. 29.
Vandevenne
, D.
, Verhaegen
, P.-A.
, Dewulf
, S.
, and Duflou
, J. R.
, 2016
, “SEABIRD: Scalable Search for Systematic Biologically Inspired Design
,” Artif. Intell. Eng. Des. Anal. Manuf.
, 30
(1
), pp. 78
–95
. 30.
Verhaegen
, P.
, Joris
, D.
, Vandevenne
, D.
, Dewulf
, S.
, and Duflou
, J. R.
, 2011
, “Identifying Candidates for Design-by-Analogy
,” Comput. Ind.
, 62
(4
), pp. 446
–459
. 31.
Melluso
, N.
, Pardelli
, S.
, Fantoni
, G.
, Chiarello
, F.
, and Bonaccorsi
, A.
, 2021
, “Detecting Bad Design and Bias From Patents
,” International Conference on Engineering Design (ICED21)
, Gothenburg, Sweden
, Aug. 16–20
, pp. 1173
–1182
.32.
Li
, Z.
, and Tate
, D.
, 2010
, “Automatic Function Interpretation: Using Natural Language Processing on Patents to Understand Design Purposes
,” ASME International Design Engineering Technical Conferences and Computers and Information in Engineering Conference (IDETC/CIE 2010)
, Montreal, Quebec, Canada
, Aug. 15–18
, pp. 443
–452
.33.
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
. 34.
Fu
, K.
, Murphy
, J.
, Yang
, M.
, Otto
, K.
, Jensen
, D.
, and Wood
, K.
, 2015
, “Design-by-Analogy: Experimental Evaluation of a Functional Analogy Search Methodology for Concept Generation Improvement
,” Res. Eng. Des.
, 26
(1
), pp. 77
–95
. 35.
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
. 36.
Fu
, K.
, Chan
, J.
, Cagan
, J.
, Kotovsky
, K.
, Schunn
, C.
, and Wood
, K.
, 2013
, “The Meaning of ‘Near’ and ‘Far’: The Impact of Structuring Design Databases and the Effect of Distance of Analogy on Design Output
,” ASME J. Mech. Des.
, 135
(2
), p. 021007
. 37.
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
. 38.
Li
, Z.
, Tate
, D.
, Lane
, C.
, and Adams
, C.
, 2012
, “A Framework for Automatic TRIZ Level of Invention Estimation of Patents Using Natural Language Processing, Knowledge-Transfer and Patent Citation Metrics
,” Comput. Aided Des.
, 44
(10
), pp. 987
–1010
. 39.
Liang
, Y.
, Liu
, Y.
, Kwong
, C. K.
, and Lee
, W. B.
, 2012
, “Learning the ‘Whys’: Discovering Design Rationale Using Text Mining—An Algorithm Perspective
,” Comput. Aided Des.
, 44
(10
), pp. 916
–930
. 40.
Liu
, Y.
, Liang
, Y.
, Kwong
, C. K.
, and Lee
, W. B.
, 2010
, “A New Design Rationale Representation Model for Rationale Mining
,” ASME J. Comput. Inf. Sci. Eng.
, 10
(3
), p. 031009
. 41.
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
. 42.
Cascini
, G.
, and Russo
, D.
, 2007
, “Computer-Aided Analysis of Patents and Search for TRIZ Contradictions
,” Int. J. Prod. Dev.
, 4
(1
), pp. 52
–67
. 43.
Smojver
, V.
, Potočki
, E.
, and Štorga
, M.
, 2017
, “A Visual Analysis of Technical Knowledge Evolution Based on Patent Data
,” International Conference on Engineering Design (ICED17)
, Vancouver, Canada
, Aug. 21–25
, pp. 307
–316
.44.
Chiarello
, F.
, Cirri
, I.
, Melluso
, N.
, Fantoni
, G.
, Bonaccorsi
, A.
, and Pavanello
, T.
, 2019
, “Approaches to Automatically Extract Affordances From Patents
,” International Conference on Engineering Design (ICED19)
, Delft, The Netherlands
, Aug. 5–8
, pp. 2487
–2496
.45.
Jiang
, P.
, Atherton
, M.
, and Sorce
, S.
, 2021
, “Automated Functional Analysis of Patents for Producing Design Insight
,” International Conference on Engineering Design (ICED21)
, Gothenburg, Sweden
, Aug. 16–20
, pp. 541
–550
.46.
Chang
, H. T.
, Chang
, C. Y.
, and Yang
, Y. P.
, 2013
, “Combining Surveying Patent Information, Reappearing Problem and Discovering Breakthrough for Design-Around
,” International Conference on Engineering Design (ICED13)
, Seoul, South Korea
, Aug. 19–22
, pp. 417
–426
.47.
Bonaccorsi
, A.
, and Fantoni
, G.
, 2007
, “Expanding the Functional Ontology in Conceptual Design
,” International Conference on Engineering Design (ICED07)
, Paris, France
, Aug. 28–31
, pp. 1
–12
.48.
Jiang
, P.
, Atherton
, M.
, Harrison
, D.
, and Malizia
, A.
, 2017
, “Framework of Mechanical Design Knowledge Representations for Avoiding Patent Infringement
,” International Conference on Engineering Design (ICED17)
, Vancouver, Canada
, Aug. 21–25
, pp. 81
–90
.49.
Chiarello
, F.
, Fantoni
, G.
, and Bonaccorsi
, A.
, 2017
, “Product Description in Terms of Advantages and Drawbacks: Exploiting Patent Information in Novel Ways
,” International Conference on Engineering Design (ICED17)
, Vancouver, Canada
, Aug. 21–25
, pp. 101
–110
.50.
Russo
, D.
, and Montecchi
, T.
, 2011
, “A Function-Behaviour Oriented Search for Patent Digging
,” International Design Engineering Technical Conferences and Computers and Information in Engineering Conference (IDETC/CIE 2011)
, Washington, DC
, Aug. 28–31
, pp. 1111
–1120
.51.
Sanaei
, R.
, Lu
, W.
, Blessing
, L. T. M.
, Otto
, K. N.
, and Wood
, K. L.
, 2017
, “Analogy Retrieval Through Textual Inference
,” International Design Engineering Technical Conferences and Computers and Information in Engineering Conference (IDETC/CIE 2017)
, Cleveland, OH
, Aug. 6–9
, Paper No. V02AT03A007
.52.
Li
, Z.
, and Tate
, D.
, 2013
, “Interpreting Design Structure in Patents Using an Ontology Library
,” ASME International Design Engineering Technical Conferences and Computers and Information in Engineering Conference (IDETC/CIE 2013)
, Paper No. V005T06A004
.53.
Srinivasan
, V.
, Song
, B.
, Luo
, J.
, Subburaj
, K.
, Elara
, M. R.
, Blessing
, L.
, and Wood
, K.
, 2018
, “Does Analogical Distance Affect Performance of Ideation?
,” ASME J. Mech. Des.
, 140
(7
), p. 071101
. 54.
Luo
, J.
, Song
, B.
, Blessing
, L.
, and Wood
, K.
, 2018
, “Design Opportunity Conception Using the Total Technology Space Map
,” Artif. Intell. Eng. Des. Anal. Manuf.
, 32
(4
), pp. 449
–461
. 55.
Luo
, J.
, Yan
, B.
, and Wood
, K.
, 2017
, “InnoGPS for Data-Driven Exploration of Design Opportunities and Directions: The Case of Google Driverless Car Project
,” ASME J. Mech. Des.
, 139
(11
), p. 111416
. 56.
Song
, B.
, Srinivasan
, V.
, and Luo
, J.
, 2017
, “Patent Stimuli Search and Its Influence on Ideation Outcomes
,” Des. Sci.
, 3
(e25
), pp. 1
–25
. 57.
He
, Y.
, and Luo
, J.
, 2017
, “The Novelty ‘Sweet Spot’of Invention
,” Des. Sci.
, 3
(e21
), pp. 1
–22
. 58.
Rios-Zapata
, D.
, Duarte
, R.
, Pailhès
, J.
, Mejia-Gutiérrez
, R.
, and Mesnard
, M.
, 2017
, “Patent-Based Creativity Method for Early Design Stages: Case Study in Locking Systems for Medical Applications
,” Int. J. Interact. Des. Manuf.
, 11
(3
), pp. 689
–701
. 59.
Koh
, E. C. Y.
, 2020
, “Read the Full Patent or Just the Claims? Mitigating Design Fixation and Design Distraction When Reviewing Patent Documents
,” Des. Stud.
, 68
, pp. 34
–57
. 60.
Siddharth
, L.
, Madhusudanan
, N.
, and Chakrabarti
, A.
, 2020
, “Toward Automatically Assessing the Novelty of Engineering Design Solutions
,” ASME J. Comput. Inf. Sci. Eng.
, 20
(1
), p. 011001
. 61.
Saliminamin
, S.
, Becattini
, N.
, and Cascini
, G.
, 2019
, “Sources of Creativity Stimulation for Designing the Next Generation of Technical Systems: Correlations With R&D Designers’ Performance
,” Res. Eng. Des.
, 30
(1
), pp. 133
–153
. 62.
Koh
, E. C. Y.
, and De Lessio
, M. P.
, 2018
, “Fixation and Distraction in Creative Design: The Repercussions of Reviewing Patent Documents to Avoid Infringement
,” Res. Eng. Des.
, 29
(3
), pp. 351
–366
. 63.
Wodehouse
, A.
, Vasantha
, G.
, Corney
, J.
, Jagadeesan
, A.
, and MacLachlan
, R.
, 2018
, “Realising the Affective Potential of Patents: A New Model of Database Interpretation for User-Centred Design
,” Res. Eng. Des.
, 29
(8–9
), pp. 484
–511
. 64.
Hwang
, D.
, and Park
, W.
, 2018
, “Design Heuristics Set for X: A Design Aid for Assistive Product Concept Generation
,” Des. Stud.
, 58
, pp. 89
–126
. 65.
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
. 66.
Kokshagina
, O.
, Le Masson
, P.
, and Weil
, B.
, 2017
, “Should We Manage the Process of Inventing? Designing for Patentability
,” Res. Eng. Des.
, 28
(4
), pp. 457
–475
. 67.
Valverde
, U. Y.
, Nadeau
, J.-P.
, and Scaravetti
, D.
, 2017
, “A New Method for Extracting Knowledge From Patents to Inspire Designers During the Problem-Solving Phase
,” J. Eng. Des.
, 28
(6
), pp. 369
–407
. 68.
Wodehouse
, A.
, Vasantha
, G.
, Corney
, J.
, Maclachlan
, R.
, and Jagadeesan
, A.
, 2017
, “The Generation of Problem-Focussed Patent Clusters: A Comparative Analysis of Crowd Intelligence With Algorithmic and Expert Approaches
,” Des. Sci.
, 3
(e16
), pp. 1
–31
. 69.
McCaffrey
, T.
, and Spector
, L.
, 2018
, “An Approach to Human–Machine Collaboration in Innovation
,” Artif. Intell. Eng. Des. Anal. Manuf.
, 32
(1
), pp. 1
–15
. 70.
Li
, M.
, Ming
, X.
, He
, L.
, Zheng
, M.
, and Xu
, Z.
, 2015
, “A TRIZ-Based Trimming Method for Patent Design Around
,” Comput. Aided Des.
, 62
, pp. 20
–30
. 71.
Koh
, E. C. Y.
, 2013
, “Engineering Design and Intellectual Property: Where Do They Meet?
,” Res. Eng. Des.
, 24
(4
), pp. 325
–329
. 72.
Linsey
, J. S.
, Markman
, A. B.
, and Wood
, K. L.
, 2012
, “Design by Analogy: A Study of the WordTree Method for Problem Re-Representation
,” ASME J. Mech. Des.
, 134
(4
), p. 041009
. 73.
Chan
, J.
, Fu
, K.
, Schunn
, C.
, Cagan
, J.
, Wood
, K.
, and Kotovsky
, K.
, 2011
, “On the Benefits and Pitfalls of Analogies for Innovative Design: Ideation Performance Based on Analogical Distance, Commonness, and Modality of Examples
,” ASME J. Mech. Des.
, 133
(8
), p. 081004
. 74.
Fitzgerald
, D. P.
, Herrmann
, J. W.
, and Schmidt
, L. C.
, 2010
, “A Conceptual Design Tool for Resolving Conflicts Between Product Functionality and Environmental Impact
,” ASME J. Mech. Des.
, 132
(9
), p. 091006
. 75.
Weaver
, J.
, Wood
, K.
, Crawford
, R.
, and Jensen
, D.
, 2010
, “Transformation Design Theory: A Meta-Analogical Framework
,” ASME J. Comput. Inf. Sci. Eng.
, 10
(3
), p. 031012
. 76.
Singh
, V.
, Skiles
, S. M.
, Krager
, J. E.
, Wood
, K. L.
, Jensen
, D.
, and Sierakowski
, R.
, 2009
, “Innovations in Design Through Transformation: A Fundamental Study of Transformation Principles
,” ASME J. Mech. Des.
, 131
(8
), p. 081010
. 77.
Koza
, J. R.
, 2008
, “Human-Competitive Machine Invention by Means of Genetic Programming
,” Artif. Intell. Eng. Des. Anal. Manuf.
, 22
(3
), pp. 185
–193
. 78.
Jugulum
, R.
, and Frey
, D. D.
, 2007
, “Toward a Taxonomy of Concept Designs for Improved Robustness
,” J. Eng. Des.
, 18
(2
), pp. 139
–156
. 79.
Busby
, J. A.
, and Lloyd
, P. A.
, 1999
, “Influences on Solution Search Processes in Design Organisations
,” Res. Eng. Des.
, 11
(3
), pp. 158
–171
. 80.
Hsu
, Y. L.
, Hsu
, P. E.
, Hung
, Y. C.
, and Xiao
, Y. D.
, 2010
, “Development and Application of a Patent-Based Design Around Process
,” ASME International Design Engineering Technical Conferences and Computers and Information in Engineering Conference (IDETC/CIE 2010)
, Montreal, Quebec, Canada
, Aug. 15–18
, pp. 91
–100
.81.
Qureshi
, A.
, Murphy
, J. T.
, Kuchinsky
, B.
, Seepersad
, C. C.
, Wood
, K. L.
, and Jensen
, D. D.
, 2006
, “Principles of Product Flexibility
,” ASME International Design Engineering Technical Conferences and Computers and Information in Engineering Conference (IDETC/CIE 2006)
, Philadelphia, PA, USA
, Sept. 10–13
, pp. 295
–325
.82.
Parvin
, M.
, Cascini
, G.
, and Becattini
, N.
, 2017
, “Information Extracted From Patents As Creative Stimuli for Product Innovation
,” International Conference on Engineering Design (ICED17)
, Vancouver, Canada
, Aug. 21–25
, pp. 297
–306
.83.
Lupu
, M.
, Fujii
, A.
, Oard
, D. W.
, Iwayama
, M.
, and Kando
, N.
, 2017
, “Patent-Related Tasks at NTCIR,” Current Challenges in Patent Information Retrieval
, Springer
, New York
, pp. 77
–111
.84.
Piroi
, F.
, and Hanbury
, A.
, 2017
, “Evaluating Information Retrieval Systems on European Patent Data: The CLEF-IP Campaign,” Current Challenges in Patent Information Retrieval
, Springer
, New York
, pp. 113
–142
.85.
Campbell
, M. I.
, Hölttä-Otto
, K.
, and Linsey
, J.
, 2016
, “Special Issue on Design Theory and Methodology,” ASME J. Mech. Des.
, 138
(10
), p. 100301
. 86.
Goel
, A. K.
, and de Silva Garza
, A. G.
, 2010
, “Special Issue on Artificial Intelligence in Design
,” ASME J. Comput. Inf. Sci. Eng.
, 10
(3
), p. 030301
. 87.
Allison
, J. T.
, Cardin
, M.-A.
, McComb
, C.
, Ren
, M. Y.
, Selva
, D.
, Tucker
, C.
, Witherell
, P.
, and Zhao
, Y. F.
, 2022
, “Special Issue on Artificial Intelligence and Engineering Design
,” ASME J. Mech. Des.
, 144
(2
), p. 020301
. 88.
Spillers
, W. R.
, and Newsome
, S. L.
, 1993
, “Engineering Design, Conceptual Design, and Design Theory: A Report,” Design Methodology and Relationships With Science
, Springer
, New York
, pp. 103
–120
.89.
Chiarello
, F.
, Belingheri
, P.
, and Fantoni
, G.
, 2021
, “Data Science for Engineering Design: State of the Art and Future Directions,” Comput. Ind.
, 129
, p. 103447
. 90.
Luo
, J.
, Sarica
, S.
, and Wood
, K. L.
, 2019
, “Computer-Aided Design Ideation Using InnoGPS
,” ASME 2019 IDETC/CIE
, Anaheim, CA
, Aug. 18–21
, p. V02AT03A011
.91.
McComb
, C.
, Cagan
, J.
, and Kotovsky
, K.
, 2017
, “Mining Process Heuristics From Designer Action Data Via Hidden Markov Models
,” ASME J. Mech. Des.
, 139
(11
), p. 111412
. 92.
Chandrasekaran
, B.
, 1990
, “Design Problem Solving: A Task Analysis
,” AI Mag.
, 11
(4
), pp. 59
–71
. 93.
Luo
, J.
, 2015
, “The United Innovation Process: Integrating Science, Design, and Entrepreneurship As Sub-Processes
,” Des. Sci.
, 1
(e2
), pp. 1
–29
. 94.
Jiang
, S.
, Hu
, J.
, Wood
, K. L.
, and Luo
, J.
, 2022
, “Data-Driven Design-By-Analogy: State-of-the-Art and Future Directions
,” ASME J. Mech. Des.
, 144
(2
), p. 020801
. 95.
Qian
, L.
, and Gero
, J. S.
, 1996
, “Function-Behavior-Structure Paths and Their Role in Analogy-Based Design
,” Artif. Intell. Eng. Des. Anal. Manuf.
, 10
(4
), pp. 289
–312
. 96.
Mccaffrey
, A.
, 2016
, “Analogy Finder
,” U.S. Patent No. US 9,501,469.97.
Chakrabarti
, A.
, Sarkar
, P.
, Leelavathamma
, B.
, and Nataraju
, B. S.
, 2005
, “A Functional Representation for Aiding Biomimetic and Artificial Inspiration of New Ideas
,” Artif. Intell. Eng. Des. Anal. Manuf.
, 19
(2
), pp. 113
–132
. 98.
Sarica
, S.
, and Luo
, J.
, 2021
, “Design Knowledge Representation With Technology Semantic Network
,” Proceedings of the Design Society: International Conference on Engineering Design (ICED)
, Gothenburg, Sweden
, Aug. 16–20
, pp. 1043
–1052
.99.
Han
, J.
, Forbes
, H.
, Shi
, F.
, Hao
, J.
, and Schaefer
, D.
, 2020
, “A Data-Driven Approach for Creative Concept Generation and Evaluation
,” Proceedings of the Design Society: DESIGN Conference (DESIGN 2020)
, Online
, Oct. 26–29
, pp. 167
–176
.100.
Han
, J.
, Sarica
, S.
, Shi
, F.
, and Luo
, J.
, 2022
, “Semantic Networks for Engineering Design: State of the Art and Future Directions
,” ASME J. Mech. Des.
, 144
(2
), p. 020802
. 101.
Choi
, S.
, Lee
, H.
, Park
, E.
, and Choi
, S.
, 2022
, “Deep Learning for Patent Landscaping Using Transformer and Graph Embedding
,” Technol. Forecast. Soc. Change
, 175
, p. 121413
. 102.
Risch
, J.
, Alder
, N.
, Hewel
, C.
, and Krestel
, R.
, 2021
, “PatentMatch: A Dataset for Matching Patent Claims & Prior Art
,” Proceedings of the 44th International ACM SIGIR Conference, the Second Workshop on Patent Text Mining and Semantic Technologies (PatentSemTech)
, Online
, July 15
, pp. 1
–5
.103.
Risch
, J.
, Garda
, S.
, and Krestel
, R.
, 2020
, “Hierarchical Document Classification As a Sequence Generation Task
,” Proceedings of the ACM/IEEE Joint Conference on Digital Libraries in 2020
, Online
, Aug. 1–5
, pp. 147
–155
.104.
Lyu
, L.
, and Han
, T.
, 2019
, “A Comparative Study of Chinese Patent Literature Automatic Classification Based on Deep Learning
,” 2019 ACM/IEEE Joint Conference on Digital Libraries (JCDL)
, Champaign, IL
, June 2–6
, pp. 345
–346
.105.
Shalaby
, M.
, Stutzki
, J.
, Schubert
, M.
, and Günnemann
, S.
, 2018
, “An LSTM Approach to Patent Classification Based on Fixed Hierarchy Vectors
,” Proceedings of the 2018 SIAM International Conference on Data Mining
, San Diego, CA
, May 3–5
, pp. 495
–503
.106.
Qi
, J.
, Lei
, L.
, Zheng
, K.
, and Wang
, X.
, 2020
, “Patent Analytic Citation-Based VSM: Challenges and Applications
,” IEEE Access
, 8
, pp. 17464
–17476
. 107.
Lin
, H.
, Wang
, H.
, Du
, D.
, Wu
, H.
, Chang
, B.
, and Chen
, E.
, 2018
, “Patent Quality Valuation With Deep Learning Models
,” International Conference on Database Systems for Advanced Applications
, Gold Coast, QLD, Australia
, May 21–24
, pp. 474
–490
.108.
Bhattarai
, M.
, Oyen
, D.
, Castorena
, J.
, Yang
, L.
, and Wohlberg
, B.
, 2020
, “Diagram Image Retrieval Using Sketch-Based Deep Learning and Transfer Learning
,” Proceedings of the IEEE/CVF Conference on Computer Vision and Pattern Recognition Workshops (CVPRW)
, Seattle, WA
, June 14–19
, pp. 663
–672
.109.
Chen
, L.
, Xu
, S.
, Zhu
, L.
, Zhang
, J.
, Lei
, X.
, and Yang
, G.
, 2020
, “A Deep Learning Based Method for Extracting Semantic Information From Patent Documents
,” Scientometrics
, 125
(1
), pp. 289
–312
. 110.
Zuo
, H.
, Yin
, Y.
, and Childs
, P.
, 2022
, “Patent-KG: Patent Knowledge Graph Extraction for Engineering Design
,” International Design Conference (DESIGN 2022)
, Online
, May 23–26
, pp. 821
–830
.111.
Zhang
, Z.
, Cui
, P.
, and Zhu
, W.
, 2022
, “Deep Learning on Graphs: A Survey
,” IEEE Trans. Knowl. Data Eng.
, 34
(1
), pp. 249
–270
. 112.
Gao
, J.
, Li
, P.
, Chen
, Z.
, and Zhang
, J.
, 2020
, “A Survey on Deep Learning for Multimodal Data Fusion
,” Neural Comput.
, 32
(5
), pp. 829
–864
. 113.
Rezende
, D. J.
, Mohamed
, S.
, and Wierstra
, D.
, 2014
, “Stochastic Backpropagation and Approximate Inference in Deep Generative Models
,” Proceedings of the 31st International Conference on Machine Learning (ICML)
, Beijing, China
, June 21–26
, pp. 1278
–1286
.114.
Goodfellow
, I.
, Pouget-Abadie
, J.
, Mirza
, M.
, Xu
, B.
, Warde-Farley
, D.
, Ozair
, S.
, Courville
, A.
, and Bengio
, Y.
, 2014
, “Generative Adversarial Nets
,” Proceedings of the 27th Conference on Neural Information Processing Systems (NIPS)
, Montreal, Quebec, Canada
, Dec. 8–13
, pp. 2672
–2680
.115.
Brown
, T. B.
, Mann
, B.
, Ryder
, N.
, Subbiah
, M.
, Kaplan
, J.
, Dhariwal
, P.
, Neelakantan
, A.
, Shyam
, P.
, Sastry
, G.
, and Askell
, A.
, 2020
, “Language Models Are Few-Shot Learners
,” The Proceedings of 33th Conference on Neural Information Processing Systems (NeurIPS)
, Virtual
, Dec. 7–12
, pp. 1877
–1901
.116.
Devlin
, J.
, Chang
, M.-W.
, Lee
, K.
, and Toutanova
, K.
, 2019
, “BERT: Pre-training of Deep Bidirectional Transformers for Language Understanding
,” Proceedings of the 2019 Conference of the North American Chapter of the Association for Computational Linguistics: Human Language Technologies (NAACL-HLT)
, Minneapolis, MN
, June 2–7
, pp. 4171
–4186
.117.
Regenwetter
, L.
, Nobari
, A. H.
, and Ahmed
, F.
, 2021
, “Deep Generative Models in Engineering Design: A Review
,” arXiv preprint arXiv:2110.10863.118.
Zhu
, Q.
, and Luo
, J.
, 2022
, “Generative Design Ideation: A Natural Language Generation Approach
,” Design Computing and Cognition
, Glasgow, UK
, July 4–6
.119.
Arrieta
, A. B.
, Díaz-Rodríguezb
, N.
, Del Ser
, J.
, Bennetot
, A.
, Tabik
, S.
, Barbado
, A.
, Garcia
, S.
, Gil-López
, S.
, Molina
, D.
, and Benjamins
, R.
, 2020
, “Explainable Artificial Intelligence (XAI): Concepts, Taxonomies, Opportunities and Challenges Toward Responsible AI
,” Inf. Fusion
, 58
, pp. 82
–115
. 120.
Liu
, Q.
, and Wong
, K. P.
, 2011
, “Intellectual Capital and Financing Decisions: Evidence From the US Patent Data
,” Manage. Sci.
, 57
(10
), pp. 1861
–1878
. 121.
Hegde
, D.
, and Luo
, H.
, 2018
, “Patent Publication and the Market for Ideas
,” Manage. Sci.
, 64
(2
), pp. 652
–672
. 122.
Wu
, L.
, Hitt
, L.
, and Lou
, B.
, 2020
, “Data Analytics, Innovation, and Firm Productivity
,” Manage. Sci.
, 66
(5
), pp. 2017
–2039
. 123.
Bakker
, J.
, 2017
, “The Log-Linear Relation Between Patent Citations and Patent Value
,” Scientometrics
, 110
(2
), pp. 879
–892
. 124.
Bass
, S.
, and Kurgan
, L.
, 2010
, “Discovery of Factors Influencing Patent Value Based on Machine Learning in Patents in the Field of Nanotechnology
,” Scientometrics
, 82
(2
), pp. 217
–241
. 125.
Du
, W.
, Wang
, Y.
, Xu
, W.
, and Ma
, J.
, 2021
, “A Personalized Recommendation System for High-Quality Patent Trading by Leveraging Hybrid Patent Analysis
,” Scientometrics
, 126
(12
), pp. 9369
–9391
. 126.
Chan
, T. H.
, Mihm
, J.
, and Sosa
, M. E.
, 2018
, “On Styles in Product Design: An Analysis of US Design Patents
,” Manage. Sci.
, 64
(3
), pp. 1230
–1249
. 127.
Huenteler
, J.
, Ossenbrink
, J.
, Schmidt
, T. S.
, and Hoffmann
, V. H.
, 2016
, “How a Product’s Design Hierarchy Shapes the Evolution of Technological Knowledge—Evidence From Patent-Citation Networks in Wind Power
,” Res. Policy
, 45
(6
), pp. 1195
–1217
. 128.
Lee
, J.-S.
, and Hsiang
, J.
, 2020
, “Patent Claim Generation by Fine-Tuning OpenAI GPT-2
,” World Pat. Inf.
, 62
, p. 101983
. 129.
Parraguez
, P.
, and Maier
, A.
, 2017
, “Data-Driven Engineering Design Research: Opportunities Using Open Data
,” Proceedings of the 21st International Conference on Engineering Design (ICED 17)
, Vancouver, Canada
, Aug. 21–25
, pp. 41
–50
.130.
Lee
, K.
, and Lee
, J.
, 2021
, “National Innovation Systems, Economic Complexity, and Economic Growth: Country Panel Analysis Using the US Patent Data,” Innovation, Catch-up and Sustainable Development
, Springer
, New York
, pp. 113
–151
.131.
Aristodemou
, L.
, and Tietze
, F.
, 2018
, “The State-of-the-Art on Intellectual Property Analytics (IPA): A Literature Review on Artificial Intelligence, Machine Learning and Deep Learning Methods for Analysing Intellectual Property (IP) Data
,” World Pat. Inf.
, 55
, pp. 37
–51
. 132.
Shalaby
, W.
, and Zadrozny
, W.
, 2019
, “Patent Retrieval : A Literature Review
,” Knowl. Inf. Syst.
, 61
(2
), pp. 631
–660
. 133.
Krestel
, R.
, Chikkamath
, R.
, Hewel
, C.
, and Risch
, J.
, 2021
, “A Survey on Deep Learning for Patent Analysis
,” World Pat. Inf.
, 65
, p. 102035
. 134.
Fleming
, N.
, 2018
, “How Artificial Intelligence Is Changing Drug Discovery
,” Nature
, 557
(7706
), pp. S55
–S57
. 135.
Teng
, F.
, Sun
, Y.
, Chen
, F.
, Qin
, A.
, and Zhang
, Q.
, 2021
, “Technology Opportunity Discovery of Proton Exchange Membrane Fuel Cells Based on Generative Topographic Mapping
,” Technol. Forecast. Soc. Change
, 169
, p. 120859
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