Data-driven engineering designers often search for design precedents in patent databases to learn about relevant prior arts, seek design inspiration, or assess the novelty of their own new inventions. However, patent retrieval relevant to the design of a specific product or technology is often unstructured and unguided, and the resultant patents do not sufficiently or accurately capture the prior design knowledge base. This paper proposes an iterative and heuristic methodology to comprehensively search for patents as precedents of the design of a specific technology or product for data-driven design. The patent retrieval methodology integrates the mining of patent texts, citation relationships, and inventor information to identify relevant patents; particularly, the search keyword set, citation network, and inventor set are expanded through the designer's heuristic learning from the patents identified in prior iterations. The method relaxes the requirement for initial search keywords while improving patent retrieval completeness and accuracy. We apply the method to identify self-propelled spherical rolling robot (SPSRRs) patents. Furthermore, we present two approaches to further integrate, systemize, visualize, and make sense of the design information in the retrieved patent data for exploring new design opportunities. Our research contributes to patent data-driven design.

References

References
1.
Hatchuel
,
A.
, and
Weil
,
B.
,
2003
, “
A New Approach of Innovative Design: An Introduction to CK Theory
,”
The 14th International Conference on Engineering Design
(
ICED
), Stockholm, Sweden, Aug. 19–21, pp.
109
110
.
2.
Hatchuel
,
A.
, and
Weil
,
B.
,
2009
, “
C–K Design Theory: An Advanced Formulation
,”
Res. Eng. Des.
,
19
(
4
), pp.
181
192
.
3.
Montecchi
,
T.
,
Russo
,
D.
, and
Liu
,
Y.
,
2013
, “
Searching in Cooperative Patent Classification: Comparison Between Keyword and Concept-Based Search
,”
Adv. Eng. Inform.
,
27
(
3
), pp.
335
345
.
4.
Srinivasan
,
V.
,
Song
,
B.
,
Luo
,
J.
,
Subburaj
,
K.
,
Elara
,
M. R.
,
Blessing
,
L.
, and
Wood
,
K.
,
2017
, “
Investigating Effects of Analogical Distance on Ideation Performance
,” International Design Engineering Technical Conferences & Computers and Information in Engineering Conference (IDETC/CIE), Aug. 6–9, Cleveland, OH.
5.
Srinivasan
,
V.
,
Song
,
B.
,
Luo
,
J.
,
Subburaj
,
K.
,
Elara
,
M. R.
,
Blessing
,
L.
, and
Wood
,
K.
,
2017
, “
Investigating Effects of Stimuli on Ideation Outcomes
,”
International Conference on Engineering Design
(ICED), Vancouver, BC, Canada, Paper No.
ICED2017_272
.
6.
Mukherjea
,
S.
,
Bhuvan
,
B.
, and
Kankar
,
P.
,
2005
, “
Information Retrieval and Knowledge Discovery Utilizing a Biomedical Patent Semantic Web
,”
IEEE Trans. Knowl. Data Eng.
,
17
(
8
), pp.
1099
1110
.
7.
Murphy
,
J. T.
,
2011
, “
Patent-Based Analogy Search Tool for Innovative Concept Generation
,”
Ph.D. thesis
, The University of Texas at Austin, Austin, TX.
8.
Fu
,
K.
,
Cagan
,
J.
,
Kotovsky
,
K.
, and
Wood
,
K.
,
2013
, “
Discovering Structure in Design Databases Through Function and Surface Based Mapping
,”
ASME J. Mech. Des.
,
135
(
3
), p.
031006
.
9.
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
.
10.
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
.
11.
Benson
,
C. L.
, and
Magee
,
C. L.
,
2013
, “
A Hybrid Keyword and Patent Class Methodology for Selecting Relevant Sets of Patents for a Technological Field
,”
Scientometrics
,
96
(
1
), pp.
69
82
.
12.
Benson
,
C. L.
,
2014
, “
Cross-Domain Comparison of Quantitative Technology Improvement Using Patent Derived Characteristics
,”
Ph.D. thesis
, Massachusetts Institute of Technology, Cambridge, MA.
13.
Nakamura
,
H.
,
Suzuki
,
S.
,
Sakata
,
I.
, and
Kajikawa
,
Y.
,
2015
, “
Knowledge Combination Modeling: The Measurement of Knowledge Similarity Between Different Technological Domains
,”
Technol. Forecasting Soc. Change
,
94
, pp.
187
201
.
14.
Ogawa
,
T.
, and
Kajikawa
,
Y.
,
2015
, “
Assessing the Industrial Opportunity of Academic Research With Patent Relatedness: A Case Study on Polymer Electrolyte Fuel Cells
,”
Technol. Forecasting Soc. Change
,
90
, pp.
469
475
.
15.
Chen
,
L.
,
Kim
,
K.
,
Tang
,
E.
,
Li
,
K.
,
House
,
R.
,
Agogino
,
M. A.
,
Agogino
,
A.
,
Sunspiral
,
V.
, and
Jung
,
E.
,
2016
, “
Soft Spherical Tensegrity Robot Design Using Rod-Centered Actuation and Control
,”
ASME
Paper No. DETC2016-60550.
16.
Bhattacharya
,
S.
, and
Agrawal
,
S. K.
,
2000
, “
Design, Experiments and Motion Planning of a Spherical Rolling Robot
,”
IEEE International Conference on Robotics and Automation
(
ICRA
), San Francisco, CA, Apr. 24–28, pp.
1207
1212
.
17.
Bicchi
,
A.
,
Balluchi
,
A.
,
Prattichizzo
,
D.
, and
Gorelli
,
A.
,
1997
, “
Introducing the ‘SPHERICLE’: An Experimental Testbed for Research and Teaching in Nonholonomy
,”
IEEE International Conference on Robotics and Automation
(
ICRA
), Albuquerque, NM, Apr. 20–25, pp.
2620
2625
.
18.
Bernstei
,
I. H.
, and
Wilson
,
A.
,
2015
, “
Self-Propelled Device With Actively Engaged Drive System
,” Sphero, Inc., Boulder, CO, U.S. Patent No.
9,193,404
.
19.
Kim
,
J.
,
Kwon
,
H.
, and
Lee
,
J.
,
2009
, “
A Rolling Robot: Design and Implementation
,”
Seventh Asian Control Conference
(
ASCC
), Hong Kong, China, Aug. 27–29, pp.
1474
1479
.
20.
Yoon
,
J. C.
,
Ahn
,
S. S.
, and
Lee
,
Y. J.
,
2011
, “
Spherical Robot With New Type of Two-Pendulum Driving Mechanism
,”
15th IEEE International Conference on Intelligent Engineering Systems
(
INES
), Poprad, Slovakia, June 23–25, pp.
275
279
.
21.
Halme
,
A.
,
Suomela
,
J.
,
Schönberg
,
T.
, and
Wang
,
Y.
,
1996
, “
A Spherical Mobile Micro-Robot for Scientific Applications
,”
ESA Workshop on Advanced Space Technologies for Robot Applications
, Noordwijk, The Netherlands, pp. 1–3.
22.
Mukherjee
,
R.
,
Minor
,
M. A.
, and
Pukrushpan
,
J. T.
,
1999
, “
Simple Motion Planning Strategies for Spherobot: A Spherical Mobile Robot
,”
38th IEEE Conference on Decision and Control
(
CDC
), Phoenix, AZ, Dec. 7–10, pp.
2132
2137
.
23.
Hajos
,
G. A.
,
Jones
,
J. A.
,
Behar
,
A.
, and
Dodd
,
M.
,
2005
, “
An Overview of Wind-Driven Rovers for Planetary Exploration
,”
AIAA
Paper No.
2005
-244.
24.
Fujii
,
A.
,
2007
, “
Enhancing Patent Retrieval by Citation Analysis
,”
30th Annual International ACM SIGIR Conference on Research and Development in Information Retrieval
, Amsterdam, The Netherlands, July 23–27, pp.
793
794
.
25.
Wang
,
S. J.
,
2011
, “
The State of Art Patent Search With an Example of Human Vaccines
,”
Hum. Vaccines
,
7
(
2
), pp.
265
268
.
26.
Koch
,
S.
,
Bosch
,
H.
,
Giereth
,
M.
, and
Ertl
,
T.
,
2009
, “
Iterative Integration of Visual Insights During Patent Search and Analysis
,”
IEEE Symposium on Visual Analytics Science and Technology
(
VAST
), Atlantic City, NJ, Oct. 12–13, pp.
203
210
.
27.
Alberts
,
D.
,
Yang
,
C. B.
,
Fobare-DePonio
,
D.
,
Koubek
,
K.
,
Robins
,
S.
,
Rodgers
,
M.
, and
DeMarco
,
D.
,
2011
, “
Introduction to Patent Searching
,”
Current Challenges in Patent Information Retrieval
,
Springer
,
Berlin
, pp.
3
43
.
28.
Benson
,
C. L.
, and
Magee
,
C. L.
,
2015
, “
Technology Structural Implication From the Extension of a Patent Search Method
,”
Scientometrics
,
102
(
3
), pp.
1965
1985
.
29.
D'hondt
,
E.
,
2009
, “
Lexical Issues of a Syntactic Approach to Interactive Patent Retrieval
,”
Third BCSIRSG Symposium on Future Directions in Information Access
, Padua, Italy, Sept. 1, pp.
102
109
.
30.
Takaki
,
T.
,
Fujii
,
A.
, and
Ishikawa
,
T.
,
2004
, “
Associative Document Retrieval by Query Subtopic Analysis and Its Application to Invalidity Patent Search
,”
13th ACM International Conference on Information and Knowledge Management
, Washington, DC, Nov. 8–13, pp.
399
405
.
31.
Xue
,
X.
, and
Croft
,
W. B.
,
2009
, “
Automatic Query Generation for Patent Search
,”
18th ACM Conference on Information and Knowledge Management
, Hong Kong, China, Nov. 2–6, pp.
2037
2040
.
32.
Graf
,
E.
,
Frommholz
,
I.
,
Lalmas
,
M.
, and
Van Rijsbergen, K.
,
2010
, “
Knowledge Modeling in Prior Art Search
,”
Information Retrieval Facility Conference
(
IRFC
), Vienna, Austria, May 31, pp.
31
46
.
33.
Gerken
,
J. M.
, and
Moehrle
,
M. G.
,
2012
, “
A New Instrument for Technology Monitoring: Novelty in Patents Measured by Semantic Patent Analysis
,”
Scientometrics
,
91
(
3
), pp.
645
670
.
34.
Magdy
,
W.
, and
Jones
,
G. J.
,
2010
, “
PRES: A Score Metric for Evaluating Recall-Oriented Information Retrieval Applications
,”
33rd International ACM SIGIR Conference on Research and Development in Information Retrieval
, Geneva, Switzerland, July 19–23, pp.
611
618
.
35.
Chakrabarti
,
A. K.
,
Dror
,
I.
, and
Nopphdol
,
E.
,
1993
, “
Interorganizational Transfer of Knowledge: An Analysis of Patent Citations of a Defense Firm
,”
IEEE Trans. Eng. Manage.
,
40
(
1
), pp.
91
94
.
36.
Alstott
,
J.
,
Triulzi
,
G.
,
Yan
,
B.
, and
Luo
,
J.
,
2017
, “
Mapping Technology Space by Normalizing Patent Networks
,”
Scientometrics
,
110
(
1
), pp.
443
479
.
37.
Yan
,
B.
, and
Luo
,
J.
,
2017
, “
Filtering Patent Maps for Visualization of Diversification Paths of Inventors and Organizations
,”
J. Assoc. Inf. Sci. Technol.
,
68
(
6
), pp.
1551
1563
.
38.
Yan
,
B.
, and
Luo
,
J.
,
2017
, “
Measuring Technological Distance for Patent Mapping
,”
J. Assoc. Inf. Sci. Technol.
,
68
(
2
), pp.
423
437
.
39.
Song
,
B.
,
Triulzi
,
G.
,
Alstott
,
J.
,
Yan
,
B.
, and
Luo
,
J.
,
2016
, “
Overlay Patent Network to Analyze the Design Space of a Technology Domain: The Case of Hybrid Electrical Vehicles
,”
14th International Design Conference
, Cavtat-Dubrovnik, Croatia, May 16–19, pp. 1145–1154.
40.
Weisberg
,
R. W.
,
2006
,
Creativity: Understanding Innovation in Problem Solving, Science, Invention, and the Arts
,
Wiley
,
Hoboken, NJ
.
41.
Uzzi
,
B.
,
Mukherjee
,
S.
,
Stringer
,
M.
, and
Jones
,
B.
,
2013
, “
Atypical Combinations and Scientific Impact
,”
Science
,
342
(
6157
), pp.
468
472
.
42.
Arthur
,
W. B.
,
2007
, “
The Structure of Invention
,”
Res. Policy
,
36
(
2
), pp.
274
287
.
43.
He
,
Y.
, and
Luo
,
J.
,
2016
, “
Novelty, Conventionality, and Value of Innovation
,”
Conference on Design Computing and Cognition
(
DCC
), Evanston, IL, June 27–29, pp. 23–38.
44.
Luo
,
J.
, 2015, “
The United Innovation Process: Integrating Science, Design and Entrepreneurship as Sub-Processes
,”
Des. Sci.
,
1
, p. e2.
45.
Linsey
,
J. S.
,
2007
, “
Design-by-Analogy and Representation in Innovative Engineering Concept Generation
,”
Ph.D. thesis
, University of Texas, Austin, TX.
46.
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
.
47.
Fleming
,
L.
,
2001
, “
Recombinant Uncertainty in Technological Search
,”
Manage. Sci.
,
47
(
1
), pp.
117
132
.
48.
Chan
,
J.
,
Dow
,
S. P.
, and
Schunn
,
C.
,
2015
, “
Do the Best Design Ideas (Really) Come From Conceptually Distant Sources of Inspiration?
,”
Des. Stud.
,
36
, pp.
31
58
.
49.
Fleming
,
L.
, and
Sorenson
,
O.
,
2004
, “
Science as a Map in Technological Search
,”
Strategic Manage. J.
,
25
(
8–9
), pp.
909
928
.
50.
Wilson
,
J. O.
,
Rosen
,
D.
,
Nelson
,
B. A.
, and
Yen
,
J.
,
2010
, “
The Effects of Biological Examples in Idea Generation
,”
Des. Stud.
,
31
(
2
), pp.
169
186
.
51.
Ward
,
T. B.
,
1998
, “
Analogical Distance and Purpose in Creative Thought: Mental Leaps Versus Mental Hops
,”
Advances in Analogy Research: Integration of Theory and Data From the Cognitive, Computational, and Neural Sciences
,
New Bulgarian University
,
Sofia, Bulgaria
.
52.
Tseng
,
I.
,
Moss
,
J.
,
Cagan
,
J.
, and
Kotovsky
,
K.
,
2008
, “
The Role of Timing and Analogical Similarity in the Stimulation of Idea Generation in Design
,”
Des. Stud.
,
29
(
3
), pp.
203
221
.
53.
Gentner
,
D.
, and
Markman
,
A. B.
,
1997
, “
Structure Mapping in Analogy and Similarity
,”
Am. Psychol.
,
52
(
1
), pp.
45
56
.
54.
Stone, R. B.
, and
Wood, K. L.
, 2000, “
Development of a Functional Basis for Design
,”
ASME J. Mech. Des.
,
122
(4), pp. 359–370.
55.
Hirtz
,
J.
,
Stone
,
R. B.
,
McAdams
,
D. A.
,
Szykman
,
S.
, and
Wood
,
K. L.
,
2002
, “
A Functional Basis for Engineering Design: Reconciling and Evolving Previous Efforts
,”
Res. Eng. Des.
,
13
(
2
), pp.
65
82
.
56.
Simpson
,
T. W.
,
Siddique
,
Z.
, and
Jiao
,
R. J.
, eds.,
2006
,
Product Platform and Product Family Design: Methods and Applications
,
Springer Science & Business Media
, Boston, MA.
57.
Simpson
,
T. W.
,
Maier
,
J. R.
, and
Mistree
,
F.
,
2001
, “
Product Platform Design: Method and Application
,”
Res. Eng. Des.
,
13
(
1
), pp.
2
22
.
58.
Ma
,
J.
, and
Kim
,
H. M.
, 2016, “
Product Family Architecture Design With Predictive, Data-Driven Product Family Design Method
,”
Res. Eng. Des.
,
27
(1), pp. 5–21.
59.
Liu
,
Y.
,
Lim
,
S. C. J.
, and
Lee
,
W. B.
,
2013
, “
Product Family Design Through Ontology-Based Faceted Component Analysis, Selection, and Optimization
,”
ASME J. Mech. Des.
,
135
(
8
), p.
081007
.
60.
Ward
,
T. B.
,
2001
, “
Creative Cognition, Conceptual Combination, and the Creative Writing of Stephen R. Donaldson
,”
Am. Psychol.
,
56
(
4
), pp.
350
–354.
61.
Rothenberg
,
A.
,
1980
,
The Emerging Goddess: The Creative Process in Art, Science, and Other Fields
, University of Chicago Press, Chicago, IL.
62.
Gick
,
M. L.
, and
Holyoak
,
K. J.
,
1980
, “
Analogical Problem Solving
,”
Cognit. Psychol.
,
12
(
3
), pp.
306
355
.
63.
Forbus
,
K. D.
,
Gentner
,
D.
, and
Law
,
K.
,
1995
, “
MAC/FAC: A Model of Similarity‐Based Retrieval
,”
Cognit. Sci.
,
19
(
2
), pp.
141
205
.
64.
Stone
,
R. B.
,
Wood
,
K. L.
, and
Crawford
,
R. H.
,
2000
, “
A Heuristic Method for Identifying Modules for Product Architectures
,”
Des. Stud.
,
21
(
1
), pp.
5
31
.
You do not currently have access to this content.