Skip to main content
Log in

Predicting product development directions for new product planning using patent classification-based link prediction

  • Published:
Scientometrics Aims and scope Submit manuscript

Abstract

Predicting the possible development directions of a product is useful for planning innovative products. Therefore, a systematic approach based on link prediction is proposed in this study to predict possible development directions of a product. In this approach, a target product is represented as a set of cooperative patent classifications (i.e., product CPCs) contained in the patents related to the product, and the new CPCs identified by link prediction are considered possible directions for product development. The approach analyzes co-occurrences of CPCs in the entire the united states patent and trademark office database to construct a universal CPC network, which contains the technological combination records with high potential of success already tried and qualified through patent registration. Next, it constructs a sub-network of the universal network consisting of the product CPCs and their adjacent CPCs (i.e., candidate CPC) and then creates a product-centered network by introducing an artificial product node, which means the target product itself, to the sub-network. Lastly, applying our link prediction approach, this approach calculates the possibility of entering the product CPCs for all candidate CPCs. Consequently, we can discover possible technical elements that can flow into the target product. To show the workings of the approach, this study applies it to a case of smartphones and validates its performance. We expect that this approach can provide hints on a product’s future development directions and assist experts and firms in establishing strategic product planning or identifying the new functional development of products.

This is a preview of subscription content, log in via an institution to check access.

Access this article

Price excludes VAT (USA)
Tax calculation will be finalised during checkout.

Instant access to the full article PDF.

Fig. 1
Fig. 2
Fig. 3
Fig. 4
Fig. 5
Fig. 6
Fig. 7
Fig. 8
Fig. 9
Fig. 10

Similar content being viewed by others

References

  • Aiello, L. M., Barrat, A., Schifanella, R., Cattuto, C., Markines, B., & Menczer, F. (2012). Friendship prediction and homophily in social media. ACM Transactions on the Web (TWEB), 6(2), 9.

    Google Scholar 

  • Akcora, C. G., Carminati, B., & Ferrari, E. (2011). Network and profile based measures for user similarities on social networks. In 2011 IEEE international conference on information reuse and integration (IRI) (pp. 292–298). IEEE.

  • Ashton, W. B., & Sen, R. K. (1988). Using patent information in technology business planning—I. Research-Technology Management, 31(6), 42–46.

    Google Scholar 

  • Barabâsi, A.-L., Jeong, H., Néda, Z., Ravasz, E., Schubert, A., & Vicsek, T. (2002). Evolution of the social network of scientific collaborations. Physica A: Statistical Mechanics and Its Applications, 311(3–4), 590–614.

    MathSciNet  MATH  Google Scholar 

  • Choi, J., Jeong, B., & Yoon, J. (2019). Technology opportunity discovery under the dynamic change of focus technology fields: Application of sequential pattern mining to patent classifications. Technological Forecasting and Social Change, 148, 119737.

    Google Scholar 

  • Choi, J., Jeong, B., Yoon, J., Coh, B.-Y., & Lee, J.-M. (2020a). A novel approach to evaluating the business potential of intellectual properties: A machine learning-based predictive analysis of patent lifetime. Computers and Industrial Engineering, 145, 106544.

    Google Scholar 

  • Choi, J., Oh, S., Yoon, J., Lee, J.-M., & Coh, B.-Y. (2020b). Identification of time-evolving product opportunities via social media mining. Technological Forecasting and Social Change, 156, 120045.

    Google Scholar 

  • Cohen, J. (1988). Statistical power analysis for the behavioral sciences (2nd ed.). Hillsdale, NJ: Erlbaum.

    MATH  Google Scholar 

  • Fabry, B., Ernst, H., Langholz, J., & Köster, M. (2006). Patent portfolio analysis as a useful tool for identifying R&D and business opportunities—An empirical application in the nutrition and health industry. World Patent Information, 28(3), 215–225.

    Google Scholar 

  • Gerken, J. M., & Moehrle, M. G. (2012). A new instrument for technology monitoring: novelty in patents measured by semantic patent analysis. Scientometrics, 91(3), 645–670.

    Google Scholar 

  • Geum, Y., Jeon, J., & Seol, H. (2013). Identifying technological opportunities using the novelty detection technique: A case of laser technology in semiconductor manufacturing. Technology Analysis & Strategic Management, 25(1), 1–22.

    Google Scholar 

  • Jeong, B., Yoon, J., & Lee, J.-M. (2017). Social media mining for product planning: A product opportunity mining approach based on topic modeling and sentiment analysis. International Journal of Information Management.

  • Jürgens, B., & Herrero-Solana, V. (2017). Monitoring nanotechnology using patent classifications: An overview and comparison of nanotechnology classification schemes. Journal of Nanoparticle Research, 19(4), 151.

    Google Scholar 

  • Katila, R. (2002). New product search over time: Past ideas in their prime? Academy of Management Journal, 45(5), 995–1010.

    Google Scholar 

  • Lee, C., Kang, B., & Shin, J. (2015a). Novelty-focused patent mapping for technology opportunity analysis. Technological Forecasting and Social Change, 90, 355–365.

    Google Scholar 

  • Lee, C., Kwon, O., Kim, M., & Kwon, D. (2018). Early identification of emerging technologies: A machine learning approach using multiple patent indicators. Technological Forecasting and Social Change, 127, 291–303.

    Google Scholar 

  • Lee, S., Lee, S., Seol, H., & Park, Y. (2008). Using patent information for designing new product and technology: Keyword based technology roadmapping. R&d Management, 38(2), 169–188.

    Google Scholar 

  • Lee, W., Han, E., & Sohn, S. (2015b). Predicting the pattern of technology convergence using big-data technology on large-scale triadic patents. Technological Forecasting and Social Change, 100, 317–329.

    Google Scholar 

  • Leydesdorff, L., Kogler, D. F., & Yan, B. (2017). Mapping patent classifications: Portfolio and statistical analysis, and the comparison of strengths and weaknesses. Scientometrics, 112(3), 1573–1591.

    Google Scholar 

  • Liang, Y., & Tan, R. (2007). A text-mining-based patent analysis in product innovative process. Trends in computer aided innovation (pp. 89–96). Berlin: Springer.

    Google Scholar 

  • Liben-Nowell, D., & Kleinberg, J. (2007). The link-prediction problem for social networks. Journal of the American Society for Information Science and Technology, 58(7), 1019–1031.

    Google Scholar 

  • Luo, J., Yan, B., & Wood, K. (2017). Innogps for data-driven exploration of design opportunities and directions: The case of google driverless car project. Journal of Mechanical Design, 139(11), 111416.

    Google Scholar 

  • Ma, J., & Porter, A. L. (2015). Analyzing patent topical information to identify technology pathways and potential opportunities. Scientometrics, 102(1), 811–827.

    Google Scholar 

  • Mandel, M., Petito, C. E., Tutihashi, R., Paiva, W., Abramovicz Mandel, S., Gomes Pinto, F. C., et al. (2018). Smartphone-assisted minimally invasive neurosurgery. Journal of Neurosurgery, 130(1), 90–98.

  • Montecchi, T., Russo, D., & Liu, Y. (2013). Searching in cooperative patent classification: Comparison between keyword and concept-based search. Advanced Engineering Informatics, 27(3), 335–345.

    Google Scholar 

  • Mori, J., Kajikawa, Y., Kashima, H., & Sakata, I. (2012). Machine learning approach for finding business partners and building reciprocal relationships. Expert Systems with Applications, 39(12), 10402–10407.

    Google Scholar 

  • Oliveira, M. G., & Rozenfeld, H. (2010). Integrating technology roadmapping and portfolio management at the front-end of new product development. Technological Forecasting and Social Change, 77(8), 1339–1354.

    Google Scholar 

  • Park, H., Ree, J. J., & Kim, K. (2013). Identification of promising patents for technology transfers using TRIZ evolution trends. Expert Systems with Applications, 40(2), 736–743.

    Google Scholar 

  • Park, H., & Yoon, J. (2014). Assessing coreness and intermediarity of technology sectors using patent co-classification analysis: The case of Korean national R&D. Scientometrics, 98(2), 853–890.

    Google Scholar 

  • Park, Y., & Lee, S. (2011). How to design and utilize online customer center to support new product concept generation. Expert Systems with Applications, 38(8), 10638–10647.

    Google Scholar 

  • Park, Y., & Yoon, J. (2017). Application technology opportunity discovery from technology portfolios: Use of patent classification and collaborative filtering. Technological Forecasting and Social Change, 118, 170–183.

    Google Scholar 

  • Seo, W., Yoon, J., Park, H., Coh, B.-Y., Lee, J.-M., & Kwon, O.-J. (2016). Product opportunity identification based on internal capabilities using text mining and association rule mining. Technological Forecasting and Social Change, 105, 94–104.

    Google Scholar 

  • Shen, X.-X., Tan, K. C., & Xie, M. (2000). An integrated approach to innovative product devselopment using Kano’s model and QFD. European Journal of Innovation Management, 3(2), 91–99.

    Google Scholar 

  • Shibata, N., Kajikawa, Y., Takeda, Y., & Matsushima, K. (2008). Detecting emerging research fronts based on topological measures in citation networks of scientific publications. Technovation, 28(11), 758–775.

    Google Scholar 

  • Song, K., Kim, K. S., & Lee, S. (2017). Discovering new technology opportunities based on patents: Text-mining and F-term analysis. Technovation, 60, 1–14.

    Google Scholar 

  • Spender, J. C., & Grant, R. M. (1996). Knowledge and the firm: Overview. Strategic Management Journal, 17(S2), 5–9.

    Google Scholar 

  • Statista. (2018). Global smartphone shipments from 2009 to 2018. The Statistics Portal. Retrieved February 10, 2018, from https://www.statista.com/statistics/271491/worldwide-shipments-of-smartphones-since-2009/.

  • Su, C.-T., Chen, Y.-H., & Sha, D. (2006). Linking innovative product development with customer knowledge: A data-mining approach. Technovation, 26(7), 784–795.

    Google Scholar 

  • Tang, J., Wu, S., Sun, J., & Su, H. (2012) Cross-domain collaboration recommendation. In Proceedings of the 18th ACM SIGKDD international conference on Knowledge discovery and data mining (pp. 1285–1293). ACM.

  • Tseng, Y.-H., Lin, C.-J., & Lin, Y.-I. (2007). Text mining techniques for patent analysis. Information Processing & Management, 43(5), 1216–1247.

    Google Scholar 

  • Tuarob, S., & Tucker, C. S. (2015). Quantifying product favorability and extracting notable product features using large scale social media data. Journal of Computing and Information Science in Engineering, 15(3), 031003.

    Google Scholar 

  • Wang, P., Xu, B., Wu, Y., & Zhou, X. (2015a). Link prediction in social networks: The state-of-the-art. Science China Information Sciences, 58(1), 1–38.

    Google Scholar 

  • Wang, X., Qiu, P., Zhu, D., Mitkova, L., Lei, M., & Porter, A. L. (2015b). Identification of technology development trends based on subject–action–object analysis: The case of dye-sensitized solar cells. Technological Forecasting and Social Change, 98, 24–46.

    Google Scholar 

  • Wu, S., Sun, J., & Tang, J. (2013). Patent partner recommendation in enterprise social networks. In Proceedings of the 6th ACM international conference on Web search and data mining (pp. 43–52). ACM.

  • Xianjin, Z., & Minghong, C. (2010). Study on early warning of competitive technical intelligence based on the patent map. Journal of Computers, 5(2), 274–281.

    Google Scholar 

  • Yoon, B., & Magee, C. L. (2018). Exploring technology opportunities by visualizing patent information based on generative topographic mapping and link prediction. Technological Forecasting and Social Change, 132, 105–117.

    Google Scholar 

  • Yoon, B., & Park, Y. (2004). A text-mining-based patent network: Analytical tool for high-technology trend. The Journal of High Technology Management Research, 15(1), 37–50.

    MathSciNet  Google Scholar 

  • Yoon, B., & Park, Y. (2007). Development of new technology forecasting algorithm: Hybrid approach for morphology analysis and conjoint analysis of patent information. IEEE Transactions on Engineering Management, 54(3), 588–599.

    Google Scholar 

  • Yoon, J., & Kim, K. (2011). Identifying rapidly evolving technological trends for R&D planning using SAO-based semantic patent networks. Scientometrics, 88(1), 213–228.

    Google Scholar 

  • Yoon, J., & Kim, K. (2012). Detecting signals of new technological opportunities using semantic patent analysis and outlier detection. Scientometrics, 90(2), 445–461.

    Google Scholar 

  • Yoon, J., Kim, M., Kim, D., & Kim, J. (2015a). Monitoring the change of technological impacts of technology sectors using patent information. Industrial Engineering & Management Systems, 14(1), 58–72.

    Google Scholar 

  • Yoon, J., Park, H., Seo, W., Lee, J.-M., Coh, B.-Y., & Kim, J. (2015b). Technology opportunity discovery (TOD) from existing technologies and products: A function-based TOD framework. Technological Forecasting and Social Change, 100, 153–167.

    Google Scholar 

  • Yoon, J., Seo, W., Coh, B.-Y., Song, I., & Lee, J.-M. (2017). Identifying product opportunities using collaborative filtering-based patent analysis. Computers & Industrial Engineering, 107, 376–387.

    Google Scholar 

Download references

Acknowledgements

We feel much appreciation for the editor and anonymous reviewers who provided valuable comments and suggestions on the earlier version of this paper. This paper was supported by Konkuk University in 2018.

Author information

Authors and Affiliations

Authors

Corresponding author

Correspondence to Janghyeok Yoon.

Appendices

Appendix 1: Global smartphone shipments from 2009 to 2018

figure a

Appendix 2: Top 400 candidate CPCs with high inflow possibility in Period 1 and their inflow result

CPC

Inflow possibility

Inflow

CPC

Inflow possibility

Inflow

CPC

Inflow possibility

Inflow

CPC

Inflow possibility

Inflow

H04N9

1.000

Y

Y10T156

0.105

N

B43K23

0.055

N

B81C1

0.031

N

G11B27

0.902

Y

Y10T16

0.104

N

H04L2025

0.055

N

G01S17

0.031

N

H01L21

0.707

Y

H04B10

0.103

Y

C09D11

0.055

N

G05B13

0.031

N

G06F12

0.557

Y

G09G2330

0.103

N

B41J11

0.055

N

H01Q7

0.031

N

H04L45

0.555

N

A61B1

0.102

N

G09B29

0.054

N

B60W2510

0.031

N

H04L1

0.538

N

G05B19

0.102

N

G16H15

0.053

N

B41J15

0.031

N

H01L25

0.517

Y

G02B6

0.098

N

B43K24

0.053

N

H05B37

0.031

Y

H04L2463

0.509

N

G06T15

0.097

Y

E05Y2900

0.053

N

G11B5

0.030

N

G11B20

0.501

N

H04W56

0.095

N

B43K25

0.053

N

G02B13

0.030

N

H04N2005

0.470

N

A61B2017

0.094

N

A63B2230

0.053

N

G03F7

0.030

N

G06T7

0.443

Y

G01N21

0.093

Y

B43K7

0.052

N

E05D11

0.030

N

G11B2220

0.437

N

H04N17

0.093

N

G06F2216

0.052

N

A61F2002

0.030

N

H04W80

0.392

N

B65H29

0.092

N

G09G2354

0.050

N

H05B33

0.030

Y

H05K3

0.382

N

G06F2003

0.091

N

B60R25

0.050

Y

G07G3

0.030

N

H01L27

0.381

Y

B42C9

0.091

N

B42D2035

0.050

N

B60K37

0.030

N

H04L2012

0.371

Y

G09G2300

0.090

N

G10H2240

0.050

N

H01R12

0.029

N

H04B7

0.342

Y

H04B5

0.089

Y

B60L3

0.049

N

F16M13

0.029

Y

G06F15

0.319

N

H03K17

0.089

N

G06T9

0.049

N

B60W50

0.029

N

H01L2225

0.307

Y

H04M19

0.088

N

H04B3

0.049

N

H01H2221

0.029

N

H04W92

0.306

N

A61B2090

0.088

N

Y02B90

0.049

N

G01N27

0.029

N

G06T1

0.299

Y

A61M5

0.088

N

H03K2217

0.049

N

G05F1

0.029

N

G06F2200

0.297

N

B42C19

0.088

N

B60W20

0.048

N

B23K2201

0.029

N

H04W40

0.295

N

H04R1

0.088

Y

F21Y2115

0.047

N

A63F3

0.029

N

G09G2340

0.285

Y

H03L7

0.087

N

A61F2

0.047

N

G01D4

0.029

N

G06F2217

0.260

N

B65H37

0.086

N

F02D41

0.047

N

G05B23

0.029

N

H04L5

0.259

Y

Y02P70

0.086

N

G06Q2220

0.046

N

H03K5

0.028

N

G07C9

0.255

Y

B42P2261

0.085

N

H04L2029

0.046

N

B60W2540

0.028

N

H04M2201

0.243

N

G06T2200

0.084

N

G06T13

0.046

N

Y10T436

0.028

N

A61B2562

0.242

Y

G06Q99

0.084

N

G01S1

0.046

N

G03F1

0.028

N

G09G2370

0.234

Y

H05K5

0.084

N

H04L2027

0.046

N

H01S5

0.028

N

H01L33

0.233

N

H04M17

0.083

N

Y04S10

0.045

N

B60R2325

0.028

N

H04L49

0.232

N

G07F9

0.083

N

A61B18

0.045

N

B82Y10

0.028

N

A61N1

0.225

Y

B60L2240

0.083

N

Y04S40

0.045

N

H03J1

0.028

N

G06F2212

0.225

Y

G08B25

0.083

Y

G08C23

0.044

N

H01M8

0.028

N

B41J2

0.224

N

Y02E60

0.081

N

G09B7

0.044

N

A61B7

0.028

N

G06F2209

0.220

N

G09G2310

0.080

N

H01M4

0.044

N

G08B27

0.028

N

H04M2207

0.218

N

H04K1

0.080

N

Y02D30

0.043

N

Y10S482

0.028

N

Y10T428

0.215

N

G01N33

0.080

Y

Y02E10

0.043

N

B60L2260

0.028

N

G06F2201

0.208

N

G10L13

0.079

N

G11C29

0.043

N

G02B5

0.028

N

B41J3

0.204

N

A61B17

0.078

N

G03B21

0.043

N

H02J2007

0.028

N

H04W74

0.202

N

A63B24

0.078

Y

G01S7

0.043

N

Y10T74

0.027

N

H04N2101

0.200

N

B41J2202

0.077

N

H04K3

0.043

N

G06N7

0.027

N

G09G3

0.200

N

A61M2205

0.077

Y

G01S13

0.042

N

G11B7

0.027

N

G06T11

0.194

Y

G06N99

0.076

N

A61M2230

0.041

N

B33Y80

0.027

N

G16H40

0.192

N

H01H13

0.076

N

H01L28

0.041

N

G09F9

0.027

N

H04M2242

0.189

N

B41J2002

0.075

N

G06N3

0.041

N

H04Q2209

0.027

N

H05K2203

0.185

N

H04J13

0.075

N

B60R11

0.041

N

B60R1

0.027

N

G11B2020

0.183

N

H04B17

0.075

N

Y02B70

0.041

N

H01L51

0.027

N

H04J3

0.178

N

H04L7

0.075

N

B60L15

0.041

N

B60L2270

0.026

N

H04M11

0.173

N

H01M2

0.074

Y

F21K9

0.041

N

G01P15

0.026

N

Y02D50

0.172

N

G06K1

0.074

N

G11B33

0.041

N

H04M2017

0.026

N

G09G2320

0.171

N

G11C7

0.074

N

H04N3

0.041

N

H02J13

0.026

N

G07D7

0.170

N

H04N2007

0.074

N

G06T2210

0.041

N

B60L2220

0.026

N

G16H10

0.169

N

G11C16

0.073

N

H04B2001

0.040

N

B60L2230

0.026

N

A61B2560

0.168

Y

G01R33

0.072

N

H04B2201

0.040

N

H02J2003

0.026

N

H04W68

0.168

N

A61B90

0.072

N

G07C2009

0.039

Y

G07G5

0.026

N

Y02P90

0.164

N

G06Q90

0.071

N

B60W30

0.039

N

A61N5

0.026

N

H04W60

0.162

N

G10L17

0.071

N

C12Q1

0.039

N

G03B15

0.025

N

G02F1

0.161

Y

A61B34

0.071

N

G06T2219

0.039

N

B60K1

0.025

N

G06K2209

0.157

N

H01L31

0.071

N

A61F9

0.039

N

G09B21

0.025

N

G06K15

0.157

N

B42D25

0.071

N

H04J14

0.039

N

H05K13

0.025

N

G06T5

0.157

N

H01R13

0.071

N

H01L2933

0.039

N

G05D1

0.025

N

G07G1

0.156

N

G09B5

0.068

N

G02B2027

0.038

Y

G07B2017

0.025

N

H04Q3

0.156

N

A63B2225

0.068

N

A63F9

0.038

N

B60W2550

0.025

N

G09G2360

0.156

N

G07B15

0.068

N

Y04S50

0.038

N

A63B2244

0.025

N

G06K17

0.153

N

G02F2001

0.068

N

A61B2018

0.038

N

E05D3

0.025

N

H05K7

0.152

N

G03G2215

0.067

N

H04R2499

0.038

N

B60W2710

0.024

N

H04L2001

0.139

N

A63B71

0.066

N

H04R2420

0.037

Y

F28D15

0.024

N

H01L29

0.138

Y

A61B2034

0.065

N

G02B26

0.037

N

H02M3

0.024

N

G08B13

0.137

Y

Y02B60

0.065

N

G08C19

0.037

N

H04J11

0.024

N

G06T3

0.137

N

B82Y30

0.064

N

H03G3

0.037

N

G01S15

0.024

N

G16H50

0.137

N

G10H1

0.064

N

B60L2210

0.037

N

H04N2013

0.024

N

H03M13

0.136

N

G06F2206

0.064

N

H04Q9

0.037

N

G06K2207

0.024

N

H04Q2213

0.136

N

Y10S128

0.064

N

B60L2200

0.037

N

G07B17

0.024

N

H04W16

0.135

N

Y02A90

0.063

N

G01R1

0.037

N

H01Q3

0.024

N

G11B19

0.135

N

G05B15

0.063

Y

B60K2350

0.036

N

G03B27

0.024

N

G06F2211

0.131

N

G07F11

0.063

N

H04M9

0.036

N

G01J1

0.024

N

H04H40

0.130

N

G06T17

0.063

N

G03B13

0.036

N

G11C2207

0.024

N

G06K2009

0.130

N

G10L21

0.063

N

A61M25

0.035

N

H01H2239

0.024

N

G06K2017

0.126

N

G09B19

0.062

N

G01B11

0.035

N

F16M2200

0.024

N

G06T2201

0.126

N

H01L22

0.061

N

G01N2021

0.035

N

G11B31

0.023

N

A61B6

0.126

N

H03M7

0.061

N

B60R16

0.035

N

G06F2207

0.023

N

G08C17

0.126

Y

B60W10

0.061

N

H01H2219

0.035

N

G01C22

0.023

N

G06T19

0.124

Y

B60K6

0.060

N

A63B22

0.035

N

H01Q5

0.023

N

G03G15

0.124

N

G10L2015

0.060

N

F01N3

0.035

N

G07F5

0.023

N

B41J13

0.122

N

G11C5

0.059

N

G10H2220

0.035

N

H01M2250

0.023

N

G10L19

0.121

N

Y10S715

0.059

N

A61B2503

0.035

N

C09K11

0.023

N

Y10T307

0.120

N

Y10S370

0.059

N

H04R3

0.034

Y

A45F2005

0.023

N

H01L2223

0.120

N

G10L25

0.059

Y

G01J3

0.034

Y

B81B7

0.023

N

H01L2221

0.119

N

A63B69

0.058

N

H02J50

0.034

Y

H02J9

0.022

N

G02B27

0.118

Y

H01Q21

0.057

N

A61M2005

0.034

N

B60L1

0.022

N

G06N5

0.117

N

G09G2380

0.057

N

B29C45

0.034

N

G03G21

0.022

N

H04H2201

0.117

N

A63B2071

0.057

N

H03F3

0.033

N

A63F2009

0.022

N

G11C11

0.113

N

A63B2024

0.057

N

B60K35

0.033

N

G08B5

0.022

N

B41J29

0.112

N

G06K2019

0.056

N

H04R5

0.033

N

H04N11

0.022

N

A61B8

0.112

Y

H04Q11

0.056

N

Y04S30

0.033

N

H01H2217

0.022

N

G01R31

0.109

N

B43K29

0.055

N

H04S7

0.032

N

H03F1

0.022

N

G06F7

0.107

N

H03K19

0.055

N

G07D11

0.032

N

A45C2011

0.022

Y

G06F2009

0.107

N

G06F2213

0.055

N

A61M16

0.031

N

G11C8

0.022

N

G03B17

0.105

Y

G02B7

0.055

N

B60L2250

0.031

N

H01H2223

0.022

N

Appendix 3: Top 400 candidate CPCs with high inflow possibility in Period 2

CPC

Inflow possibility

CPC

Inflow possibility

CPC

Inflow possibility

CPC

Inflow possibility

H04L29

1.0000

A61B18

0.1323

A63B2230

0.0713

G09F9

0.0442

H04L47

0.7854

B60K2350

0.1316

B60R2300

0.0711

G09B7

0.0441

H04W28

0.6262

G02B5

0.1314

H04L7

0.0702

H04Q3

0.0437

H04L45

0.5967

G06T13

0.1280

H04Q2209

0.0700

G11C13

0.0434

H04W36

0.5475

Y02D50

0.1259

E05Y2900

0.0695

G16H15

0.0432

H05K1

0.5429

A63B71

0.1253

H03M7

0.0684

G01C22

0.0431

H04L1

0.5119

G09B5

0.1249

G06F2206

0.0684

H04R2460

0.0427

H01L33

0.5059

H03M13

0.1234

H02M3

0.0676

H01M2010

0.0426

G09G3

0.4809

G11C5

0.1230

H04R2430

0.0667

H04Q2213

0.0425

G06T3

0.4524

G02B7

0.1216

G02B26

0.0666

A61N7

0.0420

G06F2009

0.4347

Y02P70

0.1197

B25J9

0.0665

G06F5

0.0419

G06F2201

0.4343

A61B2018

0.1185

B60R11

0.0660

G02B23

0.0418

H05K2201

0.4263

G02B13

0.1177

B60W10

0.0660

B82Y10

0.0418

G06F15

0.4154

A61B2576

0.1173

A61M2005

0.0659

H04N2213

0.0413

H05K3

0.4057

H04M2242

0.1173

A61M16

0.0657

G01S3

0.0413

G06T5

0.3841

G06T2219

0.1163

H04B3

0.0652

B01L3

0.0412

H04N2005

0.3607

G10L17

0.1159

B81B7

0.0651

B41J3

0.0409

Y02B60

0.3527

H04J11

0.1149

H04R2201

0.0647

B23K1

0.0408

H04L2463

0.3398

G10L21

0.1139

G06F2213

0.0645

H04N2007

0.0408

H04H20

0.3252

B60W30

0.1122

G01J5

0.0645

G09G2358

0.0406

H04W40

0.3171

A63B2225

0.1114

A61N5

0.0635

G09G2356

0.0405

H04M7

0.3039

F21Y2115

0.1109

G08C23

0.0630

G11B19

0.0405

G06F2200

0.2988

G06N7

0.1098

B60L2250

0.0624

A61N2005

0.0405

G06N5

0.2974

G01N2021

0.1097

Y10S901

0.0623

H01L45

0.0402

G09G2320

0.2939

G06F2211

0.1085

H01Q9

0.0623

G09C1

0.0402

H04W68

0.2916

H04M11

0.1080

H01H13

0.0621

B60Q9

0.0399

G06K2009

0.2865

H04N17

0.1077

B29D11

0.0617

A63F2009

0.0398

G16H40

0.2834

G01S7

0.1072

A61M1

0.0616

H02J13

0.0391

H04L27

0.2820

H04M2215

0.1062

G07G1

0.0614

Y02D30

0.0390

H05K7

0.2811

H01M2220

0.1061

B60L2210

0.0611

H01J37

0.0390

A61B6

0.2793

H04R2499

0.1033

F21V23

0.0608

Y02A90

0.0389

G06K15

0.2792

H02J2007

0.1031

G05B13

0.0608

B32B37

0.0389

G09G2354

0.2732

B60W2540

0.1004

G05F1

0.0605

G03F1

0.0388

G06T2200

0.2716

G11B2220

0.1003

E05D3

0.0601

G01D5

0.0387

H04W16

0.2705

G06F2003

0.1001

G08B17

0.0583

F02D41

0.0386

H01L2221

0.2628

A63B2024

0.0998

H01Q21

0.0583

B01L2300

0.0384

H04W74

0.2614

H04R27

0.0996

Y02B20

0.0581

G05B23

0.0384

H01L2223

0.2581

H05K13

0.0995

H05K999

0.0571

G01N2333

0.0384

G09G2300

0.2539

B60K37

0.0991

G06T9

0.0569

B81B2207

0.0382

G06K2209

0.2471

H04B2001

0.0991

A61B10

0.0566

G06T2201

0.0381

H04L49

0.2261

Y02E10

0.0991

G07F19

0.0565

F21V29

0.0381

G06N99

0.2260

G05D23

0.0990

H03F2200

0.0560

B81C2203

0.0378

H05K5

0.2234

A61F2

0.0985

Y04S10

0.0560

G03B15

0.0375

G09G2330

0.2234

Y02P90

0.0977

B60L15

0.0558

B23K2201

0.0374

H04W60

0.2208

H04N2101

0.0976

G01J1

0.0556

A63B21

0.0374

G16H50

0.2206

H04Q9

0.0967

H02J17

0.0555

G03B3

0.0374

H04W80

0.2197

H04R2227

0.0960

H01L2251

0.0554

B41J29

0.0373

Y10S707

0.2185

Y10T307

0.0945

B41J2

0.0553

G01J2005

0.0373

H04W56

0.2138

H03K2217

0.0942

A61F2002

0.0553

H03M1

0.0372

H04W92

0.2095

B60R1

0.0930

B60L2230

0.0550

A61M2016

0.0371

G02B6

0.2069

G01S17

0.0926

H04L2001

0.0545

B60L2270

0.0370

G09G2360

0.2069

A63B2071

0.0921

G03B13

0.0540

G01S11

0.0370

G05D1

0.2048

G03G15

0.0918

H03F1

0.0539

H04M17

0.0369

G06F2209

0.2037

G08B29

0.0917

G02B3

0.0538

G04G21

0.0367

A61B2090

0.2006

H01M4

0.0916

G01R27

0.0537

H03K3

0.0364

H01L22

0.1981

A61M2230

0.0915

G09G1

0.0533

H01Q3

0.0363

G02F2001

0.1933

A61B2503

0.0911

A61B7

0.0531

B60W20

0.0362

A61B2017

0.1895

H04M2207

0.0908

H04B15

0.0525

B60K6

0.0359

G11C11

0.1880

G01N27

0.0903

G01S1

0.0524

G08B3

0.0358

G06F2217

0.1878

F21K9

0.0899

G01P15

0.0522

H03L7

0.0357

G11B20

0.1865

G10L19

0.0895

B82Y30

0.0521

G01B9

0.0357

H04B17

0.1865

H03G3

0.0888

B60L2200

0.0521

G02C11

0.0357

G01R31

0.1860

B60W2040

0.0887

A61M2025

0.0521

H04S2400

0.0354

G11C7

0.1834

B60L3

0.0885

A61B2505

0.0518

G07F11

0.0353

G11C16

0.1824

G11B2020

0.0875

G02B21

0.0515

G11B5

0.0350

G06T2210

0.1801

B60Q1

0.0867

G10H1

0.0512

H01F27

0.0349

A61B34

0.1776

H04N2013

0.0855

G11C2029

0.0510

G08B27

0.0347

G16H10

0.1771

H04M19

0.0854

Y04S20

0.0509

G10H2220

0.0346

A61B1

0.1766

G08C19

0.0843

A63F9

0.0507

B60L7

0.0344

H04L25

0.1766

G06Q2220

0.0841

G01S15

0.0506

B60W2710

0.0341

G05B19

0.1762

A61M25

0.0840

A63B22

0.0505

Y04S50

0.0341

H01L31

0.1745

G03B21

0.0837

A45C11

0.0503

Y10S903

0.0339

G06T17

0.1742

G01S13

0.0827

B60R21

0.0499

G03B2205

0.0339

H03K17

0.1717

G10L13

0.0827

H04H40

0.0499

G01T1

0.0338

A61M5

0.1710

H04R5

0.0826

H01Q7

0.0497

H04L2025

0.0337

Y02E60

0.1706

Y10T16

0.0825

G06T2215

0.0496

G10H2240

0.0335

A61B17

0.1702

B60W2550

0.0814

H01S5

0.0495

B29L2031

0.0334

Y10T428

0.1675

H04R29

0.0809

G01L1

0.0494

H01B1

0.0331

B60R16

0.1659

G01N2201

0.0803

B81B2201

0.0488

H05K9

0.0330

H04M2201

0.1651

G08B5

0.0799

B60L2260

0.0486

B60R7

0.0329

B60W50

0.1629

H01R13

0.0795

G06G1

0.0483

H03K2017

0.0328

G01R33

0.1619

G06N3

0.0790

G08G5

0.0483

Y10T436

0.0328

G07F7

0.1612

H03K19

0.0788

B60L1

0.0482

B64C39

0.0327

G09G2380

0.1609

A63B69

0.0781

Y02B70

0.0482

Y02B90

0.0325

H01L2933

0.1607

B81C1

0.0779

H01F38

0.0480

H04J13

0.0325

A61B2034

0.1588

G03F7

0.0774

G07C2209

0.0480

B32B2307

0.0324

B60K35

0.1558

G06Q90

0.0762

H02M7

0.0476

A61F5

0.0324

H01L28

0.1541

H02J5

0.0761

G09B21

0.0475

G01N2800

0.0322

H05K2203

0.1537

H04H2201

0.0760

G09G2350

0.0474

F21Y2105

0.0322

G10L2015

0.1530

G09B29

0.0751

F21Y2101

0.0472

H04Q11

0.0321

G09B19

0.1525

C12Q1

0.0751

Y04S40

0.0467

H02J2003

0.0319

A61B90

0.1458

G08B6

0.0749

G01K13

0.0467

G03B37

0.0315

G01B11

0.1444

A61F9

0.0742

G05D2201

0.0463

G01D4

0.0311

H01L51

0.1442

Y10T156

0.0733

C09K11

0.0460

G07F9

0.0310

B60L2240

0.1427

H03F3

0.0732

B32B2457

0.0456

H03H7

0.0310

G06F7

0.1427

G02F2201

0.0729

H01L41

0.0456

B64C2201

0.0309

B60W40

0.1390

H04S7

0.0723

G07B15

0.0456

C23C14

0.0309

H04J3

0.1381

H02J3

0.0720

G11C8

0.0453

G01B21

0.0307

G09G2310

0.1361

Y04S30

0.0719

C23C16

0.0450

B60L2220

0.0304

G11C29

0.1346

B60W2050

0.0713

H04R2225

0.0443

B82Y40

0.0304

Rights and permissions

Reprints and permissions

About this article

Check for updates. Verify currency and authenticity via CrossMark

Cite this article

Oh, S., Choi, J., Ko, N. et al. Predicting product development directions for new product planning using patent classification-based link prediction. Scientometrics 125, 1833–1876 (2020). https://doi.org/10.1007/s11192-020-03709-w

Download citation

  • Received:

  • Accepted:

  • Published:

  • Issue Date:

  • DOI: https://doi.org/10.1007/s11192-020-03709-w

Keywords

Navigation