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Measuring textual patent similarity on the basis of combined concepts: design decisions and their consequences

Author

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  • Martin G. Moehrle

    (University of Bremen)

  • Jan M. Gerken

    (University of Bremen)

Abstract

For certain tasks in patent management it makes sense to apply a quantitative measure of textual similarity between patents and/or parts thereof: be it the analysis of freedom to operate, the analysis of technology convergence, or the mapping of patents for strategic purposes. In this paper we intend to outline the process of measuring textual patent similarity on the basis of elements referred to as ‘combined concepts’. We are going to use this process in various operations leading to design decisions, and shall also provide guidance regarding these decisions. By way of two applications from patent management, namely the prioritization of patents and the analysis of convergence between two technological fields, we mean to demonstrate the crucial importance of design decisions in terms of patent analysis results.

Suggested Citation

  • Martin G. Moehrle & Jan M. Gerken, 2012. "Measuring textual patent similarity on the basis of combined concepts: design decisions and their consequences," Scientometrics, Springer;Akadémiai Kiadó, vol. 91(3), pages 805-826, June.
    • Handle: RePEc:spr:scient:v:91:y:2012:i:3:d:10.1007_s11192-012-0682-0
    DOI: 10.1007/s11192-012-0682-0
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    1. Vladimir Batagelj & Matevz Bren, 1995. "Comparing resemblance measures," Journal of Classification, Springer;The Classification Society, vol. 12(1), pages 73-90, March.
    2. Yang, YunYun & Akers, Lucy & Klose, Thomas & Barcelon Yang, Cynthia, 2008. "Text mining and visualization tools - Impressions of emerging capabilities," World Patent Information, Elsevier, vol. 30(4), pages 280-293, December.
    3. Ryley, James F. & Saffer, Jeff & Gibbs, Andy, 2008. "Advanced document retrieval techniques for patent research," World Patent Information, Elsevier, vol. 30(3), pages 238-243, September.
    4. Trippe, Anthony J., 2003. "Patinformatics: Tasks to tools," World Patent Information, Elsevier, vol. 25(3), pages 211-221, September.
    5. Manuel Trajtenberg, 1990. "A Penny for Your Quotes: Patent Citations and the Value of Innovations," RAND Journal of Economics, The RAND Corporation, vol. 21(1), pages 172-187, Spring.
    6. Christian Sternitzke & Isumo Bergmann, 2009. "Similarity measures for document mapping: A comparative study on the level of an individual scientist," Scientometrics, Springer;Akadémiai Kiadó, vol. 78(1), pages 113-130, January.
    7. Martin G. Moehrle, 2010. "Measures for textual patent similarities: a guided way to select appropriate approaches," Scientometrics, Springer;Akadémiai Kiadó, vol. 85(1), pages 95-109, October.
    8. von Wartburg, Iwan & Teichert, Thorsten & Rost, Katja, 2005. "Inventive progress measured by multi-stage patent citation analysis," Research Policy, Elsevier, vol. 34(10), pages 1591-1607, December.
    9. Bonino, Dario & Ciaramella, Alberto & Corno, Fulvio, 2010. "Review of the state-of-the-art in patent information and forthcoming evolutions in intelligent patent informatics," World Patent Information, Elsevier, vol. 32(1), pages 30-38, March.
    10. Wanner, Leo & Baeza-Yates, Ricardo & Brügmann, Sören & Codina, Joan & Diallo, Barrou & Escorsa, Enric & Giereth, Mark & Kompatsiaris, Yiannis & Papadopoulos, Symeon & Pianta, Emanuele & Piella, Gemma , 2008. "Towards content-oriented patent document processing," World Patent Information, Elsevier, vol. 30(1), pages 21-33, March.
    11. Moehrle, Martin G. & Walter, Lothar & Bergmann, Isumo & Bobe, Sebastian & Skrzipale, Svenja, 2010. "Patinformatics as a business process: A guideline through patent research tasks and tools," World Patent Information, Elsevier, vol. 32(4), pages 291-299, December.
    12. Leo Egghe, 2000. "The Distribution of N-Grams," Scientometrics, Springer;Akadémiai Kiadó, vol. 47(2), pages 237-252, February.
    13. Peters, H. P. F. & van Raan, A. F. J., 1993. "Co-word-based science maps of chemical engineering. Part I: Representations by direct multidimensional scaling," Research Policy, Elsevier, vol. 22(1), pages 23-45, February.
    14. Jian Qin, 2000. "Semantic similarities between a keyword database and a controlled vocabulary database: An investigation in the antibiotic resistance literature," Journal of the American Society for Information Science, Association for Information Science & Technology, vol. 51(2), pages 166-180.
    15. Gaetano Cascini & Davide Russo, 2007. "Computer-aided analysis of patents and search for TRIZ contradictions," International Journal of Product Development, Inderscience Enterprises Ltd, vol. 4(1/2), pages 52-67.
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    Citations

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    Cited by:

    1. Ansgar Moeller & Martin G. Moehrle, 2015. "Completing keyword patent search with semantic patent search: introducing a semiautomatic iterative method for patent near search based on semantic similarities," Scientometrics, Springer;Akadémiai Kiadó, vol. 102(1), pages 77-96, January.
    2. Eilers, Kathi & Frischkorn, Jonas & Eppinger, Elisabeth & Walter, Lothar & Moehrle, Martin G., 2019. "Patent-based semantic measurement of one-way and two-way technology convergence: The case of ultraviolet light emitting diodes (UV-LEDs)," Technological Forecasting and Social Change, Elsevier, vol. 140(C), pages 341-353.
    3. Hyunseok Park & Janghyeok Yoon & Kwangsoo Kim, 2013. "Identification and evaluation of corporations for merger and acquisition strategies using patent information and text mining," Scientometrics, Springer;Akadémiai Kiadó, vol. 97(3), pages 883-909, December.
    4. Michael Rennings & Philipp Baaden & Carolin Block & Marcus John & Stefanie Bröring, 2024. "Assessing emerging sustainability-oriented technologies: the case of precision agriculture," Scientometrics, Springer;Akadémiai Kiadó, vol. 129(6), pages 2969-2998, June.
    5. Kuan, Chung-Huei & Chen, Dar-Zen & Huang, Mu-Hsuan, 2019. "Bibliographically coupled patents: Their temporal pattern and combined relevance," Journal of Informetrics, Elsevier, vol. 13(4).
    6. Niemann, Helen & Moehrle, Martin G. & Frischkorn, Jonas, 2017. "Use of a new patent text-mining and visualization method for identifying patenting patterns over time: Concept, method and test application," Technological Forecasting and Social Change, Elsevier, vol. 115(C), pages 210-220.
    7. José Manuel López‐Fernández & Mariluz Maté‐Sánchez‐Val & Francisco Manuel Somohano‐Rodriguez, 2021. "The effect of micro‐territorial networks on industrial small and medium enterprises' innovation: A case study in the Spanish region of Cantabria," Papers in Regional Science, Wiley Blackwell, vol. 100(1), pages 51-77, February.
    8. Moehrle, Martin G. & Caferoglu, Hüseyin, 2019. "Technological speciation as a source for emerging technologies. Using semantic patent analysis for the case of camera technology," Technological Forecasting and Social Change, Elsevier, vol. 146(C), pages 776-784.
    9. Andrew Rodriguez & Byunghoon Kim & Mehmet Turkoz & Jae-Min Lee & Byoung-Youl Coh & Myong K. Jeong, 2015. "New multi-stage similarity measure for calculation of pairwise patent similarity in a patent citation network," Scientometrics, Springer;Akadémiai Kiadó, vol. 103(2), pages 565-581, May.
    10. Eun Han & So Sohn, 2015. "Patent valuation based on text mining and survival analysis," The Journal of Technology Transfer, Springer, vol. 40(5), pages 821-839, October.
    11. Zhu, Chen & Motohashi, Kazuyuki, 2022. "Identifying the technology convergence using patent text information: A graph convolutional networks (GCN)-based approach," Technological Forecasting and Social Change, Elsevier, vol. 176(C).
    12. Lothar Walter & Alfred Radauer & Martin G. Moehrle, 2017. "The beauty of brimstone butterfly: novelty of patents identified by near environment analysis based on text mining," Scientometrics, Springer;Akadémiai Kiadó, vol. 111(1), pages 103-115, April.
    13. Roman Jurowetzki, 2015. "Unpacking Big Systems - Natural Language Processing meets Network Analysis. A Study of Smart Grid Development in Denmark," SPRU Working Paper Series 2015-15, SPRU - Science Policy Research Unit, University of Sussex Business School.
    14. Berg, S. & Wustmans, M. & Bröring, S., 2019. "Identifying first signals of emerging dominance in a technological innovation system: A novel approach based on patents," Technological Forecasting and Social Change, Elsevier, vol. 146(C), pages 706-722.
    15. Moehrle, Martin G. & Frischkorn, Jonas, 2021. "Bridge strongly or focus – An analysis of bridging patents in four application fields of carbon fiber reinforcements," Journal of Informetrics, Elsevier, vol. 15(2).

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    More about this item

    Keywords

    Patent; Similarity measurement; Similarity coefficients; Prior art analysis; Convergence analysis; Patent mapping;
    All these keywords.

    JEL classification:

    • O32 - Economic Development, Innovation, Technological Change, and Growth - - Innovation; Research and Development; Technological Change; Intellectual Property Rights - - - Management of Technological Innovation and R&D
    • O34 - Economic Development, Innovation, Technological Change, and Growth - - Innovation; Research and Development; Technological Change; Intellectual Property Rights - - - Intellectual Property and Intellectual Capital

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