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Text mining applied to patent mapping: a practical business case

Author

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  • Fattori, Michele
  • Pedrazzi, Giorgio
  • Turra, Roberta

Abstract

Professional patent searchers are traditionally rather suspicious of the alleged "black box" effect inherently attached to intelligent software engines relying upon linguistic technologies for patent analysis and mapping. In this article, the authors propose that such prejudices can be overcome by setting a realistic business objective while experimenting with these new linguistic tools, as well as by applying serious methodology for validating the results of the analysis. The strengths and weaknesses of a particular text mining tool are assessed with reference to a practical business case in the field of packaging technology, and a comparison of the outcome of such an analysis with a traditional one, carried out using conventional patent classifications, is also described.

Suggested Citation

  • Fattori, Michele & Pedrazzi, Giorgio & Turra, Roberta, 2003. "Text mining applied to patent mapping: a practical business case," World Patent Information, Elsevier, vol. 25(4), pages 335-342, December.
    • Handle: RePEc:eee:worpat:v:25:y:2003:i:4:p:335-342
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    Citations

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    Cited by:

    1. Hyundong Nam & Taewoo Nam, 2021. "Exploring Strategic Directions of Pandemic Crisis Management: A Text Analysis of World Economic Forum COVID-19 Reports," Sustainability, MDPI, vol. 13(8), pages 1-19, April.
    2. Altuntas, Serkan & Dereli, Turkay & Kusiak, Andrew, 2015. "Analysis of patent documents with weighted association rules," Technological Forecasting and Social Change, Elsevier, vol. 92(C), pages 249-262.
    3. Curci, Ylenia & Mongeau Ospina, Christian A., 2016. "Investigating biofuels through network analysis," Energy Policy, Elsevier, vol. 97(C), pages 60-72.
    4. Mario Corona & Youngjung Geum & Sungjoo Lee, 2017. "Patterns of Protecting Both Technological and Nontechnological Innovation for Service Offerings: Case of the Video-Game Industry," Service Science, INFORMS, vol. 9(3), pages 192-204, September.
    5. Antonin Bergeaud & Yoann Potiron & Juste Raimbault, 2017. "Classifying patents based on their semantic content," PLOS ONE, Public Library of Science, vol. 12(4), pages 1-22, April.
    6. Munari, Federico & Toschi, Laura, 2014. "Running ahead in the nanotechnology gold rush. Strategic patenting in emerging technologies," Technological Forecasting and Social Change, Elsevier, vol. 83(C), pages 194-207.
    7. Ulas Akkucuk & Mehmet Nafi Artemel, 2016. "Patent Data Visualization: A Regional Study," International Journal of Research in Business and Social Science (2147-4478), Center for the Strategic Studies in Business and Finance, vol. 5(3), pages 66-79, April.
    8. Xi, Xi & Ren, Feifei & Yu, Lean & Yang, Jing, 2023. "Detecting the technology's evolutionary pathway using HiDS-trait-driven tech mining strategy," Technological Forecasting and Social Change, Elsevier, vol. 195(C).
    9. Jia-Yen Huang & Hung-Tu Hsu, 2017. "Technology–function matrix based network analysis of cloud computing," Scientometrics, Springer;Akadémiai Kiadó, vol. 113(1), pages 17-44, October.
    10. A. Fronzetti Colladon & B. Guardabascio & F. Venturini, 2023. "A new mapping of technological interdependence," Papers 2308.00014, arXiv.org, revised Mar 2024.
    11. Chen, Lixin, 2017. "Do patent citations indicate knowledge linkage? The evidence from text similarities between patents and their citations," Journal of Informetrics, Elsevier, vol. 11(1), pages 63-79.
    12. Jaeyoung Kim & Janghyeok Yoon & Eunjeong Park & Sungchul Choi, 2020. "Patent document clustering with deep embeddings," Scientometrics, Springer;Akadémiai Kiadó, vol. 123(2), pages 563-577, May.
    13. Benoit Chevalier, 2020. "Leverage Patent Analytics to Achieve Business-Oriented Objectives: A Pragmatic Approach," Science Governance and Scientometrics Journal, Russian Research Institute of Economics, Politics and Law in Science and Technology (RIEPL), vol. 15(2), pages 120-135, May.
    14. Martin, Hilary & Daim, Tugrul U., 2012. "Technology roadmap development process (TRDP) for the service sector: A conceptual framework," Technology in Society, Elsevier, vol. 34(1), pages 94-105.
    15. Jongchan Kim & Joonhyuck Lee & Gabjo Kim & Sangsung Park & Dongsik Jang, 2016. "A Hybrid Method of Analyzing Patents for Sustainable Technology Management in Humanoid Robot Industry," Sustainability, MDPI, vol. 8(5), pages 1-14, May.
    16. Nadezhda Mikova & Anna Sokolova, 2014. "Selection of information sources for identifying technology trends: A comparative analysis," HSE Working papers WP BRP 25/STI/2014, National Research University Higher School of Economics.

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