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Research on the Identification and Analysis of Technological Opportunities Utilizing the BERT Model and MULTIMOORA Approach

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World Conference of AI-Powered Innovation and Inventive Design (TFC 2024)

Part of the book series: IFIP Advances in Information and Communication Technology ((IFIPAICT,volume 735))

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Abstract

Product innovation is considered a crucial component of enhancing corporate competitiveness. Identifying technological opportunities plays a pivotal role in the success of a company’s research and development (R&D) activities. Technological opportunities are defined as the potential for technological advancements in specific areas. Historically, product innovation often relied on identifying singular technological opportunities. However, the current challenge lies in recognizing and leveraging a series of interacting multiple technological opportunities. To address this, our study introduces a novel approach based on the Transformer-based Bidirectional Encoder Representations from Transformers (BERT) model. This method transforms multiple technological objectives into generalized functional behaviors by restructuring them. An in-depth analysis of patent databases is conducted using the semantic search tool from Patsnap, extracting patent information related to these functional requirements. Subsequently, the data undergoes a transition from qualitative to quantitative analysis using spherical fuzzy sets. Finally, the quantified technologies are ranked for opportunities using the MULTIMOORA method, thus completing the identification of single or multiple interacting technological opportunities.

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Correspondence to Jianguang Sun or Runze Miao .

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Sun, J., Miao, R., Du, Y., Zhang, D. (2025). Research on the Identification and Analysis of Technological Opportunities Utilizing the BERT Model and MULTIMOORA Approach. In: Cavallucci, D., Brad, S., Livotov, P. (eds) World Conference of AI-Powered Innovation and Inventive Design. TFC 2024. IFIP Advances in Information and Communication Technology, vol 735. Springer, Cham. https://doi.org/10.1007/978-3-031-75919-2_8

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  • DOI: https://doi.org/10.1007/978-3-031-75919-2_8

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  • Publisher Name: Springer, Cham

  • Print ISBN: 978-3-031-75918-5

  • Online ISBN: 978-3-031-75919-2

  • eBook Packages: Computer ScienceComputer Science (R0)

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