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.