[Purpose/Significance] The dual analysis of scientific perspectives and technical attributes serves as an effective pathway for identifying high-value technological opportunities. It holds significant value in accurately grasping the evolution patterns of technology within complex innovation ecosystems and achieving breakthrough innovations. [Method/Process] Starting from the underlying logic of science and the deconstruction of technical attributes, a framework for technological opportunity discovery based on multi-attribute comparison of review articles and patent samples is constructed. First, this study demonstrations on the homogeneity and forward-looking exploratory nature of technological knowledge representation based on review articles and patents. Second, multiple dimensions of technical attributes are defined and technological opportunities are decomposed. Techniques such as text annotation, rule extraction, and LSTM are employed to obtain corpora for different technical attributes. Bertopic is selected for multi-level topic modeling of technical attributes. Finally, by comparing the forward-looking technical themes in review articles with those in patents, correlation indicators and rules for technological opportunity discovery are designed to identify opportunities across different technical attributes. [Result/Conclusion] A case study in the graphene field has verified the validity of a research framework. This framework elaborates on the connotative differences of technological opportunities, allowing for the anticipation of technical trends from the dimensions of functional improvement, performance optimization, and application scenario creation. It adapts to various scenarios such as emerging technology, traditional technology upgrading, and cross-domain integration.
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