Identifying technology opportunity using SAO semantic mining and outlier detection method: A case of triboelectric nanogenerator technology

• Published in: Technological forecasting & social change Vol. 189; p. 122353
• Main Authors: Li, Xin, Wu, Yundi, Cheng, Haolun, Xie, Qianqian, Daim, Tugrul
• Format: Journal Article
• Language: English
• Published: Elsevier Inc 01.04.2023
• Subjects: Outlier detection; Subject-action-object semantic analysis; Technology forecasting; Technology opportunity; Text mining; Triboelectric nanogenerator; Text mining; Triboelectric nanogenerator; Outlier detection; Technology forecasting; Technology opportunity; Subject-action-object semantic analysis
• ISSN: 0040-1625; 1873-5509
• DOI: 10.1016/j.techfore.2023.122353

With the high integration of science and technology development, how to early identify technology opportunity is crucial for the governments’ and enterprises’ research and development (R&D) strategic planning and innovation policy to gain a first-mover advantage in the market competition environment. Most researchers have applied Subject-Action-Object (SAO) semantic mining approach or outlier detection method to mine scientific papers or patent information for identifying technology opportunity. However, few researchers have combined information from both scientific papers and patents to identify technology opportunity by integrating SAO semantic mining and outlier detection method. Therefore, this paper proposes a research framework that uses scientific papers and patents as data resources, and integrates SAO semantic mining and outlier detection method to identify technology opportunity. In this framework, we first use the SAO semantic mining method to mine technical problems and solutions contained in scientific papers and patents respectively. Then we conduct comparative analysis to identify potential technology opportunity in the gaps between scientific papers and patents. Secondly, we use a outlier detection method to identify outlier points in scientific papers, and we incorporate the outlier points into the analysis scope of technology opportunity identification. Finally, we combine the results of SAO semantic mining method with outlier detection method, and use expert knowledge to identify technology opportunity. The triboelectric nanogenerator technology is selected as a case study to verify the feasibility of this framework. The results show that the framework can effectively and comprehensively identify technology opportunity from the two levels of technical problems and technical solutions. This paper contributes to technology opportunity study, and will be of interest to triboelectric nanogenerator technology R&D experts. •A framework to identify technology opportunity using SAO semantic mining and outlier detection method.•Identifying technology opportunities from the two levels of technical problems and technical solutions.•Two analysis results of gaps between science and technology.•Fourteen technology opportunities of triboelectric nanogenerator technology.