Identifying Technology Opportunity Using SAO Semantic Mining and Outlier Detection Method: A Case of Triboelectric Nanogenerator Technology
Published In
Technological Forecasting and Social Change
Document Type
Citation
Publication Date
4-1-2023
Abstract
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.
Rights
© 2023 Published by Elsevier Inc
Locate the Document
DOI
10.1016/j.techfore.2023.122353
Persistent Identifier
https://archives.pdx.edu/ds/psu/39614
Citation Details
Li, X., Wu, Y., Cheng, H., Xie, Q., & Daim, T. (2023). Identifying technology opportunity using SAO semantic mining and outlier detection method: A case of triboelectric nanogenerator technology. Technological Forecasting and Social Change, 189, 122353.