Demand identification model of potential technology based on SAO structure semantic analysis: The case of new energy and energy saving fields
| Autor: | Yan-bo Dong, Yu-ying Wu, Xi-jun He, Xue Meng |
|---|---|
| Rok vydání: | 2019 |
| Předmět: |
Decision support system
Wind power Sociology and Political Science business.industry Computer science 020209 energy 05 social sciences Human Factors and Ergonomics 02 engineering and technology Python (programming language) Industrial engineering Education Visualization Supply and demand Semantic similarity 0502 economics and business 0202 electrical engineering electronic engineering information engineering Business and International Management business Cluster analysis computer 050203 business & management computer.programming_language Efficient energy use |
| Zdroj: | Technology in Society. 58:101116 |
| ISSN: | 0160-791X |
| DOI: | 10.1016/j.techsoc.2019.02.002 |
| Popis: | This study proposes an identification model based on subject–action–object (SAO) structure semantic analysis for the potential hotspots of technology demand to address the shortcomings of technology demand mining on the basis of word frequency statistical analysis. The SAO structure is extracted using Python tools to identify the potential hotspots of technology demand, the domain dictionary and professional corpus are introduced, and the clustering of technology demand is realized by applying Word2Vec and HowNet to calculate the semantic similarity among the SAO structures. The layout of the technology demand in the different stages of the technical lifecycle is divided by constructing a technology map. The proposed model is validated as an example of the network technology demand text of the new energy and energy saving fields. Therefore, the hotspots of technology demand are the technology of new energy vehicle motor and its control system, technology of energy efficient and technology of wind power, and the new energy vehicle technology is still in the research and development (R&D) stage. Moreover, solar energy products and production equipment are still in the technical application stage. This study provides an effective method for identifying potential technology demand and based on technology lifecycle to implement the layout and visualization of demand, which will make the decision support for guiding the direction of technology R&D, optimizing the allocation of science and technology resources, and promoting the effective docking of technology supply and demand. |
| Databáze: | OpenAIRE |
| Externí odkaz: |
|
Full Text from ScienceDirect