# Technology Commercialization Activation Model Using Imagification of Variables
## 2 Related Work
### Technology Transfer Using Patent Analysis  
Technology transfer is intended to increase the success rate of technology commercialization by disseminating the research results to consumers and industries [7; 8; 9]. There are various types of technology transfer, but the transfer of a patent is a common form. Patent-based technology transfer can maximize the cost efficiency and dissemination of research results by transferring R&D results that have already been developed. A technology transfer study using patent analysis was previously conducted [17; 18; 19; 20; 21; 22]. Patent analysis is primarily divided into qualitative and quantitative techniques [30; 31]. In the qualitative technique, the patents are analyzed by experts, whose subjectivity can be seen in the results, and it requires a significant amount of time and money [14]. Solving these problems requires technology transfer research using quantitative, objective techniques [15; 16].  
Such techniques use various information from patent data [17; 18; 19; 20; 21; 22]. [PERSON] et al. extracted quantitative indicators through principal component analysis and the Kaiser-Meier-Olkien test to evaluate the quality of technology-transfer patents. In addition, they constructed a patent-quality evaluation model with a neural network [17]. [PERSON] proposed a model to analyze technology transferability using patent citation information [18]. [PERSON] et al. analyzed the potential functions of patents through text-mining techniques and proposed a model to examine the possibility of technology transfer in various industries [19]. [PERSON] et al. used patents to analyze factors affecting technology transfer [20]. Furthermore, technology transfer characteristics were analyzed by applying social network analysis (SNA) to each institution. These prior studies searched for technology transfer fields and influence factors based on patent analysis. In fact, R&D institutions or technology consumers must focus on things such as marketing by searching for patents with high transfer potential. Therefore, a quantitative model is needed to identify potential technology transfer patents in advance. [PERSON] et al. applied text-mining techniques to structure patents and predicted the possibility of technology transfer through SNA [21]. [PERSON] et al. applied textual information and quantitative indicators to an ensemble model to improve the prediction of technology transfer patents [22]. Previous studies for predicting technology transfer patents have built quantitative models using various patent information, but the patent information used to build the actual model was limited. Furthermore, due to the characteristics of technology transfer, the amount of patent training data was insufficient. This makes it difficult to capture small technology-transfer-related variations in the data, and predictive performance may be poor in certain industries due to the lack of training data. The model proposed in this paper converts patent information into images and effectively searches for information related to technology transfer. Moreover, data augmentation allows it to be used when the training data are sparse.