This paper proposes a new method for decomposing a technological domain (TD). Specifically, the method identifies sub-TDs at the different levels of technological hierarchy within the TD based on the characteristics of patent co-classification and classification hierarchy. We defined the smallest class, named Minimum Overlapped Class (MOC), constructed by overlaps of sub-group IPC(s) and sub-class UPC(s), and sub-TD is basically identified as a set of the MOCs. In order to cluster the MOCs, technological distances among MOCs are calculated based on patent co-classification and hierarchical structure of patent classification systems. Technologically similar MOCs are grouped by using a hierarchical clustering and the identified clusters at the different level of hierarchy show the hierarchical structure of a TD. Detailed technological content for each sub-TD is represented by extracting representative keywords through a text-mining technique. The method is empirically tested by the solar photovoltaic technology and the results show that the identified sub-TDs are reasonably acceptable by qualitative analysis.
Purpose
The purpose of this paper is to propose a quantitative method for identifying multiple and hierarchical knowledge trajectories within a specific technological domain (TD).
Design/methodology/approach
The proposed method as a patent-based data-driven approach is basically based on patent classification systems and patent citation information. Specifically, the method first analyzes hierarchical structure under a specific TD based on patent co-classification and hierarchical relationships between patent classifications. Then, main paths for each sub-TD and overall-TD are generated by knowledge persistence-based main path approach. The all generated main paths at different level are integrated into the hierarchical main paths.
Findings
This paper conducted an empirical analysis by using Genome sequencing technology. The results show that the proposed method automatically identifies three sub-TDs, which are major functionalities in the TD, and generates the hierarchical main paths. The generated main paths show knowledge flows across different sub-TDs and the changing trends in dominant sub-TD over time.
Originality/value
To the best of the authors’ knowledge, the proposed method is the first attempt to automatically generate multiple hierarchical main paths using patent data. The generated main paths objectively show not only knowledge trajectories for each sub-TD but also interactive knowledge flows among sub-TDs. Therefore, the method is definitely helpful to reduce manual work for TD decomposition and useful to understand major trajectories for TD.
In an industry, society gets more interest in software. In accordance with this trend, in the process of composing the university's curriculum, it is increasingly emphasized that problem-based learning through computational thinking and programming ability based on logical thinking is weighted. This study conducted a study on how to identify students' educational characteristics and study intention. In particular, a methodology to explore the study intention for Python programming from the characteristics of each student was reviewed. For this analysis, the relationship between new technology from their point of view and factors is analyzed, factors are identified for methodologies, and statistical methodologies are used to verify them. The purpose of this study is to find improvements for software education operation and to provide help in educational policy decision-making of university members who conduct computer software education.
scite is a Brooklyn-based organization that helps researchers better discover and understand research articles through Smart Citations–citations that display the context of the citation and describe whether the article provides supporting or contrasting evidence. scite is used by students and researchers from around the world and is funded in part by the National Science Foundation and the National Institute on Drug Abuse of the National Institutes of Health.