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| Identification of Key Core Technologies Based on Matrix Profile and Louvain Community Discovery Algorithms |
| Wan Xiaoji1,2, Lai Jing1, Mou Yingxi1, Zhu Zhiguo3, Zhang Liping1 |
1.College of Business Administration, Huaqiao University, Quanzhou 362021
2.Oriental Enterprise Management Research Center, Huaqiao University, Quanzhou 362021
3.School of Management Science and Engineering, Dongbei University of Finance and Economics, Dalian 116025 |
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Abstract Aiming at the problems of existing key core technology identification methods, such as less consideration of the time factor and more difficulty in interpreting the identification results, this study proposes a key core technology identification method based on the matrix profile (MP) and Louvain community detection algorithm. This method is based on International Patent Classification (IPC) subclass weights and word frequency analysis to identify hot technology topics in the target domain. Combining the high-frequency IPC subclass time series and the MP algorithm to construct the technology association network, the Louvain algorithm and social network analysis method are used to identify the initial key core technology topics in the target domain. Based on the features, the key core technology topics are screened, and the key core technologies in the target field are identified through a deep interpretation of the technology association subnetwork, original patent data, relevant policy documents, and journal literature. Through data processing and mining of granted patents in the field of logistics from 2014 to 2023 in the incoPat patent database, this method is noted to effectively identify the key core technologies in the field of logistics that not only helps to promote technological breakthroughs and innovations in the industry but also enhances the country’s position in the global industrial chain and value chain.
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Received: 03 September 2024
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