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| Multi-source Information Fusion Analysis for Emerging Technology Development Trend Identification, Using Blockchain as an Example |
| Zhang Weichong1,2, Wang Fang1,3, Zhao Hong1,2 |
1.Department of Information Resources Management, Business School, Nankai University, Tianjin 300071
2.CEC Data Research Institute Co., Ltd. Guiyang 550081
3.The Center for Network Society Governance, Nankai University, Tianjin 300071 |
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Abstract The scientific literature is constantly being enriched, and has become valuable quantitative analysis data. The information fusion analysis of different sources and different types of scientific and technical literature can provide powerful information support for comprehensively revealing the development status and trends of emerging technologies. The efficient acquisition of topics from multi-source heterogeneous data is a technical difficulty in solving the problem of “subject” measurement entities in multi-source information fusion. This article is aimed at studying seven different scientific and technical literature types: patents, journal articles, dissertations, conference papers, books, funding projects, and industry reports. A summary-based topic analysis method is proposed. The topic words are obtained from multi-source heterogeneous texts, and data fusion and topic association analysis are performed. The results are effective and efficient, which provides a reference for solving the problem. In the experiment, blockchain is taken as an example. Based on data fusion, sequential association analysis and topic association analysis are carried out to reveal the development of blockchain technology. The results show that the method effectively reveals the production process, the theme diffusion, and the evolution trajectory of blockchain technology innovation in the scientific literature.
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Received: 17 May 2019
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