多源信息融合用于新兴技术发展趋势识别——以区块链为例

Multi-source Information Fusion Analysis for Emerging Technology Development Trend Identification,Using Blockchain as an Example

科技文献不断丰富,成为十分有价值的计量分析数据。对不同来源、不同类型科技文献的信息融合分析,能为全面揭示新兴技术的发展现状及趋势提供有力的情报支撑。从多源异构数据中有效获取主题是多源信息融合中解决"主题"计量实体问题的一项技术难点。本文面向专利、期刊论文、学位论文、会议论文、图书、基金项目、行业报告共7种不同的科技文献类型,提出了基于摘要的主题解析方法,从多源异构文本中获取主题词,并进行数据融合与主题关联分析,在处理效果和效率上都取得不错的效果,为该问题的解决提供了参考。实验部分以区块链为例,在数据融合的基础上分别进行时序性关联分析和主题关联分析,以揭示区块链技术的发展情况。结果显示,本文所提方法有效地揭示了区块链技术创新在科技文献中的产生过程、主题扩散和演化轨迹。

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.