Abstract:

The arrival of cyberization and big data era has posed a serious challenge to science and technology intelligence research. It is imperative to innovate the traditional intelligence research methods which give priority to qualitative analysis. Mapping knowledge domains is an information visualization method, which can visualize the structure, relationships and evolutionary process of scientific knowledge based on the analysis to the large sample of academic information (such as journal articles, patent report).In this paper, the general pattern of domestic science and technology intelligence research of “factual database+ special tools+ the wisdom of experts” and the “targetcentric” intelligence analysis process put forth by Robert M. Clark are overviewed. Based on the analysis to the function and boundedness of mapping knowledge domains and to the characteristics of science and technology intelligence research, three application strategies are put forward:multisource data fusion, collaborative use of analysis methods and scientific interpretation of mapping results. Putting the application scenarios of mapping knowledge domains as the breakthrough point, it is suggested that mapping knowledge domains could be applied to four intelligence research processes:topic selection, construction of factual database, intelligence analysis and expert group selection. Based on the discussion above, the optimization model of mapping knowledge domains’ application in science and technology intelligence research is designed. Then the application flow of mapping knowledge domains is put forward. Several integrations are realized through the application model-the integration of quantitative analysis and qualitative analysis, the integration of intelligence personnel and subject experts, mapping knowledge domains and other intelligence research methods, etc. The model lays a foundation for the follow-up application of mapping knowledge domains in science and technology intelligence research.

Key words: Mapping knowledge domains, Science and technology intelligence research, Information visualization, Data mining, Bibliometric analysis, Citation analysis, Co-occurrence analysis