Сравнение методов

	Tech Mining	Картографирование науки (Science Mapping)
Область	Science Technology Studies	Библиометрия
Семейство	Process / pipeline	Process / pipeline
Год появления	2005	2000s
Автор метода	Alan L. Porter & Scott W. Cunningham	Katy Börner, Chaomei Chen, and others
Тип	Text-mining methodology for competitive technical intelligence	Method
Основополагающий источник	Porter, A. L., & Cunningham, S. W. (2005). Tech Mining: Exploiting New Technologies for Competitive Advantage. Wiley. ISBN: 9780471475675	Börner, K., Chen, C., & Boyack, K. W. (2003). Visualizing knowledge domains. Annual Review of Information Science and Technology, 37, 179–255.
Другие названия	Technology mining, S&T text mining, Technical intelligence mining	knowledge mapping, domain mapping, research landscape visualization
Связанные	4	5
Сводка	Tech mining is the text mining of science and technology information—the publication, patent, and proposal databases that record the world's research and invention—to extract competitive technical intelligence. Coined by Alan Porter and Scott Cunningham, it turns large, fielded bibliographic corpora into actionable answers about who is doing what, where, with whom, and along which trajectories. By extracting entities such as authors, institutions, countries, keywords, and assignees and analysing their co-occurrence over time, tech mining profiles emerging technologies, maps research landscapes, and supports R&D management and innovation policy decisions.	Science mapping is a bibliometric visualization method that creates visual representations of research domains, showing the structure, development, and relationships of scientific fields. Using bibliographic data (citations, keywords, authors, journals), science mapping algorithms generate network diagrams where nodes represent documents, concepts, or authors and edges represent relationships (citation, collaboration, semantic similarity). The resulting maps make invisible intellectual structures visible, enabling researchers to understand field topology, identify emerging areas, and navigate disciplinary landscapes. Pioneered by Börner, Chen, and Boyack in the 2000s, science mapping has become a standard tool in research evaluation and strategic planning.