Comparar métodos
Examine os métodos selecionados lado a lado; as linhas que diferem ficam destacadas.
| Tech Mining× | Science Mapping× | |
|---|---|---|
| Área≠ | Science Technology Studies | Bibliometria |
| Família | Process / pipeline | Process / pipeline |
| Ano de origem≠ | 2005 | 2000s |
| Autor original≠ | Alan L. Porter & Scott W. Cunningham | Katy Börner, Chaomei Chen, and others |
| Tipo≠ | Text-mining methodology for competitive technical intelligence | Method |
| Fonte seminal≠ | 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. DOI ↗ |
| Outros nomes | Technology mining, S&T text mining, Technical intelligence mining | knowledge mapping, domain mapping, research landscape visualization |
| Relacionados≠ | 4 | 5 |
| Resumo≠ | 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. |
| ScholarGateConjunto de dados ↗ |
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