| 期刊全稱 | Anticipating Future Innovation Pathways Through Large Data Analysis | | 影響因子2023 | Tugrul U. Daim,Denise Chiavetta,Ozcan Saritas | | 視頻video | http://file.papertrans.cn/159/158500/158500.mp4 | | 發(fā)行地址 | Identifies promising future developmental opportunities and applications for Tech Mining.Presents frontier advances in Science, Technology & Innovation (ST&I) text analytics and other approaches.Combi | | 學(xué)科分類 | Innovation, Technology, and Knowledge Management | | 圖書封面 |  | | 影響因子 | .This book aims to identify promising future developmental opportunities and applications for Tech Mining. Specifically, the enclosed contributions will pursue three converging themes:.The increasing availability of electronic text data resources relating to Science, Technology and Innovation (ST&I)..The multiple methods that are able to treat this data effectively and incorporate means to tap into human expertise and interests..Translating those analyses to provide useful intelligence on likely future developments of particular emerging S&T targets.?.Tech Mining can be defined as text analyses of ST&I information resources to generate Competitive Technical Intelligence (CTI). It combines bibliometrics and advanced text analytic, drawing on specialized knowledge pertaining to ST&I. Tech Mining may also be viewed as a special form of “Big Data” analytics because it searches on a target emerging technology (or key organization) of interest in global databases. One then downloads, typically, thousands of field-structured text records (usually abstracts), and analyses those for useful CTI. ?Forecasting Innovation Pathways (FIP) is a methodology drawing on Tech Mining plus additional st | | Pindex | Book 2016 |
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