The evolution of patent mining: Applying bibliometrics analysis and keyword network analysis

How do funding agencies ramp-up their capabilities to support research in a rapidly emerging area? This paper addresses this question through a comparison of research proposals awarded by the US National Science Foundation (NSF) and the National Natural Science Foundation of China (NSFC) in the field of Big Data. Big data is characterized by its size and difficulties in capturing, curating, managing and processing it in reasonable periods of time. Although Big Data has its legacy in longstanding information technology research, the field grew very rapidly over a short period. We find that the extent of interdisciplinarity is a key aspect in how these funding agencies address the rise of Big Data. Our results show that both agencies have been able to marshal funding to support Big Data research in multiple areas, but the NSF relies to a greater extent on multi-program funding from different fields. We discuss how these interdisciplinary approaches reflect the research hot-spots and innovation pathways in these two countries.

/pdf/how-does-national-scientific-funding-support-emerging-5djpcwiapt.pdf

How Does National Scientific Funding Support Emerging Interdisciplinary Research: A Comparison Study of Big Data Research in the US and China.

According to advances in text mining methods and tools, technology mining, or its brevity ‘tech mining’, is one of recent research areas progressively emerged in technology management area. Over past two decades, this area has been attractive for many scholars in business management, technology management, and computer science departments. The majority of tech mining applications is concentrated on analyzing patents which is also called patent mining by some scholars; moreover, there are some researchers reported tech mining applied to other types of technological documents like RD there is a jump in the number of publications after 2005 and a huge rise in the number of citation after 2012.

`Technology Mining' bibliometrics analysis: applying network analysis and cluster analysis

Patent analysis for generating the technology landscape and competition situation of renewable energy

An assessment of technology forecasting: Revisiting earlier analyses on dye-sensitized solar cells (DSSCs)

‘Tech mining’ is a multistep process for the analysis of science, technology, & innovation (‘ST&I’) information resources. It uses text mining, visualization, and communication tools to provide the empirical knowledge necessary to address management of technology questions. Tech mining can help assess mature or emerging fields of science and technology, such as nanotechnology. Here, we depict select analyses and visualizations of relevant ST&I data on the topics of nanoenhanced, thin-film solar cells and dye-sensitized solar cells. These analyses help identify complementary and competitive research activity, evaluate research productivity, assess research interdisciplinarity, understand nanotechnology developmental trajectories, and identify and forecast promising nanoapplications. © 2011 John Wiley & Sons, Inc. WIREs Data Mining Knowl Discov 2011 1 172-181 DOI: 10.1002/widm.7

Tech mining: Text mining and visualization tools, as applied to nanoenhanced solar cells

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Tech mining: Text mining and visualization tools, as applied to nanoenhanced solar cells