Knowledge Mapping for Nanotechnology
Nanotechnology holds the promise of revolutionizing a wide range of application areas and has been recognized by most countries as critical to a nation's future technology competence. Increased funding and research have generated a growing number of patents and an increase in the amount of literature available. Government interest, funding levels, industry investment, and active research activities have created a greater need to monitor global development of Nanoscale Science and Engineering (NSE) and the R&D status in industry and academic institutions, and to understand the impact of the funding in the NSE field. The research directions of the Artificial Intelligence Lab include:
- Development of the patent analysis framework for worldwide NSE R&D status.
- In-depth grant-patent association analysis to assess the impact of NSF funding and NSF-funded researchers in NSE field.
- Comparative study of the NSE patents issued by multiple patent offices.
- Assessment of NSE research in academia using scientific literature and comparison with industries' efforts as represented by patents.
- Citation network topological analysis for knowledge diffusion trend identification.
- Text mining based methods for research topic identification and topic burst identification.
- Development of an integrated NanoMap system for NSE patent and literature retrieval, analysis, and visualization.
For additional information, see:
- H. Chen and M. Roco. Mapping Nanotechnology Innovations and Knowledge: Global and Longitudinal Patent and Literature Analysis, Berlin: Springer, 2009.
- IEEE Intelligent Systems, Trends & Controversies; with introductions by Dr. Hsinchun Chen (2009)
- AI, E-Government, and Politics 2.0; AI and Global Science and Technology Assessment; and AI for Global Disease Surveillance
This work is supported in part, by the National Science Foundation through the following grants:
- NSF CMMI-1249210."Two Decades of Nanotechnology Development: Global Competitive Landscape and Knowledge Diffusion via ERGM and SIR Analysis" (EAGER)," October 2012-September 2014($298,358)
- NSF CMMI-1057624."Long-term View on Nanotechnology R&D as Reflected in Scientific Papers, Patents, and NSF Awards" (EAGER)." September 2010-August 2013 ($279,522).
- NSF #0926270. "Unveiling Trends in Global Nanotechnology Research and Development" (EAGER)," May 2009 - April 2011 ($250,000).
- NSF #0738803. "SGER: Inter-repository Patent Analysis to Understand Worldwide Nanotechnology Research and Development," December 1, 2007-May 30, 2009 ($100,000).
- NSF #0654232. "Worldwide Nanotechnology Development: A Comparative Study of Global Patents,December 15, 2006 – May 30, 2008 ($100,000).
- NSF #0533749. "NanoMap: Mapping Nanotechnology Development," August 15, 2005-July 31, 2007 ($200,000).
- NSF #0549663. "Mapping Nanotechnology Development Based on the ISI Literature-Citation Database," September 15, 2005-August 31, 2006 ($100,000).
- NSF #0311652. "Intelligent Patent Analysis for Nanoscale Science and Engineering," May 1, 2003-April 30, 2005 ($99,935).
- NSF #0311628. "Intelligent Patent Analysis and Visualization," May 15, 2003-August 31, 2004 ($99,935).
- NSF #0204375. "NanoPort: Intelligent Web Searching for Nanoscale Science and Engineering," January 1, 2002-December 31, 2002 ($99,980).
- NSF #9817473. Digital Library Initiative 2, "High-performance Digital Library Systems: From Information Retrieval to Knowledge Management," April 1999-March 2002 ($500,000).
We are grateful for the funding provided by the National Science Foundation as listed above. Please note that any opinions, findings, and conclusions or recommendations expressed in this material are those of the author(s) and do not necessarily reflect the views of the National Science Foundation. We would also like to acknowledge the generous support provided by Thomson Scientific.
- US Patent and Trademark Office (USPTO) NSE patent data (1976-2008) searched by a domain expert, who provided keywords on: title, abstract, description, claims, and specifications.
- European Patent Office (EPO) NSE patent data (1978-2008) searched by domain expert who provided keywords on title and abstract.
- Japan Patent Office (JPO) NSE patent data (1976-2008) searched by domain expert who provided keywords on title and abstract.
- National Science Foundation (NSF) NSE grant data (1989-2008) searched by domain expert who provided keywords on : grant title, program, and abstract.
- Thomson Science Citation Index Expanded (SCIE) NSE literature data (1976-2007) searched by domain expert who provided keywords on title, paper keywords, and abstract.
- Basic bibliographic analysis on the key indicators of technology development performance
- Content map analysis
1) Using the Arizona Noun Phraser-indexing and Kohonen self-organization map (SOM) algorithm to compare and associate the main topic areas.
2) Longitudinal content map analysis visualizes the change of topic areas in terms of time periods.
- Citation network analysis
1) Network visualization: Graphviz, an open source graph drawing software, provided by AT&T Labs (Gansner and North, 2000) (available at:http://www.research.att.com/sw/tools/graphviz/).
2) Network visualization: NetDraw, a free network drawing program by Steve Borgatti (available at: http://www.analytictech.com/downloadnd.htm)
3) Network topological analysis: Using the social network analysis method to study the patterns in citation networks, the topological measures of the citation networks and their implications.
- Statistical Hypothesis Testing Statistically compare the difference of comparative groups in terms of the publication significance and impact on the field.
- Dr. Hsinchun Chen
- Yan Dang (Mandy)
- Li Fan
- Nina (WanHsin) Huang
- Xin Li
- Daning Hu (Josh)
- Cathy Larson
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- X. Li, H. Chen, Y. Dang, Y. Lin, C. Larson, M. C. Roco, "A longitudinal analysis of nanotechnology literature: 1976-2004," Journal of Nanoparticle Research, Volume 10, Pages 3-22, 2008.
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- Z. Huang, H. Chen, L. Yan, and M. Roco, "Longitudinal nanotechnology development (1991-2002): National Science Foundation funding and its impact on patents", Journal of Nanoparticle Research (JNR), 7, Pages 343-376, (2005).
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- Q. Li, L. Jiang, P. Li, and H. Chen, “Tensor-based Learning for Perceiving Information-driven Stock Movements,” The Twenty-Ninth AAAI Conference on Artificial Intelligence (AAAI-15), Austin, Texas, January 2015.
- S. Jiang S., Q. Gao, and H. Chen, "Statistical Modeling of Nanotechnology Knowledge Diffusion Networks," In Proceedings of the 34th International Conference on Information Systems (ICIS), Milano, Italy, December 15-19, 2013
- S. Kaza and H. Chen, “Effect of Inventor Status on Intra-Organizational Innovation Evolution,” HICSS 2009, Hawaii.