Journal of Intelligent Information Systems

, Volume 39, Issue 1, pp 29–58 | Cite as

Semantic distances for technology landscape visualization

  • Wei Lee Woon
  • Stuart Madnick


This paper presents a novel approach to the visualization of research domains in science and technology. The proposed methodology is based on the use of bibliometrics; i.e., analysis is conducted using information regarding trends and patterns of publication rather than the actual content. In particular, we explore the use of term co-occurrence frequencies as an indicator of semantic closeness between pairs of terms. To demonstrate the utility of this approach, a number of visualizations are generated for a collection of renewable energy related keywords. As these keywords are regarded as manifestations of the associated research topics, we contend that the proposed visualizations can be interpreted as representations of the underlying technology landscape.


Data mining Technology forecasting Clustering Semantic distance 



We would like to thank the Masdar Institute of Science and Technology (MIST) and the Masdar Initiative for their support of this work.


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Copyright information

© Springer Science+Business Media, LLC 2011

Authors and Affiliations

  1. 1.Computing and Information Science ProgramMasdar Institute of Science and TechnologyAbu DhabiUnited Arab Emirates
  2. 2.Sloan School of ManagementMassachusetts Institute of TechnologyCambridgeUSA

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