Semantic Distances for Technology Landscape Visualization

32 Pages Posted: 13 Mar 2014

See all articles by Wei Lee Woon

Wei Lee Woon

Masdar Institute of Science and Technology (MIST)

Stuart Madnick

Massachusetts Institute of Technology (MIT) - Sloan School of Management

Multiple version iconThere are 2 versions of this paper

Date Written: November 1, 2011

Abstract

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.

Keywords: Data Mining, Technology Forecasting, Clustering, Semantic Distance

Suggested Citation

Woon, Wei Lee and Madnick, Stuart E., Semantic Distances for Technology Landscape Visualization (November 1, 2011). MIT Sloan Research Paper No. 2011-10. Available at SSRN: https://ssrn.com/abstract=2338582 or http://dx.doi.org/10.2139/ssrn.2338582

Wei Lee Woon

Masdar Institute of Science and Technology (MIST) ( email )

MASDAR
PO Box 54115
Abu Dhabi
United Arab Emirates

Stuart E. Madnick (Contact Author)

Massachusetts Institute of Technology (MIT) - Sloan School of Management ( email )

E53-321
Cambridge, MA 02142
United States
617-253-6671 (Phone)
617-253-3321 (Fax)

Register to save articles to
your library

Register

Paper statistics

Downloads
246
Abstract Views
5,706
rank
80,746
PlumX Metrics