Latent Semantic Analysis Applied to Tech Mining
Name
SSRN-id1356011.pdf
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252.76 KB
Format
Adobe PDF
Checksum (MD5)
2ae1190c7a7413d11138762bb446ae62
Author(s)
Ziegler, Blaine
Woon, Wei Lee
Madnick, Stuart
Date Issued
September 1, 2008
Publisher
Cambridge, MA; Alfred P. Sloan School of Management, Massachusetts Institute of Technology
Series/Report no.
MIT Sloan School of Management Working Paper;4726-09
CISL Working Paper;2008-12
Abstract
This paper presents an approach to bibliometric analysis in the context of technology mining. Bibliometric analysis refers to the use of publication database statistics, e.g., hit counts relevant to a topic of interest. Technology mining facilitates the identification of a technology’s research landscape. Our contribution to bibliometrics in this context is the use of a technique known as Latent Semantic Analysis (LSA) to reveal the concepts that underlie the terms relevant to a field. Using this technique, we can analyze coherent concepts, rather than individual terms. This can lead to more useful results from our bibliometric analysis. We present results that demonstrate the ability of Latent Semantic Analysis to uncover the concepts underlying sets of key terms, used in a case study on the technologies of renewable energy.
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