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dc.contributor.authorZiegler, Blaine
dc.contributor.authorWoon, Wei Lee
dc.contributor.authorMadnick, Stuart
dc.date.accessioned2011-09-08T20:39:17Z
dc.date.available2011-09-08T20:39:17Z
dc.date.issued2008-09-01
dc.identifier.urihttp://hdl.handle.net/1721.1/65623
dc.description.abstractThis 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.en_US
dc.language.isoen_USen_US
dc.publisherCambridge, MA; Alfred P. Sloan School of Management, Massachusetts Institute of Technologyen_US
dc.relation.ispartofseriesMIT Sloan School of Management Working Paper;4726-09
dc.relation.ispartofseriesCISL Working Paper;2008-12
dc.titleLatent Semantic Analysis Applied to Tech Miningen_US
dc.typeArticleen_US


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