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A hybrid keyword and patent class methodology for selecting relevant sets of patents for a technological field

Author(s)
Benson, Christopher L.; Magee, Christopher L.
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Creative Commons Attribution-Noncommercial-Share Alike 3.0 http://creativecommons.org/licenses/by-nc-sa/3.0/
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Abstract
This paper presents a relatively simple, objective and repeatable method for selecting sets of patents that are representative of a specific technological domain. The methodology consists of using search terms to locate the most representative international and US patent classes and determines the overlap of those classes to arrive at the final set of patents. Five different technological fields (computed tomography, solar photovoltaics, wind turbines, electric capacitors, electrochemical batteries) are used to test and demonstrate the proposed method. Comparison against traditional keyword searches and individual patent class searches shows that the method presented in this paper can find a set of patents with more relevance and completeness and no more effort than the other two methods. Follow on procedures to potentially improve the relevancy and completeness for specific domains are also defined and demonstrated. The method is compared to an expertly selected set of patents for an economic domain, and is shown to not be a suitable replacement for that particular use case. The paper also considers potential uses for this methodology and the underlying techniques as well as limitations of the methodology.
Date issued
2012-12
URI
http://hdl.handle.net/1721.1/82523
Department
Massachusetts Institute of Technology. Department of Mechanical Engineering; Massachusetts Institute of Technology. Engineering Systems Division
Journal
Scientometrics
Publisher
Springer Science + Business Media B.V.
Citation
Benson, Christopher L., and Christopher L. Magee. “A hybrid keyword and patent class methodology for selecting relevant sets of patents for a technological field.” Scientometrics 96, no. 1 (July 15, 2013): 69-82.
Version: Author's final manuscript
ISSN
0138-9130
1588-2861

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