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Huberty, Mark
Serwaah, Amma
Zachmann, Georg
Year of Publication: 
Series/Report no.: 
Bruegel Working Paper 2014/10i
This paper reports a new approach to disambiguation of large patent databases. Available international patent databases do not identify unique innovators. Record disambiguation poses a significant barrier to subsequent research. Present methods for overcoming this barrier couple ad-hoc rules for name harmonisation with labourintensive manual checking. We present instead a computational approach that requires minimal and easily automated data cleaning, learns appropriate record-matching criteria from minimal human coding, and dynamically addresses both computational and data-quality issues that have impeded progress. We show that these methods yield accurate results at rates comparable to outcomes from more resource-intensive hand coding.
Document Type: 
Working Paper
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