  Patents and scientific papers provide an essential source for measuring
science and technology output, to be used as a basis for the most varied
scientometric analyzes. Authors' and inventors' names are the key identifiers
to carry out these analyses, which however, run up against the issue of
disambiguation. By extension identifying inventors who are also academic
authors is a non-trivial challenge. We propose a method using the International
Patent Classification (IPC) and the IPCCAT API to assess the degree of
similarity of patents and papers abstracts of a given inventor, in order to
match both types of documents. The method is developed and manually qualified
based on three corpora of patents extracted from the international EPO database
Espacenet. Among a set of 4679 patents and 7720 inventors, we obtain 2501
authors. The proposed algorithm solves the general problem of disambiguation
with an error rate lower than 5%.
