Pimas Oliver, Klampfl Stefan, Kohl Thomas, Kern Roman, Kröll Mark
2016
Generating Tailored Classification Schemas for German Patents
21st International Conference on Applications of Natural Language to Information Systems NLDB 2016 Springer-Verlag Salford, UK
Patents and patent applications are important parts of acompany’s intellectual property. Thus, companies put a lot of effort indesigning and maintaining an internal structure for organizing their ownpatent portfolios, but also in keeping track of competitor’s patent port-folios. Yet, official classification schemas offered by patent offices (i) areoften too coarse and (ii) are not mappable, for instance, to a company’sfunctions, applications, or divisions. In this work, we present a first steptowards generating tailored classification. To automate the generationprocess, we apply key term extraction and topic modelling algorithmsto 2.131 publications of German patent applications. To infer categories,we apply topic modelling to the patent collection. We evaluate the map-ping of the topics found via the Latent Dirichlet Allocation method tothe classes present in the patent collection as assigned by the domainexpert.