2012/06/21 by Péter Érdi, Kinga Makovi, Zoltán Somogyvári +5 · 1 citation
Business, Management and Accounting · Computer Science · Economics, Econometrics and Finance · Physics and Astronomy · #Artificial intelligence #Citation #Cluster (spacecraft) #Cluster analysis #Computer science #Data science #Economic and Technological Innovation #Graph #Innovation and Knowledge Management #Intellectual Property and Patents #Patent analysis #Political science #Representation (politics) #Theoretical computer science #World Wide Web #cs.SI #physics.soc-ph
paper · pdf · doi:10.1007/s11192-012-0796-4
published as Scientometrics: Volume 95, Issue 1 (2013), Page 225-242
openalex publication_date 2012/06/21 · arxiv created 2013/04/04 · arxiv updated 2013/04/05 · openalex created_date 2025/10/10 · openalex updated_date 2026/08/05
The network of patents connected by citations is an evolving graph, which provides a representation of the innovation process. A patent citing another implies that the cited patent reflects a piece of previously existing knowledge that the citing patent builds upon. A methodology presented here (i) identifies actual clusters of patents: i.e. technological branches, and (ii) gives predictions about the temporal changes of the structure of the clusters. A predictor, called the citation vector, is defined for characterizing technological development to show how a patent cited by other patents belongs to various industrial fields. The clustering technique adopted is able to detect the new emerging recombinations, and predicts emerging new technology clusters. The predictive ability of our new method is illustrated on the example of USPTO subcategory 11, Agriculture, Food, Textiles. A cluster of patents is determined based on citation data up to 1991, which shows significant overlap of the class 442 formed at the beginning of 1997. These new tools of predictive analytics could support policy decision making processes in science and technology, and help formulate recommendations for action.