Filtering Patent Maps for Visualization of Diversification Paths of Inventors and R&D Organizations

Journal of the Association for Information Science and Technology, Forthcoming

30 Pages Posted: 21 Feb 2016 Last revised: 5 Jan 2018

See all articles by Bowen Yan

Bowen Yan

Singapore University of Technology and Design (SUTD)

Jianxi Luo

City University of Hong Kong (CityU)

Date Written: November 14, 2015

Abstract

In the information science literature, recent studies have used patent databases and patent classification information to construct network maps of patent technology classes. In such a patent technology map, almost all pairs of technology classes are connected, whereas most of the connections between them are extremely weak. This observation suggests the possibility of filtering the patent network map by removing weak links. However, removing links may reduce the explanatory power of the network on inventor or organization diversification. The network links may explain the patent portfolio diversification paths of inventors and inventing organizations. We measure the diversification explanatory power of the patent network map, and present a method to objectively choose an optimal trade-off between explanatory power and removing weak links. We show that this method can remove a degree of arbitrariness compared with previous filtering methods based on arbitrary thresholds, and also identify previous filtering methods that created filters outside the optimal trade-off. The filtered map aims to aid in network visualization analyses of the technological diversification of inventors, organizations and other innovation agents, and potential foresight analysis. Such applications to a prolific inventor (Leonard Forbes) and company (Google) are demonstrated.

Keywords: Patent, network, diversification, innovation

Suggested Citation

Yan, Bowen and Luo, Jianxi, Filtering Patent Maps for Visualization of Diversification Paths of Inventors and R&D Organizations (November 14, 2015). Journal of the Association for Information Science and Technology, Forthcoming, Available at SSRN: https://ssrn.com/abstract=2735500 or http://dx.doi.org/10.2139/ssrn.2735500

Bowen Yan

Singapore University of Technology and Design (SUTD) ( email )

20 Dover Drive
Singapore, 138682
Singapore

Jianxi Luo (Contact Author)

City University of Hong Kong (CityU) ( email )

83 Tat Chee Avenue
Kowloon
Hong Kong

HOME PAGE: http://https://www.cityu.edu.hk/stfprofile/jianxiluo.htm

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