A semantic analysis approach for identifying patent infringement based on a product–patent map

Abstract

Identifying patent infringement beforehand is highly important for reducing the risk of damages. However, as the approach to patents is changing from the technological and legal approaches of the past to the business approach, strategic patent infringement litigation and securement of patents can be important tools for companies. From various viewpoints, companies can consider an aggressive patent infringement litigation as well as evasion strategy of patent infringement litigation to keep competitors in check. Previous research on patent infringement identification only considered the possibility of infringement between patents. However, infringement cases between patent and product are prevalent. Thus, this research aims to suggest an automated method for identifying patent infringement between the patent and product in business. To this end, this paper proposes the subject–action–object (SAO) semantic technological similarity-based product–patent method for generating infringement maps. Several indices and subgrouping methods are suggested to interpret the map. As an exemplary case, data on technology and products related to the light emitting diode (LED) lamp are collected and exploited.

Keywords:

• product–patent map
• patent infringement
• semantic analysis
• subject–action–object (SAO) structure
• social network analysis

Acknowledgements

This work was partially supported by the National Research Foundation of Korea Grant funded by the Korean Government (NRF-2012R1A1A1011934).

Notes on contributors

Byungun Yoon is an Associate Professor in Department of Industrial & Systems Engineering of Dongguk University. His work experience includes an IT consultant in LG and a visiting scholar in the Centre for Technology Management (CTM) of the University of Cambridge. His theme of study has involved patent analysis, new technology development methodology and visualisation algorithms. His current interest is in enhancing technology roadmapping and product designing with data mining techniques. He has authored articles published in Research Policy, R&D Management, Technological Forecasting and Social Change, Technology Analysis & Strategic Management, among others.

Inchae Park is currently a PhD candidate in Department of Industrial & Systems Engineering of the Dongguk University. His theme of study has involved technology forecasting, data mining and patent analysis.