- P-ISSN2287-1608
- E-ISSN2287-1616
- KCI
Identifying Core Robot Technologies by Analyzing Patent Co-classification Information
전정환 (경상대학교)
서용윤 (부경대학교)
고진환 (경상대학교)
이상훈 (한남대학교)
Abstract
This study suggests a new approach for identifying core robot tech-nologies based on technological cross-impact. Specifically, the approach applies data mining techniques and multi-criteria decision-making methods to the co-classification information of registered patents on the robots. First, a cross-impact matrix is constructed with the confidence values by applying association rule mining (ARM) to the co-classification information of patents. Analytic network process (ANP) is applied to the co-classification frequency matrix for deriving weights of each robot technology. Then, a technique for order performance by similarity to ideal solution (TOPSIS) is employed to the derived cross-impact matrix and weights for identifying core robot technologies from the overall cross-impact perspective. It is expected that the proposed approach could help robot technology managers to formulate strategy and policy for technology planning of robot area.
- keywords
- Core robot technology, patent co-classification, cross-impact analysis, association rule mining, analytic network process
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