Technology-oriented national R&D programs produce intellectual property as their final result. Patents, as typical industrial intellectual property, are therefore considered an important factor when evaluating the outcome of R&D programs. Among the main components of patent evaluation, in particular, the patent right quality is a key component constituting patent value, together with marketability and usability. Current approaches for patent right quality evaluation rely mostly on intrinsic knowledge of patent attorneys, and the recent rapid increase of national R&D patents is making expert-based evaluation costly and time-consuming. Therefore, this study defines a hierarchy of patent right quality and then proposes how to quantify the evaluation process of patent right quality by combining text mining and regression analysis. This study will contribute to understanding of the systemic view of the patent right quality evaluation, as well as be an efficient aid for evaluating patents in R&D program assessment processes.

1. Introduction
 2. Groundwork
  2.1 Analytic Hierarchy Process in R&D Management
  2.2 Text Mining in R&D Management
  2.3 Multiple Linear Regression Analysis in R&DManagement
 3. Expert Group
 4. Research Framework
  4.1 Defining a Hierarchy of Patent Right Quality
  4.2 Identifying the Importance of EvaluationFactors in the Patent Right Quality Hierarchy
  4.3 Defining the Variables of Patent RightScope and Strength
  4.4 Extracting Values for the Explanatory Variables
  4.5 Developing Quantitative Models
 5. Evaluating the Patent Right Quality ofIT-Related National R&D Programs
 6. Conclusions and Challenges Remaining
 References

• Janghyeok Yoon(Department of Industrial Engineering, Konkuk University) | 윤장혁
• Jaeguk Song(Department of Economics and Statistics, Korea University) | 송재국
• Tae-Kyu Ryu(Korea Institute of Intellectual Property) | 류태규 Corresponding Author