Integrating Honey-Bee Mating Optimization and Support Vectors Machines for Patent Classification

• Main Authors: Pei-Ting Huang, 黃培婷
• Other Authors: Chui-Yu Chiu
• Format: Others
• Language: zh-TW
• Published: 2010
• Online Access: http://ndltd.ncl.edu.tw/handle/cr79ph

碩士 === 國立臺北科技大學 === 工業工程與管理研究所 === 98 === The patent right has the property of exclusiveness. The inventors can protect their right in the legal range and has monopoly for their open inventions. People are not allowed to use the invention before the inventors permit them to use. Companies try to avoid the research and development investment in the invention that has been protected by patent. Patent retrieval and categorization technologies are used to appear the patent information to reduce the cost of tort. In this research, we propose a novel method which integrates Honey-Bee Mating Optimization with Support Vectors Machines for patent categorization. First, the CKIP method is utilized to extract phrases of the patent summary and title. Then, we calculate the probability that a specific key phrase contains a certain concept based on Term Frequency - Inverse Document Frequency (TF-IDF) methods. By combining frequencies and probabilities of key phases generated from Honey-Bee Mating Optimization, our proposed method is expected to obtain better representative input values for SVM model. Finally, this research uses patents of Chemical Mechanical Polishing (CMP) as case examples to illustrate and demonstrate the proposed methodology at work with superior results.