Feature Selection for Cloud Computing Patents Classification

Abstract

Nowadays, many enterprises have considered cloud computing as a seminal technology, and have exploited various types of service models to respond to different customer needs. Patent analysis is an essential ability of survival and development for high technology enterprises. It takes a huge number of patents to support the generation of a business service model of cloud computing. Patent engineers usually fail to collect and analyze patents efficiently due to their large number of professional glossaries and unknown patent classification. This study uses patents in lawsuit as partial important components of pearl patents and proposes a compound retrieval strategy to completely collect the patents of cloud computing. By using text mining as a tool for data processing and keywords extraction, we adopt the technique for order preference by similarity to ideal solution (TOPSIS) to pick out features with high degree of distinguishability for classification. These results establish an important foundation for developing a patent classification system in the future.