Abstract
With the fast pace of technology development and the global nature of competitors in the marketplace, patent management has become an important issue for R&D knowledge management. In this thesis, we develop an integrated framework based on data mining techniques to help companies manage patent documents automatically and effectively. Since patents provide exclusive rights and legal protection for patent inventors, these documents play an important role in the development of technology. Through patent analysis, the companies determine the state of technology development and the degree of competition in the market. This thesis proposes the process of patent knowledge extraction and methodologies of patent analysis to improve the efficiency of patent analysis. Furthermore, the methodologies proposed in this thesis include patent map analysis, patent technology clustering, patent document clustering and technology maturity measurement. Through these methodologies, companies derive rich information and achieve a better patent management. Moreover, the strategic plans of R&D can also be developed with the result of methodologies proposed in this thesis. In this research, the prototype is implemented and patents related to designs of innovative power hand-tools and radio frequency identification technologies are used to demonstrate the results of proposed framework.