中文摘要：

Patents are critically important for a company to protect its core business concepts and proprietary technologies. Effective patent mining in massive patent databases not only provides business enterprises with valuable insights to develop strategies for research and development, intellectual property management, and product marketing, but also helps patent offices to improve efficiency and optimize their patent examination processes. This paper describes the patent mining problem of automatically discovering core patents (i.e., novel and influential patents in a domain). In addition, the value of core patent mining is illustrated by revealing the potential competitive relationships among companies in their core patents. The work addresses the unique patent vocabulary usage which is not considered in traditional word-based statistical methods with a topic-based temporal mining approach that quantifies a patent’s novelty and influence through topic activeness variations. Tests of this method on real-world patent portfolios show the effectiveness of this approach over state-of-the-art methods.

英文摘要：

Patents are critically important for a company to protect its core business concepts and proprietary technologies. Effective patent mining in massive patent databases not only provides business enterprises with valuable insights to develop strategies for research and development, intellectual property management, and product marketing, but also helps patent offices to improve efficiency and optimize their patent examination processes. This paper describes the patent mining problem of automatically discovering core patents （i.e., novel and influential patents in a domain）. In addition, the value of core patent mining is illustrated by revealing the potential competitive relationships among companies in their core patents. The work addresses the unique patent vocabulary usage which is not considered in traditional word-based statistical methods with a topic-based temporal mining approach that quantifies a patent＇s novelty and influence through topic activeness variations. Tests of this method on real-world patent portfolios show the effectiveness of this approach over state-of-the-art methods.