SBIR Phase I: Finding Value in Patent Portfolios Using Co-Citation Analysis

SBIR 第一阶段：使用共引分析发现专利组合的价值

• 批准号: 9661754
• 负责人: Mary Ellen Mogee
• 金额: $ 7.47万
• 依托单位: Mogee Research and Analysis Associates
• 依托单位国家: 美国
• 项目类别: Standard Grant
• 财政年份: 1997
• 资助国家: 美国
• 起止时间: 1997-01-01 至 1997-10-31
• 项目状态: 已结题
• 来源: https://www.nsf.gov/awardsearch/showAward?AWD_ID=9661754&HistoricalAwards=false
• 关键词: SBIR; Phase; Finding; Value; Patent

*** 9661754 Mogee In this Small Business Innovation Research Phase I project, Mogee Research & Analysis Associates will apply co-citation analysis techniques developed in the field of bibliometrics to patent data in an effort to identify patents closely related in terms of subject matter that may represent valuable licensing packages. Co-citation analysis techniques will be used to cluster the U.S. patents assigned to two companies in two different technologies based on citations they have received from U.S. patent examiners, European Patent Office examiners, and patent applicants. The resulting patent clusters will be evaluated by licensing professionals to assess how the clustered patents relate to one another technologically and how valuable the clusters would be as licensing packages. The co-citation clusters will also be compared to clusters generated using other standard search methods such as word searching and classification searching. The goal of this research is to develop a tool that patent licensing professionals can use to group patents into valuable licensing packages more quickly, cheaply, and accurately than they can using current methods. A primary commercial application of this research would be a software tool that could be licensed to companies or other organizations with large patent portfolios or to technology licensing companies. This tool would help them identify potentially valuable clusters of patents within their patent portfolios and help them identify potential licensing partners. ***

* 9661754莫吉 在这个小企业创新研究第一阶段项目中，Mogee Research Analysis Associates将把文献计量学领域开发的共引分析技术应用于专利数据，以识别在主题方面密切相关的专利，这些专利可能代表有价值的许可包。 共同引用分析技术将用于根据美国专利审查员、欧洲专利局审查员和专利申请人的引用，对分配给两家公司的两种不同技术的美国专利进行聚类。 由此产生的专利集群将由许可专业人员进行评估，以评估集群专利在技术上如何相互关联，以及集群作为许可包的价值。 共同引用的聚类也将与使用其他标准搜索方法（如单词搜索和分类搜索）生成的聚类进行比较。 这项研究的目标是开发一种工具，专利许可专业人员可以使用它来将专利分组为有价值的许可包，比使用现有方法更快，更便宜，更准确。 这项研究的主要商业应用将是一个软件工具，可以授权给拥有大量专利组合的公司或其他组织或技术许可公司。 这一工具将帮助他们在其专利组合中发现潜在的有价值的专利集群，并帮助他们找到潜在的许可合作伙伴。 ***