Overview of the Patent Landscape Process
James H. Moeller - Moeller Ventures LLC - https://www.moellerventures.com/
A patent landscape study is a research process that filters and analyzes patent and patent application information to produce strategic business information that provides overview insights into competitors, technologies, and markets.
The patent landscape process used for Moeller Ventures IP reports utilize data science analytics and semantic analysis for the grouping of similar patents based on feature information, as well as common feature analysis to derive insights. These reports utilize Google's BigQuery cloud-based data warehouse service and the patent datasets provided in BigQuery. This project architecture enables the integration of the analysis into modern data science platforms. The results in Moeller Ventures IP reports have been produced via Python programs executed within Jupyter notebooks that access the BigQuery data warehouse via remote SQL queries.
The diagram below shows the general analysis process. A collection of patent documents is created that represents the intellectual property domain to be analyzed. That collection of patent documents is then further grouped by specific feature information (e.g. assignees, inventors, citations, and class codes). Finally, the feature information is tabulated and analyzed to identify the trends and show insightful results focused on strategic business information such as the competitive landscape, key intellectual property experts, notable prior art, existing patents, and technology profiles.