Human IP experts combine deep technological background knowledge with patent law expertise to act as patent finders and decision makers, not just as patent searchers. By comparison, a modern artificial intelligence is rarely much more than an uneducated child with enormous computing power and endless data storage. The key to next-generation high-quality knowledge extraction lies in combining the two approaches.
EconSight has created a taxonomy of more than 500 technologies that have been gathered, vetted, and selected by human experts with more than 20 years of patent research experience. EconSight’s proprietary AI algorithms are similarly designed to read, understand, and categorize the 130+ million patent documents at the text level and in their technological context. By combining these two worlds, we can find the missing text fragments or long sought documents that the traditional human searcher may have missed. Huge patent landscapes with more than 100’000 patent families can be structured, clustered and categorized into content-separated segments, fully multilabel and purely text-based. Our 3D cluster analysis calculates dynamics, size and conceptual distance from the main field concept to find and identify the most promising segments in large fields: Fully explicable AI down to the single patent and most likely owner.