Florent MATHIEU, Chemical Process Engineer, R&D, Michelin
Technology intelligence, especially patent intelligence, is a crucial step in the development of new technologies or new processes. This task is often tedious because it requires reading many patents. JMP Pro's text exploration and predictive modeling tools facilitate patent intelligence. First, patents must be identified as critical for a corpus of patents. The patent title, summary, and claims are analyzed with JMP's Text Explorer to associate each patent with a vector representing its lexical field (the Document Term Matrix). Next, a predictive modeling tool, such as neural networks, is used to predict the probability that a patent is critical. Once the machine learning is complete, it is possible to identify, in a fraction of a second, the relevant patents to be read within an extended patent corpus. Once implemented, this methodology accelerates the patent intelligence process, broadens the search scope and limits the risk of missing critical patents. This presentation demonstrates the process of developing this methodology for patent intelligence.
