Set of MySQL and python scripts to create familiarity indicator by IPC class
Inventor’s familiarity with components of the invention measured by the (a) recent and (b) frequent usage of focal patent’s classes across all US patents. Thus, we calculate a measure of familiarity for each separate class of a focal patent. Therefore, the more recently and frequently a class has been used, its individual measure will be higher.
Based on Fleming 2001 https://funginstitute.berkeley.edu/wp-content/uploads/2012/10/Recombinant-Uncertainty-in-Technological-Search.pdf
The set of scripts allow to create patents familiarity by IPC4 (set A) or IPC4 combination (SET B)
Prerequisites:
NBER data source https://sites.google.com/site/patentdataproject/Home
Patentsview applications table (for applciation date) http://www.patentsview.org/download/ table application
Python version used: 3.5 or above Modules needed: Pandas, sqlalchemy, pymysql:
programs are divided into 3 batches to run strictly in progression by prefix (i.e. A01, A02... )
A builds familiarity by class
B builds familiarity by class comination
C builds DISTANT citation based indicator
A01: SQL script - creates in MySQL the environment and FAMt0 table that is the source for Python programs following.
A02 Python script - creates familiarity by patent / IPC4 - intermediate result
A03 Python script - creates familiarity by company / year - final result
B01 Python script - creates familiarity by patent / IPC4 combination - intermediate result
B02 Python script - creates familiarity by company / year - final result