Machine learning-based patent quality metric

Abstract

A machine-learning based artificial intelligence device for finding an estimate of patent quality, such as patent lifetime or term is disclosed. Such a device may receive a first set of patent data and generate a list of binary classifiers. A candidate set of binary classifiers may be selected and using a heuristic search, for example an artificial neural network (ANN), a genetic algorithm, a final set of binary classifiers is found by maximizing iteratively a yield according to a cost function, such an area under a curve (AUC) of a receiver operating characteristic (ROC). The device may then receive patent information for a target patent and report an estimate of patent quality according to the final set of binary classifiers.

What is claimed is: 
     
         1 . A machine-learning based artificial intelligence device for finding an estimate of patent quality, the device comprising:
 a patent data retriever configured to receive a first set of patent data comprising at least one of patent application data and patent data for a plurality of patents, and to generate a list of binary classifiers based on the first set of patent data;   a quantitative data scalar configured to assign a standardized scaled score to each binary classifier of the list of binary classifiers; and   a binary classifier optimizer configured to generate, using an automated processor, a candidate set of binary classifiers from the list of binary classifiers using a heuristic search and to generate, using the automated processor, a final set of binary classifiers by maximizing iteratively a yield according to a cost function,   wherein the device is configured to provide a signal representing the final set of binary classifiers.   
     
     
         2 . The device of  claim 1 , wherein the heuristic search comprises an artificial neural network model. 
     
     
         3 . The device of  claim 2 , wherein the maximizing iteratively comprises changing a number of hidden layers of the artificial neural network. 
     
     
         4 . The device of  claim 1 , wherein the maximizing iteratively comprises using a genetic algorithm. 
     
     
         5 . The device of  claim 1 , wherein the maximizing iteratively comprises using an artificial neural network model and a genetic algorithm. 
     
     
         6 . The device of  claim 1 , wherein the cost function is a receiver operating characteristic and the yield is calculated according an area under a curve. 
     
     
         7 . The device of  claim 1 , wherein the estimate of patent quality represents an estimate of a lifetime of the patent. 
     
     
         8 . The device of  claim 1 , wherein the patent data retriever is configured to receive a second set of patent data comprising at least one of patent application data and patent data for a plurality of patents, and
 wherein the device is configured to test a validity of the final set of binary classifiers using the second set of patent data.   
     
     
         9 . The device of  claim 1 , further comprising a user information manager configured to receive patent information for a target patent and to report the estimate of patent quality according to the final set of binary classifiers. 
     
     
         10 . A system comprising the device of  claim 1  and a second device communicatively connected to the device over a network, the second device comprising:
 a second automated processor: 
 a user interface receiving the patent information for the target patent; 
 an estimate requester requesting from the device the estimate of patent quality for the target patent; and 
 the user interface providing to a user a signal representing the estimate of patent quality.