US 2015/0310068 A1Published application

Reinforcement Learning Based Document Coding

AssigneeCatalyst Repository Systems, Inc.

InventorsJeremy Pickens, Bruce Kiefer

Life of this patent

Estimating the term…

Loading patent…

Abstract

Systems and methods for enhanced document analysis and identification through a reinforcement learning framework are provided. A system may employ computer based reinforcement learning to interact with large populations of documents to help users achieve a goal. To accomplish this goal, rewards, value functions, states, policies, and actions may be modeled and various tools within the system can be used to achieve the user's goal. As actions are performed, the results of these actions may be used to update state, assess rewards, and update value functions and policy functions. If the goal is not achieved, the system may make adjustments by adjusting policies, pushing the user closer to their goal by methods of reinforcement learning. Once the goal is achieved, such as a confidence that at least a certain percentage of relevant documents have been identified, relevant documents may be provided to a party desiring the documents.

Claims10

Dependent claims

A method for analyzing and identifying one or more documents of a plurality of documents, comprising:

accessing the plurality of documents;
determining a range of possible actions that may be taken on the plurality of documents;
initializing a reward function based on one or more goals for the analysis and identification of documents, a value function, and a policy function;
selecting a first action of the possible actions to execute on the plurality of documents based on a probability associated with each of the possible actions, the probability associated with each action based on the policy function;
executing the first action on the plurality of documents;
determining a first reward based on executing the first action;
updating the reward function, policy function, and action probabilities based on a first reward;
selecting a second action of the possible actions based on the updated probability associated with each of the remaining possible actions;
and
repeating the executing and updating until the one or more goals are achieved.

7 more elements

Dependencies are inferred from the claim text.