MACHINE LEARNING SYSTEM FOR A TASK BROKERAGE SYSTEM
First Claim
1. A method in a computing device for learning models for processing documents in a task brokerage system, the method comprising:
- providing demographic information for customers;
providing training data for the customers;
generating models based on the provided training data and demographic information of the customers;
receiving a target document of a customer;
selecting a generated model based on demographic information of the customer;
applying the selected model to the target document to generate a result;
determining refinements to the result made by a provider when generating a refined result; and
adjusting the selected model based on the refinements to the result made by the providerwherein refinements made by providers to results of applying a selected model to a target document are used to adjust the selected model.
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Accused Products
Abstract
A machine learning system learns models to assist providers in processing documents of customers. Providers may use various productivity tools that use the learned models to assist in performing tasks on target documents of customers. The machine learning system may initially train models based on demographic information of customers and training data of the customers. To generate the models, the machine learning system collects the training data for the customers of each cluster and then trains a model for each cluster. The machine learning system uses the models to perform tasks on documents of customers. A provider can then modify the results of the task. The machine learning system can use those modifications to adjust the models.
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Citations
20 Claims
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1. A method in a computing device for learning models for processing documents in a task brokerage system, the method comprising:
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providing demographic information for customers; providing training data for the customers; generating models based on the provided training data and demographic information of the customers; receiving a target document of a customer; selecting a generated model based on demographic information of the customer; applying the selected model to the target document to generate a result; determining refinements to the result made by a provider when generating a refined result; and adjusting the selected model based on the refinements to the result made by the provider wherein refinements made by providers to results of applying a selected model to a target document are used to adjust the selected model. - View Dependent Claims (2, 3, 4, 5, 6, 7, 8, 9, 10, 11, 12, 13)
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14. A computing device for providing models for processing documents of customers in a task brokerage system, comprising:
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a model store containing models for processing documents, the models being learned based on training data and demographic information of customers of the task brokerage system; a component that selects a model for a customer and applies the selected model to a target document of a customer to generate a result; a component that identifies refinements to the result made by a provider when generating a refined result for the result; and a component that adjusts the selected model based on the refinements to the result made by the provider to the result. - View Dependent Claims (15, 16, 17, 18, 19)
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20. A computer-readable storage medium encoded with computer-executable instructions for learning models for processing documents in a task brokerage system, by a method comprising:
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providing demographic information for customers; providing training data for the customers; generating models by identifying clusters of customers based on their demographic information and, for each cluster, training a model based on the training data of the customers within the cluster; for each of a plurality of target documents of customers, receiving the target document of a customer; selecting a generated model based on demographics of the customer; applying the selected model to the target document to generate a result; providing the result to a provider for refinement; and identifying refinements to the result made by the provider; and adjusting the models of the clusters based on the identified refinements made by the providers to the results of target documents of customers of the cluster so that the adjusted models can subsequently be applied to target documents of customers.
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Specification