Abstract: Information extraction methods for use in extracting values from unstructured documents for predetermined or user-specified attributes into structured databases are provided herein. Methods include (a) automatically training machine learning models for extracting values from unstructured documents such that the values of the attributes are known for those training documents but the locations of the values in the documents are not known, (b) making a sustained connection between structured databases and unstructured documents so that the data across those two types of data stores can be cross-referred by the users any time, (c) a graphical interface specialized for rich user feedback to rapidly adapt and improve the machine learning models.
Type:
Grant
Filed:
December 9, 2016
Date of Patent:
December 31, 2019
Assignee:
AGILE DATA DECISIONS, LLC
Inventors:
Amit Juneja, Jacques Micaelli, Joe Johnston
Abstract: Information extraction methods for use in extracting values from unstructured documents for predetermined or user-specified attributes into structured databases are provided herein. Methods include (a) automatically training machine learning models for extracting values from unstructured documents such that the values of the attributes are known for those training documents but the locations of the values in the documents are not known, (b) making a sustained connection between structured databases and unstructured documents so that the data across those two types of data stores can be cross-referred by the users any time, (c) a graphical interface specialized for rich user feedback to rapidly adapt and improve the machine learning models.
Type:
Application
Filed:
December 9, 2016
Publication date:
June 15, 2017
Applicant:
Agile Data Decisions LLC
Inventors:
Amit Juneja, Jacques Micaelli, Joe Johnston