The patent badge is an abbreviated version of the USPTO patent document. The patent badge does contain a link to the full patent document.

The patent badge is an abbreviated version of the USPTO patent document. The patent badge covers the following: Patent number, Date patent was issued, Date patent was filed, Title of the patent, Applicant, Inventor, Assignee, Attorney firm, Primary examiner, Assistant examiner, CPCs, and Abstract. The patent badge does contain a link to the full patent document (in Adobe Acrobat format, aka pdf). To download or print any patent click here.

Date of Patent:
Jul. 21, 2015

Filed:

Sep. 13, 2010
Applicants:

Pankaj Dhoolia, Uttar Pradesh, IN;

Juhnyoung Lee, Yorktown Heights, NY (US);

Debdoot Mukherjee, Kolkata, IN;

Aubrey J. Rembert, Chappaqua, NY (US);

Inventors:

Pankaj Dhoolia, Uttar Pradesh, IN;

Juhnyoung Lee, Yorktown Heights, NY (US);

Debdoot Mukherjee, Kolkata, IN;

Aubrey J. Rembert, Chappaqua, NY (US);

Attorneys:
Primary Examiner:
Assistant Examiner:
Int. Cl.
CPC ...
G06F 9/44 (2006.01); G06K 9/00 (2006.01);
U.S. Cl.
CPC ...
G06K 9/00476 (2013.01); G06F 8/10 (2013.01); G06F 8/20 (2013.01); G06F 8/30 (2013.01);
Abstract

An example embodiment disclosed is a system for automated model extraction of documents containing flow diagrams. An extractor is configured to extract from the flow diagrams flow graphs. The extractor further extracts nodes and edges, and relational, geometric and textual features for the extracted nodes and edges. A classifier is configured to recognize process semantics based on the extracted nodes and edges, and the relational, geometric and textual features of the extracted nodes and edges. A process modeling language code is generated based on the recognized process semantics. Rules to recognize patterns in process diagrams may be determined using supervised learning and/or unsupervised learning. During supervised learning, an expert labels example flow diagrams so that a classifier can derive the classification rules. During unsupervised learning flow diagrams are clustered based on relational, geometric and textual features of nodes and edges.


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