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:
Oct. 09, 2018

Filed:

Jun. 08, 2015
Applicant:

International Business Machines Corporation, Armonk, NY (US);

Inventors:

Shivali Agarwal, Bangalore, IN;

Arjun R. Akula, Hyderabad, IN;

Gaargi B. Dasgupta, Bangalore, IN;

Shripad J. Nadgowda, Nagpur, IN;

Tapan K. Nayak, New Delhi, IN;

Attorney:
Primary Examiner:
Int. Cl.
CPC ...
G06F 17/30 (2006.01); G06F 7/00 (2006.01); G06N 99/00 (2010.01); G06N 7/00 (2006.01); G06F 17/27 (2006.01);
U.S. Cl.
CPC ...
G06F 17/30705 (2013.01); G06F 17/271 (2013.01); G06F 17/2765 (2013.01); G06F 17/30684 (2013.01); G06N 7/005 (2013.01); G06N 99/005 (2013.01);
Abstract

Methods, systems, and computer program products for structured representation and classification of noisy and unstructured tickets are provided herein. A method includes correlating one or more items of problem incident text data from a given problem incident identifier with items of event text data to generate items of correlated text data within the given problem incident identifier; applying a syntactic grammar to the items of correlated text data to identify in the given problem incident identifier (i) one or more domain-dependent concepts and (ii) one or more domain-independent concepts; parsing noisy and/or unstructured text from the given problem incident identifier based on analysis of (i) the domain-dependent concepts and (ii) the domain-independent concepts; and classifying the given problem incident identifier by classifying features derived from text of the given problem incident identifier subsequent to said parsing of said noisy and/or unstructured text from the given problem incident identifier.


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