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. 28, 2014

Filed:

Jun. 29, 2012
Applicants:

David Dietrich, Hopedale, MA (US);

Milind Bhandarkar, San Jose, CA (US);

David Stephen Reiner, Lexington, MA (US);

Inventors:

David Dietrich, Hopedale, MA (US);

Milind Bhandarkar, San Jose, CA (US);

David Stephen Reiner, Lexington, MA (US);

Assignee:

EMC Corporation, Hopkinton, MA (US);

Attorney:
Primary Examiner:
Assistant Examiner:
Int. Cl.
CPC ...
G06K 9/00 (2006.01); G06K 9/62 (2006.01);
U.S. Cl.
CPC ...
G06K 9/6267 (2013.01);
Abstract

Classification of images or other types of high-resolution data is performed by a cluster-based data classification system. The system comprises a learner module, a classification director, and a complex classifier comprising a plurality of multi-outcome data classifiers. The classification director determines particular process rules and settings to be applied to a classification request, and the complex classifier is instantiated to process the classification request in accordance with the process rules and settings determined by the classification director. The process rules and settings are adapted under control of the learner module at least in part based on results obtained in processing the classification request and one or more additional classification requests. The cluster-based data classification system may be implemented on a processing platform comprising at least one Hadoop cluster, such that the classification is performed in a parallel manner across multiple processing devices utilizing MapReduce processing.


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