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:
Jun. 14, 2016

Filed:

Dec. 22, 2014
Applicant:

Palantir Technologies Inc., Palo Alto, CA (US);

Inventors:

Alexander Visbal, New York, NY (US);

James Thompson, San Francisco, CA (US);

Marvin Sum, Sunnyvale, CA (US);

Jason Ma, Mountain View, CA (US);

Bing Jie Fu, Redwood City, CA (US);

Ilya Nepomnyashchiy, Mountain View, CA (US);

Devin Witherspoon, Palo Alto, CA (US);

Vicktoria Lai, Palo Alto, CA (US);

Steven Berler, Menlo Park, CA (US);

Alexei Smaliy, Palo Alto, CA (US);

Suchan Lee, Redwood City, CA (US);

Assignee:

PALANTIR TECHNOLOGIES INC., Palo Alto, CA (US);

Attorney:
Primary Examiner:
Int. Cl.
CPC ...
G06Q 40/00 (2012.01); G06F 12/10 (2016.01); G06F 17/30 (2006.01); G06K 9/62 (2006.01);
U.S. Cl.
CPC ...
G06Q 40/00 (2013.01); G06F 12/1036 (2013.01); G06F 17/30716 (2013.01); G06F 17/30991 (2013.01); G06K 9/6218 (2013.01); G06K 9/6253 (2013.01);
Abstract

Embodiments of the present disclosure relate to a data analysis system that may automatically generate memory-efficient clustered data structures, automatically analyze those clustered data structures, automatically tag and group those clustered data structures, and provide results of the automated analysis and grouping in an optimized way to an analyst. The automated analysis of the clustered data structures (also referred to herein as data clusters) may include an automated application of various criteria or rules so as to generate a tiled display of the groups of related data clusters such that the analyst may quickly and efficiently evaluate the groups of data clusters. In particular, the groups of data clusters may be dynamically re-grouped and/or filtered in an interactive user interface so as to enable an analyst to quickly navigate among information associated with various groups of data clusters and efficiently evaluate those data clusters in the context of, for example, a fraud investigation.


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