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:
Nov. 10, 2020

Filed:

Jan. 15, 2019
Applicant:

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

Inventors:

Matthew Sprague, Palo Alto, CA (US);

Michael Kross, Palo Alto, CA (US);

Adam Borochoff, New York, NY (US);

Parvathy Menon, Palo Alto, CA (US);

Michael Harris, Palo Alto, CA (US);

Assignee:

Palantir Technologies Inc., Denver, CO (US);

Attorney:
Primary Examiner:
Int. Cl.
CPC ...
G06Q 40/00 (2012.01); H04L 29/06 (2006.01); G06F 16/2457 (2019.01); G06F 16/23 (2019.01); G06F 16/242 (2019.01); G06F 16/28 (2019.01); G06F 16/9535 (2019.01); G06Q 10/10 (2012.01); G06Q 40/02 (2012.01); G06F 16/335 (2019.01); G06F 16/35 (2019.01); G06F 16/26 (2019.01); G06F 16/2458 (2019.01); G06Q 20/40 (2012.01); G06Q 30/00 (2012.01); G06Q 20/38 (2012.01);
U.S. Cl.
CPC ...
H04L 63/145 (2013.01); G06F 16/23 (2019.01); G06F 16/244 (2019.01); G06F 16/2465 (2019.01); G06F 16/24578 (2019.01); G06F 16/26 (2019.01); G06F 16/283 (2019.01); G06F 16/285 (2019.01); G06F 16/287 (2019.01); G06F 16/288 (2019.01); G06F 16/335 (2019.01); G06F 16/35 (2019.01); G06F 16/355 (2019.01); G06F 16/9535 (2019.01); G06Q 10/10 (2013.01); G06Q 20/382 (2013.01); G06Q 20/4016 (2013.01); G06Q 30/0185 (2013.01); G06Q 40/00 (2013.01); G06Q 40/02 (2013.01); G06Q 40/025 (2013.01); G06Q 40/10 (2013.01); G06Q 40/123 (2013.12);
Abstract

Techniques are disclosed for prioritizing a plurality of clusters. Prioritizing clusters may generally include identifying a scoring strategy for prioritizing the plurality of clusters. Each cluster is generated from a seed and stores a collection of data retrieved using the seed. For each cluster, elements of the collection of data stored by the cluster are evaluated according to the scoring strategy and a score is assigned to the cluster based on the evaluation. The clusters may be ranked according to the respective scores assigned to the plurality of clusters. The collection of data stored by each cluster may include financial data evaluated by the scoring strategy for a risk of fraud. The score assigned to each cluster may correspond to an amount at risk.


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