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:
Apr. 16, 2024

Filed:

Mar. 15, 2023
Applicant:

Oracle International Corporation, Redwood Shores, CA (US);

Inventors:

Dhileeban Kumaresan, Foster City, CA (US);

Jae Young Yoon, San Mateo, CA (US);

Adrienne Wong, Redwood City, CA (US);

Chandra Sekhar Komali, Mountain House, CA (US);

Sreeji Krishnan Das, Fremont, CA (US);

Assignee:

Oracle International Corporation, Redwood Shores, CA (US);

Attorney:
Primary Examiner:
Int. Cl.
CPC ...
G06F 16/00 (2019.01); G06F 11/32 (2006.01); G06F 11/34 (2006.01); G06F 16/21 (2019.01); G06F 16/2455 (2019.01); G06F 16/2457 (2019.01); G06F 16/28 (2019.01); G06F 16/35 (2019.01); G06F 40/242 (2020.01); G06F 40/284 (2020.01);
U.S. Cl.
CPC ...
G06F 16/355 (2019.01); G06F 11/32 (2013.01); G06F 11/3476 (2013.01); G06F 16/217 (2019.01); G06F 16/2455 (2019.01); G06F 16/24575 (2019.01); G06F 16/285 (2019.01); G06F 16/287 (2019.01); G06F 40/242 (2020.01); G06F 40/284 (2020.01); G06F 2201/80 (2013.01);
Abstract

Techniques for implementing user interfaces, systems, and processes for multidimensional clustering and analysis are described herein. In one aspect, an application or cloud service receives a request to cluster a set of records where the request identifies a first set of one or more dimensions to use for clustering and a second set of one or more dimensions to analyze for correlation patterns. Responsive to receiving the request to cluster the set of records, the system generates clusters based at least in part on variances in the first set of one or more dimensions, wherein each cluster includes at least one record from the set of records. The system may generate, for each respective cluster, an analytic result that identifies how strongly the second set of one or more dimensions correlate to the respective cluster. The system may present the clusters and analytic results for further processing.


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