IP Library Granted Patent US 12,299,600
Granted Patent B2
US 12,299,600 · App. 17/940,726 · Granted May 13, 2025

Cognitive rule engine

Inventors: Mohsen Rais-Ghasem (Ottawa, CA); Elif Tutuk (Verona, WI)
Assignee: QlikTech International AB
G06N5/043G06F16/2423G06F16/24564G06F16/248
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Quick Facts
Patent No.
US 12,299,600
App. No.
17/940,726
Granted
May 13, 2025
Kind
B2
Abstract

In an aspect, provided is a method comprising monitoring one or more data analysis sessions, determining, based on the monitoring, a common data analysis technique performed across common data analysis sessions, identifying the common data analysis technique as a precedent, and providing the precedent to a precedent engine.

Claims (34)

1. A method comprising:

determining, based on one or more monitored data analysis sessions, a common data analysis technique performed across the one or more monitored data analysis sessions, wherein the common data analysis technique comprises a result of an evaluation of a plurality of data records during the one or more monitored data analysis sessions, and wherein the result of the evaluation is based on one or more user interface selections received during the one or more monitored data analysis sessions and associated with one or more dimensions of the plurality of data records;

determining, during a current data analysis session, that one or more current user interface selections are associated with the one or more dimensions of the plurality of data records;

causing, based on the one or more current user interface selections, at least one graphical object to be output during the current data analysis session, wherein the at least one graphical object comprises an indication that the common data analysis technique is available to be applied during the current data analysis session, and wherein the one or more current user interface selections cause a selection of a portion of the plurality of data records associated with the one or more dimensions and indicative of the common data analysis technique; and

causing, based on an indication of a selection of the at least one graphical object during the current data analysis session, and based on the selection of the portion of the plurality of data records, the common data analysis technique to be applied during the current data analysis session.

2. The method of claim 1 , wherein the one or more dimensions comprise one or more classification variables within the plurality of data records.

3. The method of claim 1 , wherein the common data analysis technique comprises one or more of an expression, a visualization, or an aggregation.

4. The method of claim 1 , wherein determining the common data analysis technique performed across the one or more monitored data analysis sessions comprises determining a common feature associated with the one or more monitored data analysis sessions, and wherein the common feature comprises one or more of a common user, a common data set, a common data type, a common visualization, or a common title.

5. The method of claim 1 , wherein the current data analysis session comprises a visualization of at least the portion of the plurality of data records based on the one or more current user interface selections, and wherein causing the common data analysis technique to be applied during the current data analysis session comprises applying the common data analysis technique to the visualization.

6. The method of claim 1 , wherein causing the common data analysis technique to be applied during the current data analysis session comprises determining a result of an evaluation of at least the portion of the plurality of data records, and wherein the portion of the plurality of data records comprises the one or more dimensions.

7. The method of claim 1 , wherein the common data analysis technique comprises one or more parameters based on the one or more dimensions, and wherein the one or more parameters comprise a class, a match criteria, a scope, or a content type.

8. An apparatus comprising:

one or more processors, and

a memory storing processor-executable instructions that, when executed by the one or more processors, cause the apparatus to:

determine, based on one or more monitored data analysis sessions, a common data analysis technique performed across the one or more monitored data analysis sessions, wherein the common data analysis technique comprises a result of an evaluation of a plurality of data records during the one or more monitored data analysis sessions, and wherein the result of the evaluation is based on one or more user interface selections received during the one or more monitored data analysis sessions and associated with one or more dimensions of the plurality of data records;

determine, during a current data analysis session, that one or more current user interface selections are associated with the one or more dimensions of the plurality of data records;

cause, based on the one or more current user interface selections, at least one graphical object to be output during the current data analysis session, wherein the at least one graphical object comprises an indication that the common data analysis technique is available to be applied during the current data analysis session, and wherein the one or more current user interface selections cause a selection of a portion of the plurality of data records associated with the one or more dimensions and indicative of the common data analysis technique; and

cause, based on an indication of a selection of the at least one graphical object during the current data analysis session, and based on the selection of the portion of the plurality of data records, the common data analysis technique to be applied during the current data analysis session.

9. The apparatus of claim 8 , wherein the one or more dimensions comprise one or more classification variables within the plurality of data records.

10. The apparatus of claim 8 , wherein the common data analysis technique comprises one or more of an expression, a visualization, or an aggregation.

11. The apparatus of claim 8 , wherein the processor-executable instructions that cause the apparatus to determine the common data analysis technique performed across the one or more monitored data analysis sessions further cause the apparatus to determine a common feature associated with the one or more monitored data analysis sessions, and wherein the common feature comprises one or more of a common user, a common data set, a common data type, a common visualization, or a common title.

12. The apparatus of claim 8 , wherein the current data analysis session comprises a visualization of at least the portion of the plurality of data records based on the one or more current user interface selections, and wherein causing the common data analysis technique to be applied during the current data analysis session comprises applying the common data analysis technique to the visualization.

13. The apparatus of claim 8 , wherein wherein the processor-executable instructions that cause the apparatus to cause the common data analysis technique to be applied during the current data analysis session further cause the apparatus to determine a result of an evaluation of at least the portion of the plurality of data records, and wherein the portion of the plurality of data records comprises the one or more dimensions.

14. The apparatus of claim 8 , wherein the common data analysis technique comprises one or more parameters based on the one or more dimensions, and wherein the one or more parameters comprise a class, a match criteria, a scope, or a content type.

15. A non-transitory computer-readable medium storing processor- executable instructions that, when executed by one or more processors of a computing device, cause the computing device to:

determine, based on one or more monitored data analysis sessions, a common data analysis technique performed across the one or more monitored data analysis sessions, wherein the common data analysis technique comprises a result of an evaluation of a plurality of data records during the one or more monitored data analysis sessions, and wherein the result of the evaluation is based on one or more user interface selections received during the one or more monitored data analysis sessions and associated with one or more dimensions of the plurality of data records;

determine, during a current data analysis session, that one or more current user interface selections are associated with the one or more dimensions of the plurality of data records;

cause, based on the one or more current user interface selections, at least one graphical object to be output during the current data analysis session, wherein the at least one graphical object comprises an indication that the common data analysis technique is available to be applied during the current data analysis session, and wherein the one or more current user interface selections cause a selection of a portion of the plurality of data records associated with the one or more dimensions and indicative of the common data analysis technique; and

cause, based on an indication of a selection of the at least one graphical object during the current data analysis session, and based on the selection of the portion of the plurality of data records, the common data analysis technique to be applied during the current data analysis session.

16. The non-transitory computer-readable medium of claim 15 , wherein the one or more dimensions comprise one or more classification variables within the plurality of data records.

17. The non-transitory computer-readable medium of claim 15 , wherein the common data analysis technique comprises one or more of an expression, a visualization, or an aggregation.

18. The non-transitory computer-readable medium of claim 15 , wherein the processor-executable instructions that cause the computing device to determine the common data analysis technique performed across the one or more monitored data analysis sessions further cause the computing device to determine a common feature associated with the one or more monitored data analysis sessions, and wherein the common feature comprises one or more of a common user, a common data set, a common data type, a common visualization, or a common title.

19. The non-transitory computer-readable medium of claim 15 , wherein the current data analysis session comprises a visualization of at least the portion of the plurality of data records based on the one or more current user interface selections, and wherein causing the common data analysis technique to be applied during the current data analysis session comprises applying the common data analysis technique to the visualization.

20. The non-transitory computer-readable medium of claim 15 , wherein the processor-executable instructions that cause the computing device to cause the common data analysis technique to be applied during the current data analysis session further cause the computing device to determine a result of an evaluation of at least the portion of the plurality of data records, and wherein the portion of the plurality of data records comprises the one or more dimensions.

Assignments (3)
SECOND LIEN INTELLECTUAL PROPERTY SECURITY AGREEMENT Recorded May 8, 2025
From: QLIKTECH INTERNATIONAL AB
To: MORGAN STANLEY SENIOR FUNDING, INC., AS COLLATERAL AGENT
Reel/Frame 071224/0394 →
ASSIGNMENT OF ASSIGNOR'S INTEREST Recorded Sep 30, 2024
From: RAIS-GHASEM, MOHSEN; TUTUK, ELIF
To: QLIKTECH INTERNATIONAL AB
Reel/Frame 068742/0285 →
SECURITY INTEREST Recorded Apr 18, 2024
From: QLIKTECH INTERNATIONAL AB
To: MORGAN STANLEY SENIOR FUNDING, INC., AS COLLATERAL AGENT
Reel/Frame 067168/0117 →
Continuity (3)
Continuation 15984116 · May 18, 2018
Provisional Application 62505691 · May 12, 2017
Related Publication 20230077834A1 · Mar 16, 2023
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