IP Library Granted Patent US 11,599,801
Granted Patent B2
US 11,599,801 · App. 16/825,389 · Granted Mar 7, 2023

Method for solving problem, computing system and program product

Inventors: YuHong Nie (Shanghai, CN); WuiChak Wong (Xiamen, CN); Sanping Li (Beijing, CN); Xuwei Tang (Nanjing, CN)
Assignee: EMC IP Holding Company LLC
G06N5/022
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Quick Facts
Patent No.
US 11,599,801
App. No.
16/825,389
Granted
Mar 7, 2023
Kind
B2
Abstract

Embodiments of the present disclosure provide a method for solving a problem, a computing system and a program product. A method for solving a problem includes determining information related to a to-be-solved problem; acquiring, based on the information, knowledge elements that can be used for the to-be-solved problem from a knowledge repository, the knowledge repository storing: solved problems, at least one executable task related to the solved problems, at least one processing flow for implementing the at least one executable task, and a corresponding function module included in the at least one processing flow; and determining, based at least on the acquired knowledge elements, a solution to the to-be-solved problem. By such arrangements, automatic problem solving can be achieved in a faster, simpler way with a lower cost through division of the repository and the knowledge elements.

Claims (69)

1. A method for solving a problem, comprising:

determining information related to a to-be-solved problem;

acquiring, based on the information related to the to-be-solved problem, knowledge elements that are used for the to-be-solved problem from a knowledge repository, wherein the knowledge repository stores: solved problems, at least one executable task related to the solved problems, at least one processing flow for implementing the at least one executable task, and a corresponding function module included in the at least one processing flow;

determining, based at least on the acquired knowledge elements, a solution to the to-be-solved problem;

updating the knowledge repository based on the solution to the to-be-solved problem; and

automatically utilizing the updated knowledge repository to determine a solution to a subsequent to-be-solved problem;

wherein acquiring the knowledge elements comprises:

acquiring, based on the information related to the to-be-solved problem, a set of knowledge elements including: a target executable task related to a target solved problem matching the to-be-solved problem, a target processing flow for implementing the target executable task, and a corresponding function module included in the target processing flow from the knowledge repository.

2. The method of claim 1 , wherein the information related to the to-be-solved problem comprises a problem description of the to-be-solved problem, and wherein acquiring the knowledge elements further comprises:

searching, based on the problem description of the to-be-solved problem, the knowledge repository for the target solved problem matching the to-be-solved problem; and

acquiring, according to a finding of the target solved problem matching the to-be-solved problem, the target executable task related to the target solved problem matching the to-be-solved problem, the target processing flow for implementing the target executable task, and the corresponding function module included in the target processing flow from the knowledge repository as at least a portion of the set of knowledge elements.

3. The method of claim 1 , wherein the information related to the to-be-solved problem comprises a task description of a source executable task related to the to-be-solved problem, and wherein acquiring the knowledge elements further comprises:

searching, based on the task description of the source executable task, the knowledge repository for the target executable task matching the source executable task; and

acquiring, according to a finding of the target executable task matching the source executable task, the target processing flow for implementing the target executable task, and the corresponding function module included in the target processing flow from the knowledge repository as at least a portion of the set of knowledge elements.

4. The method of claim 3 , wherein determining the information related to the to-be-solved problem comprises:

providing to a user, according to a failure to find the target solved problem matching the to-be-solved problem from the knowledge repository, a request to designate the source executable task related to the to-be-solved problem; and

receiving the task description of the source executable task related to the to-be-solved problem.

5. The method of claim 1 , wherein the information related to the to-be-solved problem comprises a function description of a source function module included in a source processing flow which is used for implementing a source executable task related to the to-be-solved problem, and wherein acquiring the knowledge elements further comprises:

searching, based on the function description of the source function module, the knowledge repository for a target function module matching the source function module; and

acquiring, according to a finding of the target function module matching the source function module, the target function module from the knowledge repository as at least a portion of the set of knowledge elements.

6. The method of claim 5 , wherein determining the information related to the to-be-solved problem comprises:

providing to a user, according to a failure to find the target executable task matching the source executable task from the knowledge repository, a request to designate the source function module included in the source processing flow; and

receiving the function description of the source function module included in the source processing flow.

7. The method of claim 1 , wherein determining the solution to the to-be-solved problem comprises:

determining the solution to the to-be-solved problem to comprise a source executable task related to the to-be-solved problem, a source processing flow for implementing the source executable task, and a corresponding function module included in the source processing flow.

8. The method of claim 7 , further comprising:

storing the to-be-solved problem, the source executable task, the source processing flow, and the corresponding function module included in the source processing flow to the knowledge repository as the knowledge elements.

9. The method of claim 1 , further comprising:

determining a data format related to raw data to be processed for the to-be-solved problem, wherein acquiring the knowledge elements further comprises determining the knowledge elements from the knowledge repository based on the data format, so that the solution to the to-be-solved problem corresponding to the knowledge elements is suitable for the data format.

10. The method of claim 1 , wherein the to-be-solved problem and the solved problems comprise abstract problems, wherein the at least one executable task comprises a machine learning task, and wherein the at least one processing flow comprises an algorithm pipeline.

11. A computing system, comprising:

at least one processor; and

at least one memory storing computer program instructions, wherein the at least one memory and the computer program instructions are configured to control the at least one processor to perform actions, the actions comprising:

determining information related to a to-be-solved problem;

acquiring, based on the information related to the to-be-solved problem, knowledge elements that are used for the to-be-solved problem from a knowledge repository, wherein the knowledge repository stores: solved problems, at least one executable task related to the solved problems, at least one processing flow for implementing the at least one executable task, and a corresponding function module included in the at least one processing flow;

determining, based at least on the acquired knowledge elements, a solution to the to-be-solved problem;

updating the knowledge repository based on the solution to the to-be-solved problem; and

automatically utilizing the updated knowledge repository to determine a solution to a subsequent to-be-solved problem;

wherein acquiring the knowledge elements comprises:

acquiring, based on the information related to the to-be-solved problem, a set of knowledge elements including: a target executable task related to a target solved problem matching the to-be-solved problem, a target processing flow for implementing the target executable task, and a corresponding function module included in the target processing flow from the knowledge repository.

12. The computing system of claim 11 , wherein the information related to the to-be-solved problem comprises a problem description of the to-be-solved problem, and wherein acquiring the knowledge elements further comprises:

searching, based on the problem description of the to-be-solved problem, the knowledge repository for the target solved problem matching the to-be-solved problem; and

acquiring, according to a finding of the target solved problem matching the to-be-solved problem, the target executable task related to the target solved problem matching the to-be-solved problem, the target processing flow for implementing the target executable task, and the corresponding function module included in the target processing flow from the knowledge repository as at least a portion of the set of knowledge elements.

13. The computing system of claim 11 , wherein the information related to the to-be-solved problem comprises a task description of a source executable task related to the to-be-solved problem, and wherein acquiring the knowledge elements further comprises:

searching, based on the task description of the source executable task, the knowledge repository for the target executable task matching the source executable task; and

acquiring, according to a finding of the target executable task matching the source executable task, the target processing flow for implementing the target executable task, and the corresponding function module included in the target processing flow from the knowledge repository as at least a portion of the set of knowledge elements.

14. The computing system of claim 13 , wherein determining the information related to the to-be-solved problem comprises:

providing to a user, according to a failure to find the target solved problem matching the to-be-solved problem from the knowledge repository, a request to designate the source executable task related to the to-be-solved problem; and

receiving the task description of the source executable task related to the to-be-solved problem.

15. The computing system of claim 11 , wherein the information related to the to-be-solved problem comprises a function description of a source function module included in a source processing flow which is used for implementing a source executable task related to the to-be-solved problem, and wherein acquiring the knowledge elements further comprises:

searching, based on the function description of the source function module, the knowledge repository for a target function module matching the source function module; and

acquiring, according to a finding of the target function module matching the source function module, the target function module from the knowledge repository as at least a portion of the set of knowledge elements.

16. The computing system of claim 15 , wherein determining the information related to the to-be-solved problem comprises:

providing to a user, according to a failure to find the target executable task matching the source executable task from the knowledge repository, a request to designate the source function module included in the source processing flow; and

receiving the function description of the source function module included in the source processing flow.

17. The computing system of claim 11 , wherein determining the solution to the to-be-solved problem comprises:

determining the solution to the to-be-solved problem to comprise a source executable task related to the to-be-solved problem, a source processing flow for implementing the source executable task, and a corresponding function module included in the source processing flow.

18. The computing system of claim 17 , wherein the actions further comprise at least one of:

storing the to-be-solved problem, the source executable task, the source processing flow, and the corresponding function module included in the source processing flow to the knowledge repository as the knowledge elements; and

determining a data format related to raw data to be processed for the to-be-solved problem, wherein acquiring the knowledge elements further comprises determining the knowledge elements from the knowledge repository based on the data format, so that the solution to the to-be-solved problem corresponding to the knowledge elements is suitable for the data format.

19. The computing system of claim 11 , wherein the to-be-solved problem and the solved problems comprise abstract problems, wherein the at least one executable task comprises a machine learning task, and wherein the at least one processing flow comprises an algorithm pipeline.

20. A computer program product, the computer program product being tangibly stored on a non-volatile computer-readable medium and including machine-executable instructions which, when being executed, cause a device to implement a method for solving a problem, comprising:

determining information related to a to-be-solved problem;

acquiring, based on the information related to the to-be-solved problem, knowledge elements that are used for the to-be-solved problem from a knowledge repository, wherein the knowledge repository stores: solved problems, at least one executable task related to the solved problems, at least one processing flow for implementing the at least one executable task, and a corresponding function module included in the at least one processing flow;

determining, based at least on the acquired knowledge elements, a solution to the to-be-solved problem;

updating the knowledge repository based on the solution to the to-be-solved problem; and

automatically utilizing the updated knowledge repository to determine a solution to a subsequent to-be-solved problem;

wherein acquiring the knowledge elements comprises:

acquiring, based on the information related to the to-be-solved problem, a set of knowledge elements including: a target executable task related to a target solved problem matching the to-be-solved problem, a target processing flow for implementing the target executable task, and a corresponding function module included in the target processing flow from the knowledge repository.

Assignments (13)
RELEASE OF SECURITY INTEREST IN PATENTS PREVIOUSLY RECORDED AT REEL/FRAME (052851/0917) Recorded Jun 23, 2022
From: THE BANK OF NEW YORK MELLON TRUST COMPANY, N.A., AS NOTES COLLATERAL AGENT
To: DELL PRODUCTS L.P.; EMC IP HOLDING COMPANY LLC
Reel/Frame 060436/0509 →
RELEASE OF SECURITY INTEREST IN PATENTS PREVIOUSLY RECORDED AT REEL/FRAME (052852/0022) Recorded Jun 23, 2022
From: THE BANK OF NEW YORK MELLON TRUST COMPANY, N.A., AS NOTES COLLATERAL AGENT
To: DELL PRODUCTS L.P.; EMC IP HOLDING COMPANY LLC
Reel/Frame 060436/0582 →
RELEASE OF SECURITY INTEREST IN PATENTS PREVIOUSLY RECORDED AT REEL/FRAME (052851/0081) Recorded Jun 23, 2022
From: THE BANK OF NEW YORK MELLON TRUST COMPANY, N.A., AS NOTES COLLATERAL AGENT
To: DELL PRODUCTS L.P.; EMC IP HOLDING COMPANY LLC
Reel/Frame 060436/0441 →
RELEASE OF SECURITY INTEREST IN PATENTS PREVIOUSLY RECORDED AT REEL/FRAME (053311/0169) Recorded Jun 23, 2022
From: THE BANK OF NEW YORK MELLON TRUST COMPANY, N.A., AS NOTES COLLATERAL AGENT
To: DELL PRODUCTS L.P.; EMC CORPORATION; EMC IP HOLDING COMPANY LLC
Reel/Frame 060438/0742 →
RELEASE OF SECURITY INTEREST IN PATENTS PREVIOUSLY RECORDED AT REEL/FRAME (053546/0001) Recorded Jun 23, 2022
From: THE BANK OF NEW YORK MELLON TRUST COMPANY, N.A., AS NOTES COLLATERAL AGENT
To: DELL MARKETING L.P. (ON BEHALF OF ITSELF AND AS SUCCESSOR-IN-INTEREST TO CREDANT TECHNOLOGIES, INC.); DELL INTERNATIONAL L.L.C.; DELL PRODUCTS L.P.; DELL USA L.P.; EMC CORPORATION; DELL MARKETING CORPORATION (SUCCESSOR-IN-INTEREST TO FORCE10 NETWORKS, INC. AND WYSE TECHNOLOGY L.L.C.); EMC IP HOLDING COMPANY LLC
Reel/Frame 071642/0001 →
RELEASE OF SECURITY INTEREST AT REEL 052771 FRAME 0906 Recorded Nov 2, 2021
From: CREDIT SUISSE AG, CAYMAN ISLANDS BRANCH
To: DELL PRODUCTS L.P.; EMC IP HOLDING COMPANY LLC
Reel/Frame 058001/0298 →
SECURITY INTEREST Recorded Jun 5, 2020
From: DELL PRODUCTS L.P.; EMC IP HOLDING COMPANY LLC
To: THE BANK OF NEW YORK MELLON TRUST COMPANY, N.A., AS COLLATERAL AGENT
Reel/Frame 052852/0022 →
SECURITY INTEREST Recorded Jun 5, 2020
From: DELL PRODUCTS L.P.; EMC IP HOLDING COMPANY LLC; THE BANK OF NEW YORK MELLON TRUST COMPANY, N.A., AS COLLATERAL AGENT
To: THE BANK OF NEW YORK MELLON TRUST COMPANY, N.A., AS COLLATERAL AGENT
Reel/Frame 052851/0081 →
SECURITY INTEREST Recorded Jun 5, 2020
From: DELL PRODUCTS L.P.; EMC IP HOLDING COMPANY LLC
To: THE BANK OF NEW YORK MELLON TRUST COMPANY, N.A., AS COLLATERAL AGENT
Reel/Frame 052851/0917 →
SECURITY INTEREST Recorded Jun 5, 2020
From: DELL PRODUCTS L.P.; EMC CORPORATION; EMC IP HOLDING COMPANY LLC
To: THE BANK OF NEW YORK MELLON TRUST COMPANY, N.A., AS COLLATERAL AGENT
Reel/Frame 053311/0169 →
SECURITY AGREEMENT Recorded May 28, 2020
From: DELL PRODUCTS L.P.; EMC IP HOLDING COMPANY LLC
To: CREDIT SUISSE AG, CAYMAN ISLANDS BRANCH
Reel/Frame 052771/0906 →
SECURITY AGREEMENT Recorded Apr 22, 2020
From: CREDANT TECHNOLOGIES INC.; DELL INTERNATIONAL L.L.C.; DELL MARKETING L.P.; DELL PRODUCTS L.P.; DELL USA L.P.; EMC CORPORATION; FORCE10 NETWORKS, INC.; WYSE TECHNOLOGY L.L.C.; EMC IP HOLDING COMPANY LLC
To: THE BANK OF NEW YORK MELLON TRUST COMPANY, N.A.
Reel/Frame 053546/0001 →
ASSIGNMENT OF ASSIGNOR'S INTEREST Recorded Mar 31, 2020
From: NIE, YUHONG; WONG, WUICHAK; LI, SANPING; TANG, XUWEI
To: EMC IP HOLDING COMPANY LLC
Reel/Frame 052274/0956 →
Priority Claims (1)
CN 202010125604.4 · Feb 27, 2020 · national
Continuity (1)
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