Intelligent knowledge management-driven decision making model
A computer-implemented method includes receiving user input including codified knowledge management information and/or engine data; and processing the input using one or more trained machine learning models to generate one or more living documents. A computing system includes one or more processors; and a memory having stored thereon instructions that, when executed, cause the computing system to receive user input including codified knowledge management information and/or engine data; and process the user input using one or more trained machine learning models to generate one or more living documents. A non-transitory computer-readable storage medium includes executable instructions that, when executed by a processor, cause a computer to receive user input including codified knowledge management information and/or engine data; and process the user input using one or more trained machine learning models to generate one or more living documents.
1. A computer-implemented method for improving efficiency and consistency of knowledge management living documents, the method comprising:
receiving, via one or more processors, user input including codified knowledge management information and/or engine data; and
processing, via one or more processors, the user input including the codified knowledge management information and/or the engine data using one or more trained machine learning models to generate one or more living documents.
2. The computer-implemented method of claim 1 , further comprising:
providing a customer recommendation based on the generated one or more living documents.
3. The computer-implemented method of claim 1 , further comprising:
processing the user input including one or more problems and associated respective parameters and/or variables with a natural language processing model to identify a detailed problem statement, at least one associated parameter and at least one associated variable.
4. The computer-implemented method of claim 1 , further comprising:
processing the user input using a trained information collection machine learning model to generate the codified knowledge management information.
5. The computer-implemented method of claim 1 , wherein the engine data includes at least one of (i) intelligent cloud data and technology solutions engine data; (ii) smart domain expertise solutions engine data; (iii) AI-driven experimentation engine data; or (iv) security solutions engine data.
6. The computer-implemented method of claim 1 , further comprising:
updating the one or more living documents with new knowledge based on at least one of (i) a user approval; (ii) output of a machine learning information collection model; or (iii) output of a machine learning extraction, classification and strategy model.
7. The computer-implemented method of claim 6 , wherein updating the one or more living documents with new knowledge is performed continuously.
8. A computing system for improving the efficiency and consistency of knowledge management living documents, comprising:
one or more processors; and
a memory having stored thereon instructions that, when executed, cause the computing system to:
receive, via one or more processors, user input including codified knowledge management information and/or engine data; and
process, via one or more processors, the user input including the codified knowledge management information and/or the engine data using one or more trained machine learning models to generate one or more living documents.
9. The computing system of claim 8 , the having stored thereon further instructions that, when executed, cause the computing system to:
provide a customer recommendation based on the generated one or more living documents.
10. The computing system of claim 8 , the having stored thereon further instructions that, when executed, cause the computing system to:
process the user input including one or more problems and associated respective parameters and/or variables with a natural language processing model to identify a detailed problem statement, at least one associated parameter and at least one associated variable.
11. The computing system of claim 8 , the having stored thereon further instructions that, when executed, cause the computing system to:
process the user input using a trained information collection machine learning model to generate the codified knowledge management information.
12. The computing system of claim 8 , the having stored thereon further instructions that, when executed, cause the computing system to:
receive at least one of (i) intelligent cloud data and technology solutions engine data; (ii) smart domain expertise solutions engine data; (iii) AI-driven experimentation engine data; or (iv) security solutions engine data.
13. The computing system of claim 8 , the having stored thereon further instructions that, when executed, cause the computing system to:
update the one or more living documents with new knowledge based on at least one of (i) a user approval; (ii) output of a machine learning information collection model; or (iii) output of a machine learning extraction, classification and strategy model.
14. The computing system of claim 8 , the having stored thereon further instructions that, when executed, cause the computing system to:
analyze the one or more living documents to identify one or more domain experts.
15. A non-transitory computer-readable storage medium comprising executable instructions that, when executed by a processor, cause a computer to:
receive, via one or more processors, user input including codified knowledge management information and/or engine data; and
process, via one or more processors, the user input including the codified knowledge management information and/or the engine data using one or more trained machine learning models to generate one or more living documents.
16. The non-transitory computer-readable storage medium of claim 15 , storing further executable instructions that, when executed, cause a computer to:
provide a customer recommendation based on the generated one or more living documents.
17. The non-transitory computer-readable storage medium of claim 15 , comprising further executable instructions that, when executed, cause a computer to:
process the user input including one or more problems and associated respective parameters and/or variables with a natural language processing model to identify a detailed problem statement, at least one associated parameter and at least one associated variable.
18. The non-transitory computer-readable storage medium of claim 15 , comprising further executable instructions that, when executed, cause a computer to:
process the user input using a trained information collection machine learning model to generate the codified knowledge management information.
19. The non-transitory computer-readable storage medium of claim 15 , comprising further executable instructions that, when executed, cause a computer to:
receive at least one of (i) intelligent cloud data and technology solutions engine data; (ii) smart domain expertise solutions engine data; (iii) AI-driven experimentation engine data; or (iv) security solutions engine data.
20. The non-transitory computer-readable storage medium of claim 15 , comprising further executable instructions that, when executed, cause a computer to:
update the one or more living documents with new knowledge based on at least one of (i) a user approval; (ii) output of a machine learning information collection model; or (iii) output of a machine learning extraction, classification and strategy model.