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US 11,443,256 B2Granted
Real-time matching and smart recommendations for tasks and experts
AssigneeSap SE
InventorOren Haze
Life of this patent
Estimating the term…
Abstract
User information for a particular user is accessed. Expert information for experts and training that is available in an organization of the particular user is accessed. One or more pattern matches between the user information and the expert information are determined. One or more expert recommendations are generated based on the one or more pattern matches and provided.
Claims20
A computer-implemented method, comprising:
- accessing, by one or more processors, user information for a particular user;
- accessing, by the one or more processors, expert information for experts and training that is available in an organization of the particular user;
- determining, by the one or more processors, by using a plurality of pattern recognition algorithms, a plurality of pattern matches defining matches between the user information and a predefined pattern relating to the expert information, wherein each pattern match is weighed using an adjustable weight corresponding to a type of pattern recognition algorithm from the plurality of pattern recognition algorithms;
- generating, by the one or more processors, by using a machine learning engine, one or more expert recommendations based on the plurality of pattern matches and past user feedback;
- providing, by the one or more processors, in real time, the one or more expert recommendations corresponding to the training that is available in the organization;
- receiving, by the one or more processors, user feedback associated with the one or more expert recommendations corresponding to the training that is available in the organization;
- and
- updating, by the one or more processors, the machine learning engine based on the user feedback to tailor future expert recommendations.
5 more elements
A non-transitory, computer-readable medium storing one or more instructions executable by a computer system to perform operations comprising:
- accessing user information for a particular user;
- accessing expert information for experts and training that is available in an organization of the particular user;
- determining, by using a plurality of pattern recognition algorithms, a plurality of pattern matches defining matches between the user information and a predefined pattern relating to the expert information, wherein each pattern match is weighed using an adjustable weight corresponding to a type of pattern recognition algorithm from the plurality of pattern recognition algorithms;
- generating, by using a machine learning engine, one or more expert recommendations based on the plurality of pattern matches and past user feedback;
- providing, in real time, the one or more expert recommendations corresponding to the training that is available in the organization;
- receiving user feedback associated with the one or more expert recommendations corresponding to the training that is available in the organization;
- and
- updating the machine learning engine based on the user feedback to tailor future expert recommendations.
5 more elements
A computer-implemented system, comprising:
- one or more computers;
- and
- one or more computer memory devices interoperably coupled with the one or more computers and having tangible, non-transitory, machine-readable media storing one or more instructions that, when executed by the one or more computers, perform one or more operations comprising:
- accessing user information for a particular user;
- accessing expert information for experts and training that is available in an organization of the particular user;
- determining, by using a plurality of pattern recognition algorithms, a plurality of pattern matches defining matches between the user information and a predefined pattern relating to the expert information, wherein each pattern match is weighed using an adjustable weight corresponding to a type of pattern recognition algorithm from the plurality of pattern recognition algorithms;
- generating, by using a machine learning engine, one or more expert recommendations based on the plurality of pattern matches and past user feedback;
- providing, in real time, the one or more expert recommendations corresponding to the training that is available in the organization;
- receiving user feedback associated with the one or more expert recommendations corresponding to the training that is available in the organization;
- and
- updating the machine learning engine based on the user feedback to tailor future expert recommendations.
8 more elements
Dependencies are inferred from the claim text.