US 2025/0148348 A1Published application

Knapsack-based recommendation engine

AssigneeSap SE

InventorsBarbora BLASKOVA, Nitin Chavan, Gaurav Vanawat, Sudhir Verma, Rohan Koul, Rajeev Kansal, Shubham Gupta

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Abstract

A machine-learning model is trained to cluster support requests based on the contents of the support requests. A user of the recommendation system may select a set of support requests to be clustered. Based on the selected set of support requests, the trained machine-learning model may be tuned and used to cluster the selected set of support requests. Using the characteristics of the support requests in one or more generated insights, one or more tools suitable for providing automated support for the cluster of support requests may be identified. Using a knapsack-based approach, one or more of the identified tools is selected for recommendation to the user.

Claims20

Dependent claims

A system comprising:

a memory that stores instructions;
and
one or more processors coupled to the memory and configured to execute the instructions to perform operations comprising:
training a machine-learning model to assign support requests to clusters;
receiving, via a first user interface, a selection of an application component;
tuning one or more hyperparameters of the trained machine learning model using a set of previously received support requests for the selected application component to provide a tuned machine-learning model;
determining, using the tuned machine-learning model, a set of clusters of the previously received support requests for the application component;
determining, based on the set of clusters, a set of insights for the application component;
identifying, based on the set of insights, a set of tools for improved support request handling;
based on an amount of resources available for the improved support request handling and an amount of resources consumed by implementing each of the identified tools, selecting a subset of the identified tools;
and
causing a second user interface to be presented that identifies the selected subset of the identified tools.

9 more elements

A non-transitory computer-readable medium that stores instructions that, when executed by one or more processors, cause the one or more processors to perform operations comprising:

training a machine-learning model to assign support requests to clusters;
receiving, via a first user interface, a selection of an application component;
tuning one or more hyperparameters of the trained machine learning model using a set of previously received support requests for the selected application component to provide a tuned machine-learning model;
determining, using the tuned machine-learning model, a set of clusters of the previously received support requests for the application component;
determining, based on the set of clusters, a set of insights for the application component;
identifying, based on the set of insights, a set of tools for improved support request handling;
based on an amount of resources available for the improved support request handling and an amount of resources consumed by implementing each of the identified tools, selecting a subset of the identified tools;
and
causing a second user interface to be presented that identifies the selected subset of identified tools.

6 more elements

Dependencies are inferred from the claim text.