Sap Se

Naga Sai Narasimha Guru Charan Koduri

Kavitha Krishnan

Rahul Choudhary

Baber Farooq

Kumar Nitesh

A method may include applying, to various factors contributing to a sentiment that an end user exhibits towards an enterprise software application, a first machine learning model trained to determine, based on the factors, a sentiment index indicating the sentiment that the end user exhibits towards the enterprise software application. In response to the sentiment index exceeding a threshold value, a second machine learning model may be applied to identify remedial actions for addressing one or more of the factors contributing to the sentiment of the end user. A user interface may be generated to display, at a client device, a recommendation including the remedial actions. The remedial actions may be prioritized based on how much each corresponding factor contribute to the sentiment of the end user. Related systems and articles of manufacture are also provided.

Machine learning models for sentiment prediction and remedial action recommendation

A method for machine-learning based process flow recommendation is provided. The method may include training a machine-learning model by at least processing training data with the machine-learning model. The training data may include a matrix representing one or more existing process flows by at least indicating actions that are performed on a document object to generate a subsequent document object. An indication that a first document object is created as part of a process flow may be received. In response to the indication, the trained machine-learning model may be applied to generate a recommendation to perform, as part of the process flow, an action to generate a second document object. Related systems and articles of manufacture, including computer program products, are also provided.

Machine learning based process flow engine

Disclosed herein are system, method, and computer program product embodiments for developing natural language skills automatically. In order to generate a skill, metadata is read from a connected service, wherein the metadata specifies entities provided by the service. A relevant entity of the entities provided by the service is determined, and a likely request on the entity is generated.

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Vijayawada, India

Naga Sai Narasimha Guru Charan Koduri