Oracle International Corporation

Virupaksha Vajragiri

Viresh Chandrakant Amin

Rajan Mahendrakumar Modi

Rajesh Raheja

A method of generating and using a metadata files for integration flows may include analyzing definition files of integration flows to generate metadata files that include summary information for each of the integration flows. The method also includes extracting source-target relationships from the summary information for each of the integration flows and training a model using the plurality of source-target relationships. The method also includes receiving a source element from a current integration flow; providing the source element and characteristics of the current integration flow to the model; and receiving, from the model, recommended target elements to be connected to the source element in the current integration flow.

Machine learning from the integration flow metadata

In accordance with an embodiment, described herein is a system and method for providing recommended mappings to a mapper for use in designing an integration flow in a design time of a cloud-based integration service. A database can store mapping records from a plurality of sources, and mapping records inferred from the extracted mapping records. Each mapping record in the database can be associated with a rating generated by a ranking engine. A recommendation engine can be invoked to retrieve one or more mapping records from the database and an auto suggestion engine, for graphical display in the mapper. The integration flow can be published, and mapping information therein can be parsed by the recommendation engine into one or more mapping records, which are persisted into the database to update the mapping records in the database.

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Fremont, CA, United States of America

Virupaksha Vajragiri