International Business Machines Corporation

Rakesh Ranjan

Yuk Lung Chan

Heidi L Lagares-Greenblatt

Nicholas A Vargas

Vatatmaja

Badalkumar L Choudhary

Joydeep Basu

Karunakaran Karuppiah

Simao Liu

Ritu Singh

An approach is provided in which the approach trains a machine learning model using reference entries included in a reference dataset. During the training, the machine learning model learns a first set of unidirectional associations between the reference entries. The approach inputs a user dataset into the trained machine learning model and generates a second set of unidirectional associations between user dataset entries included in the user dataset. The approach builds a hierarchical relationship of the user dataset based on the second set of unidirectional associations and manages the user dataset based on the hierarchical relationship.

Discover unidirectional associations among terms or documents

First sensor data generated by a first of a plurality of sensors and at least second sensor data generated by at least a second of the plurality of sensors can be received by a sensor data broker executed by a processor. The sensor data broker can publish to at least a first virtual sensor the first sensor data as first published sensor data. The sensor data broker can publish to at least a second virtual sensor the second sensor data as second published sensor data.

Sensor data segmentation and virtualization

A utilization by at least one virtual sensor of sensor data provided by at least one sensor can be monitored. A utilization of virtual sensor data by at least one application can be monitored. The virtual sensor data can generated by the at least one virtual sensor based on the sensor data. At least a first sensor data use parameter indicating the utilization of the virtual sensor data by the at least one application can be generated.

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San Jose, CA, United States of America

Rakesh Ranjan