Patent ID: 11954098
Assignee: THOMSON REUTERS ENTERPRISE CENTRE GMBH
Field: Computer technology (Electrical engineering)
Classification: CPC G | IPC G

Claim 16:
17. A non-transitory computer readable medium which, when executed by one or more processors, causes the one or more processors to:
generate, based on a first document, a first feature in the first document associated with an ontology, the first feature including a portion of a first vector containing certain predetermined values;
generate, based on a second document, a second feature in the second document associated with the ontology, the second feature including a portion of a second vector containing certain predetermined values; and
link the first document and the second document by the first feature and the second feature, the first document and the second document being linked based on a similarity of the first vector to the second vector exceeding a defined threshold and comprising a first value of a dimension, the first value associated with the first document, and a second value of the dimension, the second value associated with the second document, the first value and the second value within a range of each other based on the defined threshold;
wherein the first vector, the second vector, and the certain predetermined values are identified by a plurality of trained machine learning models executed on the first document and the second document, the plurality of trained machine learning models comprising a learned paragraph model trained to identify an ontological category and a learned sentence model trained to identify an ontological sub-category of the ontological category that, when executed sequentially, generate the first feature and the second feature, wherein an output of the learned paragraph model is an input to the learned sentence model.