Ontology matching based on weak supervision

A processing system comprising one or more processors configured to perform a method for matching a set of first classes assigned to a first data set with a set of second classes assigned to a second data set by:

• constructing, via a set of pre-processing functions, a plurality of alignment profiles such that at least one alignment profile is assigned to each of the first classes and each of the second classes;
• generating a comparison matrix for each group of the alignment profiles to include the similarities of the first class and the second class within each group, which are calculated by different combinations of embedding functions and distance functions;
• training a first machine learning model, through supervised training, based on the generated comparison matrices and based on probabilistic labels generated by a second machine learning model, wherein the second machine learning model has been trained through weakly supervised learning;
• and
• determining with the trained first machine learning model which of the first classes can be matched with any of the second classes.