Continuous learning for document processing and analysis

A system comprising:

• a memory;
• a processor coupled to the memory, the processor configured to:
• receive one or more sets of documents;
• assign each document of the one or more sets of documents to one or more basic clusters;
• for each cluster of the one or more basic clusters, train a respective basic cluster model detecting one or more visual element types;
• generate one or more superclusters, each supercluster containing a respective plurality of basic clusters, based on an attribute shared by documents comprised by the plurality of basic clusters;
• for each supercluster of the one or more superclusters, train a respective supercluster model detecting the one or more visual element types;
• assign an input document to a corresponding basic cluster and a corresponding supercluster;
• and
• detecting one or more visual elements by processing the input document by the corresponding basic cluster model and the corresponding supercluster model.

A non-transitory machine-readable storage medium including instructions that, when accessed by a processing device, cause the processing device to:

• receive one or more sets of documents;
• assign each document of the one or more sets of documents to one or more basic clusters;
• for each cluster of the one or more basic clusters, train a respective basic cluster model detecting one or more visual element types;
• generate one or more superclusters, each supercluster containing a respective plurality of basic clusters, based on an attribute shared by documents comprised by the plurality of basic clusters;
• for each supercluster of the one or more superclusters, train a respective supercluster model detecting the one or more visual element types;
• assign an input document to a corresponding basic cluster and a corresponding supercluster;
• and
• detecting one or more visual elements by processing the input document by the corresponding basic cluster model and the corresponding supercluster model.