Automatic definition of set of categories for document classification

A system, comprising:

• a memory;
• a processor, coupled to the memory, the processor configured to:
• produce a plurality of image features by processing images of a plurality of documents;
• produce a plurality of text features by processing texts of a plurality of documents;
• produce a plurality of feature vectors, wherein each feature vector of the plurality of feature vectors comprises at least one of:
• a subset of the plurality of image features and a subset of the plurality of text features;
• clusterize the plurality feature vectors to produce a plurality of clusters;
• define a plurality of document categories, such that each document category of the plurality of document categories is defined by a respective feature cluster of the plurality of feature clusters;
• and
• train a classifier to produce a value reflecting a degree of association of an input document with one or more document categories of the plurality of document categories.

A non-transitory computer-readable storage medium comprising executable instructions that, when executed by a computer system, cause the computer system to:

• produce a plurality of image features by processing images of a plurality of documents;
• produce a plurality of text features by processing texts of a plurality of documents;
• produce a plurality of feature vectors, wherein each feature vector of the plurality of feature vectors comprises at least one of:
• a subset of the plurality of image features and a subset of the plurality of text features;
• clusterize the plurality feature vectors to produce a plurality of clusters;
• define a plurality of document categories, such that each document category of the plurality of document categories is defined by a respective feature cluster of the plurality of feature clusters;
• and
• train a classifier to produce a value reflecting a degree of association of an input document with one or more document categories of the plurality of document categories.