Framework for large-scale multi-label classification

摘要

A framework for large-scale multi-label classification of an electronic document is described. An example multi-label classification system is configured to first apply weak classifiers and identify seed labels, then determine additional labels based on the seed labels and label correlation data derived from member profiles maintained by an on-line social network system. The multi-label classification system then constructs an s-t graph comprising nodes that correspond to the seed labels and the additional labels. A clustering algorithm is then applied to the constructed graph to arrive to a labels graph. The labels graph is deemed to include nodes that correspond to topics discussed or referenced in the electronic document.