The Concept Assigner performs automatic subject indexing based on a variant of a Hopfield network. The Concept Assigner first creates a Concept Space which serves as the Hopfield network of concepts (nodes) and their associations (weights) within a corpus.

To automatically index an individual document, the MCE extracts concepts from the document to be indexed, and these concepts become the input pattern to the network. After completion of the Hopfield net parallel spreading activation process, the output from the network produces another set of concepts that are strongly related to the concepts of the input document. Due to the fact that the initial Concept Space contains knowledge obtained from the entire collection, the system is able to find a set of global concepts drawn from the entire collection without being restricted to those concepts present in the given document. These concepts are analogous to concept descriptors (i.e., keywords in the textual domain) of the document.