Agent-based clustering of abstract similar documents

Abstract

A continuous, emergent, anytime process clusters input documents according to a similarity function within a node-based, distributed computing environment, for example, within a client/server environment. An agent (DAg) assigned to each document determines whether its document should remain at a node or be moved to another node to increase similarity clustering. An agent (SAg) assigned to each node may be operative to manage storage requirements within its node, and/or manage communications between the nodes of the environment as the DAgs operate. Typically a move request is issued to another node if it is determined that clustering would increase by moving a document to that node. In such an instance, the SAg assigned to that other node would probabilistically consider the move request in view of other such requests in sequence to avoid overloading. To enhance performance, documents may be preprocessed and given values representative of similarity. The similarity between two arbitrary documents may then assessed as the average difference between the values assigned to the same attribute in the two documents.