Ontological Filters for Slow Intelligence Systems

Slow Intelligence Systems are general-purpose systems characterized by being able to improve performance over time through a process involving enumeration, propagation, adaptation, elimination and concentration. The transform functions of the building blocks for Slow Intelligence Systems are knowledge transforms. When the knowledge base is an ontology, the transforms are ontological transforms. A particularly important ontological transform is the ontological filter, which can be used both as the Eliminator and as the Concentrator. The Propagator can also use ontological filtering to selectively send messages to other Slow Intelligence Systems. In this paper the lightweight-plus ontology formalism will be introduced and adopted. We can apply the ontological filters to product and service customization, and to the detection of hot topics and trends on the Internet.