Knowledge-based Semantic Clustering

Abstract

Users of the web are increasingly interested in tracking the appearance of new postings rather than locating existing knowledge. Coupled with this is the emergence of the Web 2.0 movement (where everyone effectively publishes and subscribes), and the concept of the ?Internet of Things?. These trends bring into sharp focus the need for efficient distribution of information. However to date there has been few examples of applying ontology-based techniques to achieve this. Knowledge-based networking (KBN) involves the forwarding of messages across a network based not just on the contents of the messages but also on the semantics of the associated metadata. In this paper we examine the scalability problems of such a network that would meet the needs of Internet-scale semantic-based event feeds. This examination is conducted by evaluating an implemented extension to an existing pub-sub content-based networking (CBN) algorithm to support matching of notification messages to client subscription filters using ontology-based reasoning. We also demonstrate how the clustering of ontologies leads to increased efficiencies in the subscription forwarding tables used, which in turn results in increased scalability of the network.