A Semantic Search Algorithm for Peer-to-Peer Open Hypermedia Systems

Abstract

We consider a collaborative application scenario in Open Hypermedia Systems. We describe a semantic search algorithm to discover semantically equivalent or related resources across distributed link databases, otherwise known as linkbases. Our approach differs from traditional crawler based search mechanisms because it relies on clustering of semantically related entities. It creates clusters of related semantic entities to expedite the search for resources in a random network. It uses a distance-vector based heuristic to guide the search. Our results confirm that the algorithm yields high search efficiency in collaborative environments where the change in content published by each participant is rapid and random