Abstract :
Resource Description framework (RDF) in semantics web faces several challenges in terms of rapid increase in its volume and continuous change. This paper presents a new clustering methodology for semantic web data by utilizing ant colony optimization algorithm. The methodology has two pre-processing steps to extract RDF instances and compute a distance matrix between these instances. Next, ACO is implemented to find clusters based on ants discovering the shortest path. The algorithm also uses two objective functions, compactness and separation, to evaluate the discovered clusters. The experiments are conducted on the proposed methodology and showed promised results for clustering quality.
Keyword :
RDF, Semantic web, Clustering, ACO