Schema Evolution publication categorizer

The recent growing of the Semantic Web requires the need to cope with highly semantic heterogeneities among available ontologies. Ontology matching techniques aim to tackle this problem by establishing correspondences between ontologies’ elements. An intricate obstacle faces the ontology matching problem is its scalability against large number and large-scale ontologies. To tackle these challenges, in this paper, we propose a new matching framework based on Prüfer sequences. The proposed approach is applicable for matching a database of XML trees . Our approach is based on the representation of XML ontologies as sequences of labels and numbers by the Prüfer’s method that constructs a one-to-one correspondence between schema ontologies and sequences. We capture ontology tree semantic information in Label Prüfer Sequences (LPS) and ontology tree structural information in Number Prüfer Sequences (NPS). Then, we develop a new structural matching algorithm exploiting both LPS and NPS. Our Experimental results demonstrate the performance benefits of the proposed approach