Similarity Matching Algorithm for Ontology-Based Semantic Information Retrieval Model

In recent years the extreme growth of digital documents brought to light the need for novel approaches and more efficient techniques to improve the precision and the recall of IR systems. In this paper I proposed a novel Similarity Matching Algorithm for Ontology-Based Semantic Information Retrieval Model to measure whether two ontologies are matching or not from the name, the attribute and the theme of the concepts. Simulation shows that for the same recall, the proposed algorithm can increase the precision and flexibility compared with the traditional semantic similarity matching methods.