A node semantic similarity schema-matching method for multi-version Web Coverage Service retrieval
Different versions of the Web Coverage Service (WCS) schemas of the Open Geospatial Consortium (OGC) reflect semantic conflict. When applying the extended FRAG-BASE schema-matching approach (a schema-matching method based on COMA++, including an improved schema decomposition algorithm and schema fragments identification algorithm, which enable COMA++-based support to OGC Web Service schema matching), the average recall of WCS schema matching is only 72%, average precision is only 82% and average overall is only 57%. To improve the quality of multi-version WCS retrieval, we propose a schema-matching method that measures node semantic similarity (NSS). The proposed method is based on WordNet, conjunctive normal form and a vector space model. A hybrid algorithm based on label meanings and annotations is designed to calculate the similarity between label concepts. We translate the semantic relationships between nodes into a propositional formula and verify the validity of this formula to confirm the semantic relationships. The algorithm first computes the label and node concepts and then calculates the conceptual relationship between the labels. Finally, the conceptual relationship between nodes is computed. We then use the NSS method in experiments on different versions of WCS. Results show that the average recall of WCS schema matching is greater than 83%; average precision reaches 92%; and average overall is 67%.
web coverage service schema matching conjunctive normal form vector space model semantic relationship