Modern Information Retrieval
An Information-Theoretic Definition of Similarity
ICML '98 Proceedings of the Fifteenth International Conference on Machine Learning
Conceptual Graph Matching for Semantic Search
ICCS '02 Proceedings of the 10th International Conference on Conceptual Structures: Integration and Interfaces
Similarity Flooding: A Versatile Graph Matching Algorithm and Its Application to Schema Matching
ICDE '02 Proceedings of the 18th International Conference on Data Engineering
A semantic complement to enhance electronic market
Expert Systems with Applications: An International Journal
An ontology and peer-to-peer based data and service unified discovery system
Expert Systems with Applications: An International Journal
Bring QoS to P2P-based semantic service discovery for the Universal Network
Personal and Ubiquitous Computing
Ontology model for semantic web service matching
ICICA'10 Proceedings of the First international conference on Information computing and applications
Combining uncorrelated similarity measures for service discovery
RED'10 Proceedings of the Third international conference on Resource Discovery
An automatic subdigraph renovation plan for failure recovery of composite semantic Web services
Frontiers of Computer Science: Selected Publications from Chinese Universities
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Measuring semantic similarity of web services has several benefits and most of the proposed service discovery algorithms are based on measuring the similarity of the requested service with each of the advertised services. In this paper, we propose a method for measuring the similarity of web services which are annotated with OWL-S ontology. First, a semantic similarity measure for determining the similarity of OWL concepts is discussed and then based on this measure, the functional similarity of services is defined. Then it is showed that the precision of algorithms that only take into account the functional properties of services for measuring their similarity are low. Therefore the textual descriptions of web services are also taken into account and the textual similarity of services is also calculated. Then it is showed how Neural Networks can be used for combining these two measures for a better compound measure. The proposed technique is applied to a sample test collection and experimental results are presented which demonstrate the effectiveness of the idea.