Abstract
With the introduction of the Web 3.0 standards on the World Wide Web, there is a need to include semantic techniques and ontologies in the Web based Recommendation Systems. In order to build query relevant domains and make information retrieval more efficient, it required recommending ontologies based on the query. Most ontology recommendation systems do not preserve the associations and axioms between them rather ontology matching and clustering algorithms tend to deduce logics dynamically. In this paper, a semantic algorithm for ontology recommendation has been proposed, where query-relevant ontologies are recommended by preserving the relationships between the ontological entities. The semantic similarity is computed using the query and the concepts initially and further between the query and description logics which makes it a context-based ontology recommendation system. A strategic approach called as SemantoSim is proposed to compute the semantic similarity.
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Leena Giri, G., Deepak, G., Manjula, S., Venugopal, K. (2018). OntoYield: A Semantic Approach for Context-Based Ontology Recommendation Based on Structure Preservation. In: Chaki, N., Cortesi, A., Devarakonda, N. (eds) Proceedings of International Conference on Computational Intelligence and Data Engineering. Lecture Notes on Data Engineering and Communications Technologies, vol 9. Springer, Singapore. https://doi.org/10.1007/978-981-10-6319-0_22
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DOI: https://doi.org/10.1007/978-981-10-6319-0_22
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