Ontology concept semantic similarity matching based on Ant Colony Optimization algorithm

References

• Song L., Ma J., Liu H., Lian L., Zhang D. (2007) Fuzzy Semantic Similarity Between Ontological Concepts. In: Elleithy K. (eds) Advances and Innovations in Systems, Computing Sciences and Software Engineering. Springer, Dordrecht.
   Google Scholar
• Ganggao Zhu, Carlos A. Iglesias, “Sematech: Semantic similarity framework for Knowledge Graphs,” Knowledge-Based Systems, Volume 130, 2017.
   PubMed Web of Science ®Google Scholar
• Hau J., Lee W., Darlington J.: A Semantic Similarity Measure for Semantic Web Services. In: the 14th international conference on World Wide Web, Chiba, Japan (2005).
   Google Scholar
• Abdelhadi Daoui, Noreddine Gherabi, Abderrahim Marzouk: An enhanced method to compute the similarity between concepts of ontology, Springer International Publishing 2017 Advances in Intelligent Systems and Computing 640.
   Google Scholar
• Ge J., Qiu Y.: Concept Similarity Matching Based on Semantic Distance. In: 4th International Conference on Semantics, Knowledge, and Grid, pp. 380-383. IEEE (2008).
   Google Scholar
• Zhong, J., Zhu, H., Li, J., Yu, Y.: Conceptual Graph Matching for Semantic Search. In: Priss U., Corbett D., Angelova G. (Eds.): ICCS 2002, LNAI 2393, pp. 92-106. Springer, Heidelberg (2002).
   Google Scholar
• Ganjisaffar Y., Abolhassani H., Neshati M., Jamali M.: A Similarity Measure for OWL-S Annotated Web Services. In: International Conference on Web Intelligence, pp. 621-624. IEEE (2006).
   Google Scholar
• M. Dorigo, Optimization, learning and natural algorithms (in Italian), Ph.D. Thesis, Dipartimento di Elettronica, Politecnico di Milano, Italy, 1992.
   Google Scholar
• M. Dorigo, V. Maniezzo, A. Colorni, Positive feedback as a search strategy, Tech. Report 91-016, Dipartimento di Elettronica, Politecnico di Milano, Italy, 1991.
   Google Scholar
• G. Loshma, Nagaratna P Hedge, SAACO: Semantic Analysis based Ant Colony Optimization Algorithm for Efficient Text Document Clustering, International Journal of Recent Advances in Engineering & Technology (IJRAET), 2015
   Google Scholar
• Nisha Rathee, Rajender Singh Chhillar, Generation and Optimization of Test Paths Using Modified ACO, International Journal of Control Theory and Applications, 2017
   Google Scholar
• F. Giunchiglia, P. Shvaiko, and M. Yatskevich, “S-Match: an algorithm and an implementation of semantic matching,” Proceedings of 1^st European Semantic Web Symposium (ESWS), volume 3053 of LNCS, Springer, pp. 61-75, 2004.
   Google Scholar
• A. Madche and V. Zacharias, “Clustering ontology-based metadata in the semantic web,” Proceedings of 6th European Conference on Principles and Practice of Knowledge Discovery in Databases(PKDD), pp. 348-360, 2002.
   Google Scholar
• Jike Ge, Yuhui Qiu, “Concept Similarity Matching Based on Semantic Distance,” Fourth International Conference on Semantics, Knowledge, and Grid, IEEE Computer Society, 2008
   Google Scholar
• Z. Zhou, Y. Wang, and J. Gu. A new model of semantic similarity measuring in wordnet, ICSKE, pages 256–261, 2008.
   Google Scholar
• G. Zhu and C. A. Iglesias. Computing semantic similarity of concepts in knowledge graphs. TKDE, 29(1):72–85, 2017.
   Web of Science ®Google Scholar
• Linling M., Rubquing H.: A Review of semantic Similarity Measures in WordNet. International Journal of Hybrid Information Technology, January (2013).
   Google Scholar
• S. Anitha, Dr. J . Aklilandeswari, K. Menaga: A Survey on semantic similarity Measure. International Journal of Research in Advent Technology (2014).
   Google Scholar
• Ahmad F.: Compression of Ontology-Based Semantic –Similarity measure in Biomedical Text. Journal of Computer and Communications, Scientific Research Publishing (2017).
   Google Scholar
• Ming Mao. Ontology mapping: An information retrieval and interactive activation network-based approach. In Proc. ISWC, 2007.
   Google Scholar