Abstract
In this paper, we present HOME 2.0, an improved version of an ontology mapping tool that can create subject ontologies from subject curricula. To illustrate the design and test of the system we use a computer science curriculum. The semantic data of standard computer science topics can be created using synonyms of topics that are categorized in Wikipedia for mapping improvement of the relevant topics. The tool generates the curriculum data automatically into a course ontology with instances and properties, then finds the correspondences with a standard curriculum ontology using a combination of instance-based and structure-based ontology mapping techniques. The test results with sample data show that the tool works sufficiently and shows improved performance regarding results.
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Nuntawong, C., Namahoot, C.S., Brückner, M.: A semantic similarity assessment tool for computer science subjects using extended Wu & Palmer’s algorithm and ontology. In: Kim, K.J. (ed.) Information Science and Applications. LNEE, vol. 339, pp. 989–996. Springer, Heidelberg (2015)
Nuntawong, C., Namahoot, C.S., Brückner, M.: HOME: hybrid ontology mapping evaluation tool for computer science curricular. The Jurnal Teknologi, Malaysia (2016, to be published)
Wu, Z., Palmer, M.: Verb semantics and lexical selection. In: Proceeding of 32nd Annual Meeting of the Association for Computational Linguistics (ACL), Las Cruces, pp. 133–138 (1994)
Liu, X., Cao, L., Dai, W.: Overview of ontology mapping and approach. In: 4th IEEE International Conference on Broadband Network and Multimedia Technology (ICBNMT), 28-30 October 2011, pp. 592–595 (2011)
Octaviani, D., Pranolo, A., Othman, S.: RDB2Onto: an approach for creating semantic metadata from relational educational data. In: International Conference on Science in Information Technology (ICSITech), pp. 137–140 (2015)
Jin, T., Fu, Y., Lin, X., Liu, Q., Cui, Z.: A method of ontology mapping based on instance. In: 3rd International Conference on Intelligent Information Hiding and Multimedia Signal Processing, Kaohsiung, pp. 145–148 (2007)
Do, H. and Rahm, E.: COMA - A system for flexible combination of schema mapping approaches. In: Proceedings of the 28th VLDB Conference. pp. 610–621 (2002)
Noy, N. F., Musen, M.A.: Anchor-PROMPT: using non-local context for semantic mapping. In: Proceeding of Ontology and Information Sharing Workshop, IJCA (2001)
Zheng, C., Shen, Y., Mei, L.: Ontology mapping based on structures and instances. In: International Conference on Machine Learning and Cybernetics, vol. 1, Qingdao, pp. 460–465 (2010)
Singh, S., Cheah, Y.: Hybrid approach towards ontology mapping. In: International Symposium on Information Technology, vol. 3, Kuala Lumpur, pp. 1490–1493 (2010)
ACM and IEEE. Computer Science Curricular (2013). http://www.acm.org/education/curricularecommendation
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Nuntawong, C., Namahoot, C.S., Brückner, M. (2016). A Web Based Cooperation Tool for Evaluating Standardized Curricula Using Ontology Mapping. In: Luo, Y. (eds) Cooperative Design, Visualization, and Engineering. CDVE 2016. Lecture Notes in Computer Science(), vol 9929. Springer, Cham. https://doi.org/10.1007/978-3-319-46771-9_23
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DOI: https://doi.org/10.1007/978-3-319-46771-9_23
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