The semantic web progress gave rise to a growing number of ontologies in various fields. In order to allow knowledge reuse, ontology matching is an interesting option. In this paper, we propose an ontology matching system that performs class, property and instance matching. This latter is usually achieved by means of Natural Language Processing (NLP) techniques, which are context dependent. To avoid the limits of NLP, we use a decision tree-based instance matching scheme. Decision tree is one of the most widely used learning algorithms for inductive inference and classification. Our system works on OWL-DL ontologies, that is ontologies expressed in the Description Logic version of the Ontology Web Language. This ensures the maximum of expressiveness, completeness and decidability. Our approach is tested with the benchmark and conference tracks of the OAEI'2015 campaign. It shows very promising results since it outperforms other matching systems in most of the test cases.
الكلمات المفتاحية :
Ontology matching
Instance matching
OWL-DL
Linguistic similarity
WordNet
Decision trees
Weka
Semantic web
Knowledge reuse
S. Amrouch, S. Mostefai and M. Fahad. 2016. Decision trees in automatic ontology matching. International Journal of Metadata, Semantics and Ontologies (IJMSO), 11, 3 (January 2016), Inderscience, 180-190. DOI: https://doi.org/10.1504/IJMSO.2016.081585.
APA :
Amrouch, S., Mostefai, S. & Fahad, M. (2016, January). Decision trees in automatic ontology matching. International Journal of Metadata, Semantics and Ontologies (IJMSO), 11(3), Inderscience, 180-190. DOI: https://doi.org/10.1504/IJMSO.2016.081585
IEEE :
S. Amrouch, S. Mostefai and M. Fahad, "Decision trees in automatic ontology matching". International Journal of Metadata, Semantics and Ontologies (IJMSO), vol. 11, no. 3, Inderscience, pp. 180-190, January, 2016. DOI: https://doi.org/10.1504/IJMSO.2016.081585.
BibTeX :
@article{misc-lab-237, author = {Amrouch, Siham and Mostefai, Sihem and Fahad, Muhammad}, title = {Decision trees in automatic ontology matching}, journal = {International Journal of Metadata, Semantics and Ontologies (IJMSO)}, volume = {11}, number = {3}, issn = {1744-2621}, pages = {180--190}, publisher = {Inderscience}, year = {2016}, month = {January}, doi = {10.1504/IJMSO.2016.081585}, url = {https://doi.org/10.1504/IJMSO.2016.081585}, keywords = {ontology matching, instance matching, OWL-DL, linguistic similarity, wordNet, decision trees, Weka, semantic web, knowledge reuse} }
RIS :
TI - Decision trees in automatic ontology matching AU - S. Amrouch AU - S. Mostefai AU - M. Fahad PY - 2016 SN - 1744-2621 JO - International Journal of Metadata, Semantics and Ontologies (IJMSO) VL - 11 IS - 3 SP - 180 EP - 190 PB - Inderscience AB - The semantic web progress gave rise to a growing number of ontologies in various fields. In order to allow knowledge reuse, ontology matching is an interesting option. In this paper, we propose an ontology matching system that performs class, property and instance matching. This latter is usually achieved by means of Natural Language Processing (NLP) techniques, which are context dependent. To avoid the limits of NLP, we use a decision tree-based instance matching scheme. Decision tree is one of the most widely used learning algorithms for inductive inference and classification. Our system works on OWL-DL ontologies, that is ontologies expressed in the Description Logic version of the Ontology Web Language. This ensures the maximum of expressiveness, completeness and decidability. Our approach is tested with the benchmark and conference tracks of the OAEI'2015 campaign. It shows very promising results since it outperforms other matching systems in most of the test cases. KW - ontology matching KW - instance matching KW - OWL-DL KW - linguistic similarity KW - wordNet KW - decision trees KW - Weka KW - semantic web KW - knowledge reuse DO - 10.1504/IJMSO.2016.081585 UR - https://doi.org/10.1504/IJMSO.2016.081585 ID - misc-lab-237 ER -