%0 Journal Article %1 8731854 %A Chen, J. %A Xue, X. %A Huang, Y. %A Zhang, X. %D 2019 %J IEEE Access %K matching ontology %P 1-1 %R 10.1109/ACCESS.2019.2920881 %T Interactive Cross-Lingual Ontology Matching %U https://ieeexplore.ieee.org/document/8731854/ %X Recently, with the growing number of ontologies defined in different languages, to bridge the semantic gaps between them, it is necessary to identify the correspondences between their heterogeneous entities, so-called cross-lingual ontology matching. Due to the complexity and intricacy of the cross-lingual ontology matching, it is essential to get an expert involved in the matching process to guarantee the alignment’s quality. In this work, we propose an interactive cross-lingual ontology matching technique, which makes the user and automatic matcher work together to create high-quality alignments in a reasonable amount of time. In particular, we present a cross-lingual similarity metric to calculate the similarity value of two cross-lingual entities, construct an optimal model for the cross-lingual ontology matching problem, propose an Interactive Compact Differential Evolution (ICDE) algorithm to effectively match the cross-lingual ontologies. The experiment exploits Ontology Alignment Evaluation Initiative (OAEI)’s Multifarm track to test our proposal’s performance. The experimental results show that ICDE significantly outperforms other EA-based matchers and OAEI’s participants, and the interacting mechanism can significantly improve the alignment’s quality.

@article{8731854, abstract = {Recently, with the growing number of ontologies defined in different languages, to bridge the semantic gaps between them, it is necessary to identify the correspondences between their heterogeneous entities, so-called cross-lingual ontology matching. Due to the complexity and intricacy of the cross-lingual ontology matching, it is essential to get an expert involved in the matching process to guarantee the alignment’s quality. In this work, we propose an interactive cross-lingual ontology matching technique, which makes the user and automatic matcher work together to create high-quality alignments in a reasonable amount of time. In particular, we present a cross-lingual similarity metric to calculate the similarity value of two cross-lingual entities, construct an optimal model for the cross-lingual ontology matching problem, propose an Interactive Compact Differential Evolution (ICDE) algorithm to effectively match the cross-lingual ontologies. The experiment exploits Ontology Alignment Evaluation Initiative (OAEI)’s Multifarm track to test our proposal’s performance. The experimental results show that ICDE significantly outperforms other EA-based matchers and OAEI’s participants, and the interacting mechanism can significantly improve the alignment’s quality.}, added-at = {2019-06-08T21:03:18.000+0200}, author = {{Chen}, J. and {Xue}, X. and {Huang}, Y. and {Zhang}, X.}, biburl = {https://www.bibsonomy.org/bibtex/2e25695af2efc954a7874615356fcb2a8/jorgemart}, doi = {10.1109/ACCESS.2019.2920881}, interhash = {68021ea108aa8c63ae5fb541d14ee67c}, intrahash = {e25695af2efc954a7874615356fcb2a8}, issn = {2169-3536}, journal = {IEEE Access}, keywords = {matching ontology}, pages = {1-1}, timestamp = {2019-06-10T15:37:47.000+0200}, title = {Interactive Cross-Lingual Ontology Matching}, url = {https://ieeexplore.ieee.org/document/8731854/}, year = 2019 }