A mapping method between EXPRESS and OWL based on text similarity analysis
| Autor: | QingQuan Jian, Yan Liu |
|---|---|
| Rok vydání: | 2021 |
| Předmět: |
Computer science
Process (engineering) business.industry Semantic analysis (machine learning) Ontology (information science) computer.software_genre Semantics Knowledge sharing Schema (genetic algorithms) Similarity (psychology) Artificial intelligence business computer Natural language processing Data integration |
| Zdroj: | 2021 International Conference on Electronic Information Engineering and Computer Science (EIECS). |
| DOI: | 10.1109/eiecs53707.2021.9588116 |
| Popis: | To translate product data described by STEP to Ontology models can enhance data integration and knowledge sharing among different platforms throughout the product lifecycle. This translation process requires mapping between two languages, i.e. EXPRESS for STEP and OWL for ontology. However, limited research has explored the automatic way of determining the mapping relationships. This paper introduces a model to measure the semantic textual similarity score between the official reference manuals that explains EXPRESS and OWL. Based on the model, a method is proposed to automatically find the mapping relationships between the two languages. The experiment shows that the proposed model achieves better performance comparing with other pre-trained models on the STS-B dataset. Furthermore, this semantic analysis based method is not specific to any EXPRESS schema so that this paper gets more general purpose conversion rules of mapping EXPRESS to OWL. |
| Databáze: | OpenAIRE |
| Externí odkaz: |
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