Truveta Mapper: A Zero-shot Ontology Alignment Framework

• URL: http://arxiv.org/abs/2301.09767v3
• Date: Tue, 22 Aug 2023 00:22:42 GMT
• Title: Truveta Mapper: A Zero-shot Ontology Alignment Framework
• Authors: Mariyam Amir, Murchana Baruah, Mahsa Eslamialishah, Sina Ehsani, Alireza Bahramali, Sadra Naddaf-Sh, Saman Zarandioon
• Abstract summary: A new perspective is suggested for unsupervised Ontology Matching (OM) or Ontology Alignment (OA) The proposed framework, Truveta Mapper (TM), leverages a multi-task sequence-to-sequence transformer model to perform alignment across multiple in a zero-shot, unified and end-to-end manner. TM is pre-trained and fine-tuned only on publicly available corpus text and inner-ontologies data.
• Score: 3.5284865194805106
• License: http://creativecommons.org/licenses/by-nc-sa/4.0/
• Abstract: In this paper, a new perspective is suggested for unsupervised Ontology Matching (OM) or Ontology Alignment (OA) by treating it as a translation task. Ontologies are represented as graphs, and the translation is performed from a node in the source ontology graph to a path in the target ontology graph. The proposed framework, Truveta Mapper (TM), leverages a multi-task sequence-to-sequence transformer model to perform alignment across multiple ontologies in a zero-shot, unified and end-to-end manner. Multi-tasking enables the model to implicitly learn the relationship between different ontologies via transfer-learning without requiring any explicit cross-ontology manually labeled data. This also enables the formulated framework to outperform existing solutions for both runtime latency and alignment quality. The model is pre-trained and fine-tuned only on publicly available text corpus and inner-ontologies data. The proposed solution outperforms state-of-the-art approaches, Edit-Similarity, LogMap, AML, BERTMap, and the recently presented new OM frameworks in Ontology Alignment Evaluation Initiative (OAEI22), offers log-linear complexity, and overall makes the OM task efficient and more straightforward without much post-processing involving mapping extension or mapping repair. We are open sourcing our solution.

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