Supervised Ontology and Instance Matching with MELT
Not on the map. Why?
Abstract (arXiv)
In this paper, we present MELT-ML, a machine learning extension to the Matching and EvaLuation Toolkit (MELT) which facilitates the application of supervised learning for ontology and instance matching. Our contributions are twofold: We present an open source machine learning extension to the matching toolkit as well as two supervised learning use cases demonstrating the capabilities of the new extension.
Key facts. Cited by 5 papers in the map (data through 7 Oct 2026). First posted on arXiv 20 Sep 2020.
Builds on
No reference list yet.
Built on by
Citing papers per year: 2021: 3; 2022: 1; 2023: 1.
5 papers.
- 2021Background Knowledge in Schema Matching: Strategy vs. Datacited by 3
- 2021FinMatcher at FinSim-2: Hypernym Detection in the Financial Services Domain using Knowledge Graphscited by 2
- 2021Matching with Transformers in MELTcited by 2
- 2022KERMIT -- A Transformer-Based Approach for Knowledge Graph Matchingcited by 1
- 2023An Embedding-based Approach to Inconsistency-tolerant Reasoning with Inconsistent Ontologiescited by 0
- 2023An Embedding-based Approach to Inconsistency-tolerant Reasoning with Inconsistent Ontologies4 Apr 2023
- 2022KERMIT -- A Transformer-Based Approach for Knowledge Graph Matching29 Apr 2022
- 2021Matching with Transformers in MELT15 Sep 2021
- 2021Background Knowledge in Schema Matching: Strategy vs. Data29 Jun 2021
- 2021FinMatcher at FinSim-2: Hypernym Detection in the Financial Services Domain using Knowledge Graphs2 Mar 2021