ONTMAT: results for OAEI 2017

Keywords: Ontology matching, Ontology merging, disjoint knowledge, inconsistency, incompleteness, inconciseness, validation of mappings, verification of merged ontology.. 1

The system includes seven modules, i.e., Prepro- cess, Predicate Alignment, Mathcher Choosing, Candidate Pair Generation, Matching Score Calculation, Instance Alignment and

OntoConnect [3] is an ontology alignment system that uses an unsupervised machine learning technique that can predict similar source and target ontology classes based on

1: ontology loading, baseline matching and profiling, background knowledge match- ing (optional), extension matching and selection, property matching (conditional), and

Lily has three main matching functions: (1) Generic Ontology Matching (GOM) is used for common matching tasks with normal size ontologies.. (2) Large scale

Given two consistent ontologies, KOSIMap aligns entities in the source ontology to entities in the target ontology by extracting background knowledge about entities based on

Then we give new features in instance matching compared with traditional ontology matching (schema matching) and introduce the specific techniques we used for the 3 different

The Automated Semantic Mapping of Ontologies with Validation (ASMOV) algorithm for ontology alignment was one of the top performing algorithms in the 2007