Identifying and validating ontology mappings by formal concept analysis

As a well developed mathematical model for analyzing individuals and structuring concepts, Formal Concept Analysis (FCA) has been applied to ontology matching (OM) tasks since the beginning of OM research, whereas ontological knowledge exploited in FCA-based methods is limited. The study in this paper aims to empowering FCA with as much as ontological knowledge as possible for identifying and validating mappings across ontologies. Our method, called FCA-Map, constructs three types of formal contexts and extracts mappings from the lattices derived. Firstly, the token-based formal context describes how class names, labels and synonyms share lexical tokens, leading to lexical mappings (anchors) across ontologies. Secondly, the relation-based formal context describes how classes are in taxonomic, partonomic and disjoint relationships with the anchors, leading to positive and negative structural evidence for validating the lexical matching. Lastly, after incoherence repair, the positive relationbased context can be used to discover additional structural mappings. Evaluation on anatomy track and large biomedical ontologies track of the 2015 Ontology Alignment Evaluation Initiative (OAEI) campaign demonstrates the effectiveness of FCA-Map and its competitiveness with 2015 OAEI top-ranked OM systems.