SANOM results for OAEI 2019 Simulated annealingbased ontology matching (SANOM) participates for the second time at the ontology alignment evaluation initiative (OAEI) 2019. This paper contains the configuration of SANOM and its results on the anatomy and conference tracks. In comparison to the OAEI 2017, SANOM has improved significantly, and its results are competitive with the stateoftheart systems. In particular, SANOM has the highest recall rate among the participated systems in the conference track, and is competitive with AML, the best performing system, in terms of Fmeasure. SANOM is also competitive with LogMap on the anatomy track, which is the best performing system in this track with no usage of particular biomedical background knowledge. SANOM has been adapted to the HOBBIT platfrom and is now available for the registered users. abstract environment.

Towards Association RuleBased Complex Ontology Alignment Ontology alignment has been studied for over a decade, and over that time many alignment systems have been developed by researchers in order to find simple 1to1 equivalence alignments between ontologies. However, finding complex alignments, i.e., alignments that are not simple class or property equivalences, is a topic largely unexplored but with growing significance. Currently, establishing a complex alignment requires domain experts to work together to manually generate the alignment, which is extremely timeconsuming and laborintensive. In this paper, we propose an automated method based on association rule mining to detect not only simple alignments, but also more complex alignments between ontologies. Our algorithm can also be used in a semiautomated fashion to effectively assist users in finding potential complex alignments which they can then validate or edit. In addition, we evaluate the performance of our algorithm on the complex alignment benchmark of the Ontology Alignment Evaluation Initiative (OAEI).