Alignment results of SOBOM for OAEI 2010

In this paper we give a brief explanation of how Sub-Ontology based Ontology Matching (SOBOM) method gets the alignment results at OAEI2010. SOBOM deal with an ontology from two different views: an ontology with is-a hierarchical structure O’ and an ontology with other relationships O’’. Firstly, from the O’ view, SOBOM starts with a set of anchors provided by a linguistic matcher. And then it extracts sub-ontologies based on the anchors and ranks these sub-ontologies according to their depths. Secondly, SOBOM utilizes Semantic Inductive Similarity Flooding algorithm to compute the similarity of concepts between different sub-ontologies derived from the two ontologies according the depth of sub-ontologies to get concept alignments. Finally, from the O’’ view, SOBOM gets relationship alignments by using the concept alignment results in O’’. The experiment results show SOBOM can find more alignment results than other compared relevant methods. 1 System presentation Currently more and more ontologies are distributedly built and used by different organizations. And these ontologies are usually light-weighted [1] containing lots of concepts especially in biomedicine, such as anatomy taxonomy NCI Thesaurus. The Sub-ontology based Ontology Matching (SOBOM) is designed for matching lightweight ontologies that has is-a hierarchy as their backbones. It matches an ontology from two views: O’ and O’’ that are depicted in Fig. 1. The unique feature of our method is combining sub-ontology extraction with ontology matching. 1.1 State, purpose, general statement SOBOM is developed to match ontology automatically for general purpose. Based on two different views, we design three elementary matchers in current version. The first one is a anchor generator which is used to find anchors; the second one is a structure matcher SISF (Semantic Inductive Similarity Flooding) which is inspired by AnchorPrompt [3] and SF [4] algorithms and is exploited to flood similarity among concepts. The last one is a relationship matcher which utilizes the results of SISF to get relationship alignments. In addition, a Sub-ontology Extractor (SoE) is integrated into SOBOM to extract sub-ontologies according to the anchors got by linguistic matcher and rank them by their depths descendingly. Overall SOBOM is a sequential method, so it does not care how to combine the results of different matchers. The overview of the method is illustrated in Fig. 2.