Description of alignment implementation and benchmarking results

stuckenschmidt2005aThis deliverable presents the evaluation campaign carried out in 2005 and the improvement participants to these campaign and others have to their systems. We draw lessons from this work and proposes improvements for future campaigns

Falcon-AO: Aligning Ontologies with Falcon

Falcon-AO is an automatic tool for aligning ontologies. There are two matchers integrated in Falcon-AO: one is a matcher based on linguistic matching for ontologies, called LMO; the other is a matcher based on graph matching for ontologies, called GMO. In Falcon-AO, GMO takes the alignments generated by LMO as external input and outputs additional alignments. Reliable alignments are gained through LMO as well as GMO according to the concept of reliability. The reliability is obtained by observing the linguistic comparability and structural comparability of the two ontologies being compared. We have performed Falcon-AO on tests provided by OAEI 2005 campaign and got some preliminary results. In this paper, we describe the architecture and techniques of Falcon-AO in brief and present our results in more details. Finally, comments about test cases and lessons learnt from the campaign will be presented

GMO: A Graph Matching for Ontologies

Ontology matching is an important task to achieve interoperation between semantic web applications using different ontologies. Structural similarity plays a central role in ontology matching. However, the existing approaches rely heavily on lexical similarity, and they mix up lexical similarity with structural similarity. In this paper, we present a graph matching approach for ontologies, called GMO. It uses bipartite graphs to represent ontologies, and measures the structural similarity between graphs by a new measurement. Furthermore, GMO can take a set of matched pairs, which are typically previously found by other approaches, as external input in matching process. Our implementation and experimental results are given to demonstrate the effectiveness of the graph matching approach

Additional file 3: of Gut metagenomes of type 2 diabetic patients have characteristic single-nucleotide polymorphism distribution in Bacteroides coprocola

Phylogenetic trees of the 63 genes, except the top two, of the 65 genes with the most differentiated SNP distribution. Each tree is in a separate JPG file named by the GenBank accession of the corresponding gene. (RAR 13817 kb

Additional file 3: of Gut metagenomes of type 2 diabetic patients have characteristic single-nucleotide polymorphism distribution in Bacteroides coprocola

Phylogenetic trees of the 63 genes, except the top two, of the 65 genes with the most differentiated SNP distribution. Each tree is in a separate JPG file named by the GenBank accession of the corresponding gene. (RAR 13817 kb