title: Anatomy Ontology Matching Using Markov Logic Networks.
abstract: The anatomy of model species is described in ontologies, which are used to standardize the annotations of experimental data, such as gene expression patterns. To compare such data between species, we need to establish relationships between ontologies describing different species. Ontology matching is a kind of solutions to find semantic correspondences between entities of different ontologies. Markov logic networks which unify probabilistic graphical model and first-order logic provide an excellent framework for ontology matching. We combine several different matching strategies through first-order logic formulas according to the structure of anatomy ontologies. Experiments on the adult mouse anatomy and the human anatomy have demonstrated the effectiveness of proposed approach in terms of the quality of result alignment.
authors.affiliation: School of Computer Science and Technology, Soochow University, Suzhou 215006, China.
authors.forename: Chunhua
authors.initials: C
authors.lastname: Li
authors.affiliation: School of Computer Science and Technology, Soochow University, Suzhou 215006, China.
authors.forename: Pengpeng
authors.initials: P
authors.lastname: Zhao
authors.affiliation: School of Computer Science and Technology, Soochow University, Suzhou 215006, China.
authors.forename: Jian
authors.initials: J
authors.lastname: Wu
authors.affiliation: School of Computer Science and Technology, Soochow University, Suzhou 215006, China.
authors.forename: Zhiming
authors.initials: Z
authors.lastname: Cui