Anatomy Ontology Matching Using Markov Logic Networks
Joint Authors
Cui, Zhiming
Li, Chunhua
Zhao, Pengpeng
Wu, Jian
Source
Issue
Vol. 2016, Issue 2016 (31 Dec. 2016), pp.1-7, 7 p.
Publisher
Hindawi Publishing Corporation
Publication Date
2016-06-13
Country of Publication
Egypt
No. of Pages
7
Main Subjects
Abstract EN
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.
American Psychological Association (APA)
Li, Chunhua& Zhao, Pengpeng& Wu, Jian& Cui, Zhiming. 2016. Anatomy Ontology Matching Using Markov Logic Networks. Scientifica،Vol. 2016, no. 2016, pp.1-7.
https://search.emarefa.net/detail/BIM-1117516
Modern Language Association (MLA)
Li, Chunhua…[et al.]. Anatomy Ontology Matching Using Markov Logic Networks. Scientifica No. 2016 (2016), pp.1-7.
https://search.emarefa.net/detail/BIM-1117516
American Medical Association (AMA)
Li, Chunhua& Zhao, Pengpeng& Wu, Jian& Cui, Zhiming. Anatomy Ontology Matching Using Markov Logic Networks. Scientifica. 2016. Vol. 2016, no. 2016, pp.1-7.
https://search.emarefa.net/detail/BIM-1117516
Data Type
Journal Articles
Language
English
Notes
Includes bibliographical references
Record ID
BIM-1117516