[1] Yin Kangyin, Song Zilin, Xu Ping,. Ontology mapping based on hidden Markov model [J]. Journal of Southeast University (English Edition), 2007, 23 (3): 389-393. [doi:10.3969/j.issn.1003-7985.2007.03.017]
Copy
Ontology mapping based on hidden Markov model(
)
)Journal of Southeast University (English Edition)[ISSN:1003-7985/CN:32-1325/N]
- Volumn:
- 23
- Issue:
- 2007 3
- Page:
- 389-393
- Research Field:
- Computer Science and Engineering
- Publishing date:
- 2007-09-30
Info
- Title:
- Ontology mapping based on hidden Markov model
- Author(s):
- Yin Kangyin1; Song Zilin1; Xu Ping2
-
1 Institute of Command Automation, PLA University of Science and Technology, Nanjing 210007, China
2 EMC Research and Measurement Center of Navy, Shanghai 200235, China
- PACS:
- TP311
- DOI:
- 10.3969/j.issn.1003-7985.2007.03.017
- Abstract:
- The existing ontology mapping methods mainly consider the structure of the ontology and the mapping precision is lower to some extent.According to statistical theory, a method which is based on the hidden Markov model is presented to establish ontology mapping.This method considers concepts as models, and attributes, relations, hierarchies, siblings and rules of the concepts as the states of the HMM, respectively.The models corresponding to the concepts are built by virtue of learning many training instances.On the basis of the best state sequence that is decided by the Viterbi algorithm and corresponding to the instance, mapping between the concepts can be established by maximum likelihood estimation.Experimental results show that this method can improve the precision of heterogeneous ontology mapping effectively.
References:
[1] Doan A, Madhavan J, Domingos P, et al.Learning to map between ontologies on the semantic web[C]//Proceedings of the 11th International World Wide Web Conference.Hawaii, 2002:662-673.
[2] Berners-Lee Tim, Hendeler James, Lassila Ora.The semantic web[J]. Scientific American, 2001, 284(5):35-43.
[3] Rodriguez M A, Egenhofer M J.Determining semantic similarity among entity classes from different ontologies[J].IEEE Transactions on Knowledge and Data Engineering, 2003, 15(2):442-456.
[4] Noy N F, Musen M A.The PROMPT site:interactive tools for ontology merging and mapping[J].International Journal of Human-Computer Studies, 2003, 59(6):983-1024.
[5] Madhavan Jayant, Bernstein Philip A, Rahm Erhard.Generic schema matching with cupid[C]//Proceedings of the 27th International Conference on Very Large Databases.Rome, Italy, 2001:129-138.
[6] Tang Jie, Liang Bangyong, Li Juanzi, et al.Automatic ontology mapping in semantic web[J].Chinese Journal of Computers, 2006, 29(11):1956-1976.(in Chinese)
[7] Rabiner Lawrence R.A tutorial on HMM and selected applications in speech recognition[J].Proceedings of the IEEE, 1989, 77(2):257-286.
[8] Forney G D.The viterbi algorithm [J].Proceedings of the IEEE, 1973, 61(3):268-278.
[9] Studer R, Benjamins V R, Fensel D.Knowledge engineering:principles and methods[J].Data and Knowledge Engineering, 1998, 25(1/2):161-197.
[10] Baum L E.An inequality and associated maximization technique in statistical estimation of probabilistic function of a Markov processes [J]. Inequalities, 1972, 3(1):1-8.
[11] Su Xiaomeng.A text categorization perspective for ontology mapping[R].Norway:Department of Computer and Information Science of Norwegian University of Science and Technology, 2002.
Memo
- Memo:
- Biographies: YinKangyin(1979—), male, graduate;Song Zilin(corresponding author), male, professor, zilinsong@sina.com.