|
|
|
| Optimization Algorithm for Edge-Based Semantic Similarity Calculation |
| WANG Zhi-Xiao1,2,ZHANG Da-Lu1 |
1.Department of Computer Science and Engineering,Tongji University,Shanghai 201804
2.College of Computer Science and Technology,China University of Mining and Technology,Xuzhou 221116 |
|
|
|
|
Abstract Concept semantic similarity calculation is a problem in applications. To simplify the single ontology concept semantic similarity calculation, an optimization algorithm for edge-based similarity calculation is put forward. It utilizes hierarchical relationship between concepts to simplify calculation process. Based on the semantic similarity between a pair of ontology concepts, the optimization algorithm gives all semantic similarity between each pair of ontology concepts. Results of simulation experiments show that the calculation complexity is reduced considerably, and the similarity calculation speed is improved by a factor of two.
|
|
Received: 07 April 2009
|
|
|
|
|
|
[1] Li Yuhua, Bandar Z A, Mclean D. An Approach for Measuring Semantic Similarity between Words Using Multiple Information Sources. IEEE Trans on Knowledge and Data Engineering, 2003, 15(4): 871-882
[2] Budanitsky A, Hirst G. Evaluating WordNet-Based Measures of Semantic Distance. Computational Linguistics, 2006, 32(1): 13-47
[3] Nauer E, Napoli A. A Proposal for Annotation, Semantic Similarity and Classification of Textual Documents // Proc of the 12th International Conference on Artificial Intelligence: Methodology, Systems and Applications. Varna, Bulgaria, 2006: 201-212
[4] Hliaoutakis A, Varelas G, Voutsakis E, et al. Information Retrieval by Semantic Similarity. International Journal on Semantic Web and Information Systems, 2006, 2(3): 55-73
[5] Islam A, Inkpen D, Kiringa I. Applications of Corpus-Based Semantic Similarity and Word Segmentation to Database Schema Matching. The VLDB Journal-The International Journal on Very Large Data Bases, 2008, 17(5): 1293-1320
[6] Wang Junli, Ding Zhijun, Jiang Changjun, et al. Similarity Based Ontology Matching Using Genetic Algorithm. Chinese Journal of Electronics, 2007, 16(4): 665-670
[7] Resnik P. Using Information Content to Evaluate Semantic Similarity in Taxonomy // Proc of the 14th International Joint Conference on Artificial Intelligence. Montreal, Canada, 1995: 448-453
[8] Wu Zhibiao, Palmer M. Verb Semantics and Lexical Selection // Proc of the 32nd Annual Meeting of the Associations for Computational Linguistics. Las Cruces, New Mexico, 1994: 133-138
[9] Leacock C, Chodorow M. Combining Local Context and WordNet Similarity for Word Sense Identification // Felbaum C, ed. WordNet: An Electronic Lexical Database. Cambridge, USA: MIT Press, 1998: 265-283
[10] Hliaoutakis A. Semantic Similarity Measures in MeSH Ontology and Their Application to Information Retrieval on Medline [EB/OL]. [2009-01-10]. http://www.intelligence.tuc.gr/publications/Hliautakis.pdf
[11] Coulter N, French J, Glinert E, et al. The ACM Computing Classification System [DB/OL]. [2009-02-15]. http://www.acm.org/about/class/1998
[12] Stanford University . Protégé Ontology Library [DB/OL]. [2008-12-01]. http://protegewiki.stanford.edu/index.php/P-rotege_Ontology_Library |
|
|
|
2010, Vol. 23 
