doi: 10.4304/jsw.3.8.11-18
Automatic Discovery of Semantic Relations Based on Association Rule
- Joint Lab of Next-Generation Internet Interactive Computing, Shanghai University, Shanghai, China
Abstract
Automatic discovery of semantic relations between resources is a key issue in Web-based intelligent applications such as document understanding and Web services. This paper explores how to automatically discover the latent semantic relations and their properties based on the existing association rules. Through building semantic matrix by the association rules, four semantic relations can be extracted using union and intersection in set theory. By building a cyclic graph model, the transitive path of association relation is discovered. Document-level keywords and domain-level keywords as well as their parameters are analyzed to improve the discovery accuracy. Rules can be gained from the experiments to optimize the discovery processes for relations and properties. Further experiments validate the effectiveness and efficiency of the relation discovery algorithms, which can be applied in Web search, intelligent browsing and Web service composition.
Keywords
- Algorithm
- Association Rule
- Semantic Re
How to Cite
Xiangfeng Luo, Kai Yan, and Xue Chen, "Automatic Discovery of Semantic Relations Based on Association Rule," Journal of Software, vol. 3, no. 8, pp. 11-18, 2008. https://doi.org/ 10.4304/jsw.3.8.11-18
Copyright & License
Copyright © 2008 by the authors. This is an open access article distributed under the Creative Commons Attribution License which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited (CC BY 4.0).