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AASA: a Method of Automatically Acquiring Semantic Annotations

Department of Computer Science and Engineering, Hohai University, State Key Laboratory of Novel Software Technology, Nanjing University, and Department of Mathematics, Nanjing University, China, lixinhan2002{at}yahoo.com.cn

Guihai Chen

State Key Laboratory of Novel Software Technology, Nanjing University, China

Li Xie

State Key Laboratory of Novel Software Technology, Nanjing University, China

An important precondition for the success of the Semantic Web is founded on the principle that the content of web pages will be semantically annotated. This paper proposes a method of automatically acquiring semantic annotations (AASA). In the AASA method, we employ a combination of data mining and optimization to acquire semantic annotations. Key features of AASA include combining association rules, inference mechanism, genetic algorithm and self-organizing map to create semantic annotations, and using the k-nearest-neighbor query combined with simulated annealing to maintain semantic annotations.

Key Words: annotation • Semantic Web • data mining • inference • optimization

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