AASA: a Method of Automatically Acquiring Semantic Annotations

Authors:
Lixin Han;Guihai Chen;Li Xie
Affiliations:
Department of Computer Science and Engineering, HohaiUniversity, State Key Laboratory of Novel Software Technology, Nanjing University,and Department of Mathematics, Nanjing University, China;State Key Laboratory of Novel Software Technology, NanjingUniversity, China;State Key Laboratory of Novel Software Technology, NanjingUniversity, China
Venue:
Journal of Information Science
Year:
2007

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Abstract

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.