Resource association discovery in semantic web

被引:0
|
作者
Liang, BY [1 ]
Tang, J [1 ]
Li, JZ [1 ]
Wang, KH [1 ]
机构
[1] Tsinghua Univ, Dept Comp Sci & Technol, Knowledge Engn Grp, Beijing, Peoples R China
关键词
D O I
暂无
中图分类号
TP18 [人工智能理论];
学科分类号
081104 ; 0812 ; 0835 ; 1405 ;
摘要
Resources on the web have direct and hidden relations. Direct relations mean the visible link between two resources like hyperlinks. Direct relations are easy to discover while hidden relations are not. Current discovery methods are mostly based on the text learning and user feedback methods. The text contents are not fit for inference and they are also lack of semantics. The web pages are annotated with ontolgoies in semantic web. The annotations are useful for inference. This paper proposes a framework for resource association discovery in semantic web. The framework uses the annotation for inference and the annotation hierarchy can be solved by mapping different ontologies. The experiment shows the satisfied results. Finally, the conclusion and future work are discussed.
引用
收藏
页码:266 / 269
页数:4
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