To solve the problems of shaving and reusing information in the information system, a rules-based ontology constructing approach from object-relational databases is proposed. A 3-tuple ontology constructing model is p...To solve the problems of shaving and reusing information in the information system, a rules-based ontology constructing approach from object-relational databases is proposed. A 3-tuple ontology constructing model is proposed first. Then, four types of ontology constructing rules including class, property, property characteristics, and property restrictions ave formalized according to the model. Experiment results described in Web ontology language prove that our proposed approach is feasible for applying in the semantic objects project of semantic computing laboratory in UC Irvine. Our approach reduces about twenty percent constructing time compared with the ontology construction from relational databases.展开更多
使用SWRL(Semantic Web Rule Language)描述的数据蕴含了更多的语义信息,SWRL数据集上的数据挖掘过程必须充分考虑数据的语义特征。已有的关于这种类型数据的候选频繁模式生成方法可能产生大量无意义的模式,加重了模式评价过程的计算负...使用SWRL(Semantic Web Rule Language)描述的数据蕴含了更多的语义信息,SWRL数据集上的数据挖掘过程必须充分考虑数据的语义特征。已有的关于这种类型数据的候选频繁模式生成方法可能产生大量无意义的模式,加重了模式评价过程的计算负担。针对这一缺陷提出了基于向下求精规则和相容谓词的候选频繁模式生成方法,同时定义了谓词数量约束,从而避免产生过多的非频繁模式和冗余模式。实验证明该方法可提高频繁模式生成的效率。展开更多
基金supported by the National Natural Science Foundation of China (60471055)the National "863" High Technology Research and Development Program of China (2007AA01Z443)
文摘To solve the problems of shaving and reusing information in the information system, a rules-based ontology constructing approach from object-relational databases is proposed. A 3-tuple ontology constructing model is proposed first. Then, four types of ontology constructing rules including class, property, property characteristics, and property restrictions ave formalized according to the model. Experiment results described in Web ontology language prove that our proposed approach is feasible for applying in the semantic objects project of semantic computing laboratory in UC Irvine. Our approach reduces about twenty percent constructing time compared with the ontology construction from relational databases.
文摘使用SWRL(Semantic Web Rule Language)描述的数据蕴含了更多的语义信息,SWRL数据集上的数据挖掘过程必须充分考虑数据的语义特征。已有的关于这种类型数据的候选频繁模式生成方法可能产生大量无意义的模式,加重了模式评价过程的计算负担。针对这一缺陷提出了基于向下求精规则和相容谓词的候选频繁模式生成方法,同时定义了谓词数量约束,从而避免产生过多的非频繁模式和冗余模式。实验证明该方法可提高频繁模式生成的效率。
