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Extending the Expression Ability of LAV Using Ontology Technique

机译:利用本体技术扩展LAV的表达能力

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Information fusion is an interdisciplinary research field aiming to combine and merge the information or data from different information sources. The output of information fusion system is a global schema through which users can get information or data from different dispersed sources. To generate a deep Web information fusion system is facing many challenges, because the nature of Web is different from those of traditional databases and multi-databases. The major challenge in a deep Web information fusion system is the data source modeling problem, which determine the technical method of the whole system. The query interfaces provided by the deep Web are the clues to disclose the hidden schemas. But the complicated semantic relationships in the query interfaces lead to the lower generality and ability of local as view (LAV) method in the traditional information fusion system. We present an approach that the semantic relationships between semantic related attributes can be evaluated by the WordNet, a kind of ontology instrument. The experiment is carried out on the famous dataset, and the result shows the efficiency of ontology extended LAV of building mappings between local views and mediator schema.
机译:信息融合是一个跨学科研究领域,其旨在组合并合并来自不同信息来源的信息或数据。信息融合系统的输出是全局模式,用户可以通过该架构获取来自不同分散源的信息或数据。为了生成深网络信息融合系统面临着许多挑战,因为网络的性质与传统数据库和多数据库的性质不同。深度Web信息融合系统中的主要挑战是数据源建模问题,可确定整个系统的技术方法。 Deep Web提供的查询接口是披露隐藏模式的线索。但是,查询接口中的复杂语义关系导致了传统信息融合系统中的局部视图(LAV)方法的较低的界限和能力。我们提出了一种方法,即语义相关属性之间的语义关系可以由Wordnet,一种本体仪器评估。实验是在着名的数据集上进行的,结果显示了本地视图与中介模式之间建筑映射的本体延长莱尔科的效率。

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