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An Effective Approach for Association Identification in Real Scenarios

机译:真实场景中关联识别的有效方法

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The semantic web is an extension of current web. It is gaining the interests of researcher from few years. The aim of this web is to make web meaningful, understandable and machine processable. Making use of information on current web for the productiveness of future web is becoming vital. Heterogeneity of relational data coupled with present web complicates utilization of information for future web. To use the data associated with current web we need it to transform it into ontology. The already presented and provided algorithms merely give the result in user required form. This paper presents a scheme for the identification of association in real scenarios, where there can be very little metadata availability.`
机译:语义网是当前网的扩展。几年来它正在引起研究者的兴趣。该Web的目的是使Web有意义,易于理解和可机器处理。利用当前网络上的信息来提高未来网络的生产力变得至关重要。关系数据的异质性加上当前的网络使将来的网络信息的利用变得复杂。要使用与当前Web相关的数据,我们需要将其转换为本体。已经提出和提供的算法仅以用户要求的形式给出结果。本文提出了一种在真实场景中识别关联的方案,在这种情况下,元数据的可用性非常低。

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