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Heuristics for automated knowledge source integration and service composition

机译:用于自动知识源集成和服务组合的启发式

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The NP-hard component set identification problem is a combinatorial problem arising in the context of knowledge discovery, information integration, and knowledge source/service composition. Considering a granular knowledge domain consisting of a large number of individual bits and pieces of domain knowledge (properties) and a large number of knowledge sources and services that provide mappings between sets of properties, the objective of the component set identification problem is to select a minimum cost combination of knowledge sources that can provide a joint mapping from a given set of initially available properties (initial knowledge) to a set of initially unknown properties (target knowledge). We provide a general framework for heuristics and consider construction heuristics that are followed by local improvement heuristics. Computational results are reported on randomly generated problem instances.
机译:NP硬组件集标识问题是在知识发现,信息集成和知识源/服务组合的背景下出现的组合问题。考虑到一个粒度知识领域,它由大量单个领域的知识点(属性)和大量知识源和提供属性集之间映射的服务组成,因此组件集识别问题的目的是选择一个可以提供从给定的一组初始可用属性(初始知识)到一组初始的未知属性(目标知识)的联合映射的知识源的最低成本组合。我们提供了启发式方法的一般框架,并考虑了构建启发式方法,然后是本地改进启发式方法。在随机生成的问题实例上报告计算结果。

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