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AUGMENTED EXPLORATION FOR BIG DATA AND BEYOND

机译:大数据的扩展探索和超越

摘要

A computer is to obtain specification concept graphs of nodes spec1, spec2, . . . , specm including concept nodes and relation nodes according to at least one of a plurality of digitized data from a plurality of computerized data sources forming a first set of evidences U and obtain concept graphs of nodes cα1, cα2, . . . , cαn including concept nodes and relation nodes for corresponding obtained plurality of information and knowledge (IKs) α1,α2, . . . , αn forming a second set of evidences U. A subset of concept graphs of nodes is selected from cα1, cα2, . . . , cαn according to a computable measure of consistency, inconsistency and/or priority threshold between cαj in cα1, cα2, . . . , cαn can to specification concept graph speck in spec1, spec2, . . . , spec m. Knowledge fragments are generated for corresponding subset of concept graphs cαi1, cαi2, . . . , cαih include augmenting information objects by creating or adding into at least one knowledge-base (KB), new objects in form ω=E→A from the concept; fragments, including a computed validity (v) and a plausibility (p) for a combination of relationship constraints k for the concept fragments and obtained propositions k for the fragment concepts.
机译:计算机将获得节点spec1,spec2,...的规范概念图。 。 。包括概念节点和关系节点的样本根据来自形成第一组证据U的多个计算机化数据源的多个数字化数据中的至少一个而获得,并获得节点cα1,cα2,...的概念图。 。 。包括概念节点和关系节点,用于相应获得的多个信息和知识(IK)α1,α2,...,cαn。 。 。 ,形成第二组证据U。从cα1,cα2,...中选择节点概念图的子集。 。 。 ,cαn,cαn,cαn之间的一致性,不一致和/或优先级阈值的可计算量度。 。 。 ,可以在spec1,spec2,...中指定概念图speck。 。 。 ,规格m。为概念图cαi1,cαi2,...的对应子集生成知识片段。 。 。包括通过从概念中创建或添加到至少一个知识库(KB)中以ω= E→A形式的新对象来增强信息对象;片段,包括针对概念片段的关系约束k和针对片段概念获得的命题k的组合的计算的有效性(v)和似真性(p)。

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