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Inductive Logic Databases: From Extennsional to Intensional Knowledge

机译:归纳逻辑数据库:从Extennional达到密集知识

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Inductive Logic Programming (ILP) is a form of learning from examples that employs clausal logic as a representation formalism (Muggleton & De Raedt, 1994). Its goal is to generalise, relative to a given background theory, given extensional knowledge to obtain an intensional theory. The resulting theory may consist of a Horn clause predicate definition, or a set of clauses (possibly indefinite clauses or denials) describing relations between predicates. This corresponds well to the traditional distinction in deductive databases between view definitions and integrity constraints.
机译:归纳逻辑编程(ILP)是一种从雇用字幕逻辑作为代表性形式主义的示例的学习形式(Muggleton&De Raedt,1994)。 它的目标是概括,相对于给定的背景理论,给予延伸知识以获得密集理论。 得到的理论可以由霍恩子句谓词定义或一组条款(可能是无限条或拒绝)组成描述谓词之间的关系。 这对视图定义和完整性约束之间的演绎数据库中的传统区别很好。

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