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OntoDM: An Ontology of Data Mining

机译:OntoDM:数据挖掘的本体论

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摘要

Motivated by the need for unification of the field of data mining and the growing demand for formalized representation of outcomes of research, we address the task of constructing an ontology of data mining. The proposed ontology, named OntoDM, is based on a recent proposal of a general framework for data mining, and includes definitions of basic data mining entities, such as datatype and dataset, data mining task, data mining algorithm and components thereof (e.g., distance function), etc. It also allows for the definition of more complex entities, e.g., constraints in constraint-based data mining, sets of such constraints (inductive queries) and data mining scenarios (sequences of inductive queries). Unlike most existing approaches to constructing ontologies of data mining, OntoDM is a deep/heavy-weight ontology and follows best practices in ontology engineering, such as not allowing multiple inheritance of classes, using a predefined set of relations and usinga top level ontology.
机译:出于对数据挖掘领域统一的需求以及对研究成果的形式化表示的日益增长的推动,我们解决了构建数据挖掘本体的任务。所提议的名为OntoDM的本体基于数据挖掘通用框架的最新提议,并且包括基本数据挖掘实体的定义,例如数据类型和数据集,数据挖掘任务,数据挖掘算法及其组成部分(例如,距离)。还可以定义更复杂的实体,例如,基于约束的数据挖掘中的约束,此类约束的集合(归纳查询)和数据挖掘方案(归纳查询的序列)。与大多数现有的构建数据挖掘本体的方法不同,OntoDM是深度/重量级本体,它遵循本体工程中的最佳实践,例如,不允许使用预定的一组关系和顶层本体来进行类的多重继承。

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