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Ontology learning from data models: Advance and the requirement for a database preparation and enrichment process

机译:来自数据模型的本体学习:提前和数据库准备和浓缩过程的要求

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Ontology learning field provides automatic and semi-automatic approaches for ontology generation. This process aims to overcome the manual knowledge acquisition process that is difficult, expensive and time-consuming. Several approaches have been emerged for this purpose. However, they are not practical on real-world databases and they are far from capturing all application semantics. This paper gives, first, an overview of the ontology learning process and the peculiarities of relational models. Then, it discusses the advance in this filed according to a developed framework before presenting two main lacks: the requirement of a database preparation process and an enrichment process.
机译:本体学习领域为本体生成提供自动和半自动方法。该过程旨在克服难以,昂贵且耗时的手工知识获取过程。为此目的出现了几种方法。但是,它们对现实世界数据库并不实用,并且远远不捕获所有应用语义。本文首先给出了本体学习过程和关系模型的特点概述。然后,在提出两个主要缺乏之前,它根据发达的框架讨论了这一提交的提交:数据库准备过程的要求和丰富的过程。

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