Semantic data mining: A survey of ontology-based approaches

D. Dou, Hao Wang, Haishan Liu
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引用次数: 156

Abstract

Semantic Data Mining refers to the data mining tasks that systematically incorporate domain knowledge, especially formal semantics, into the process. In the past, many research efforts have attested the benefits of incorporating domain knowledge in data mining. At the same time, the proliferation of knowledge engineering has enriched the family of domain knowledge, especially formal semantics and Semantic Web ontologies. Ontology is an explicit specification of conceptualization and a formal way to define the semantics of knowledge and data. The formal structure of ontology makes it a nature way to encode domain knowledge for the data mining use. In this survey paper, we introduce general concepts of semantic data mining. We investigate why ontology has the potential to help semantic data mining and how formal semantics in ontologies can be incorporated into the data mining process. We provide detail discussions for the advances and state of art of ontology-based approaches and an introduction of approaches that are based on other form of knowledge representations.
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语义数据挖掘:基于本体的方法综述
语义数据挖掘是指将领域知识,特别是形式语义系统地融入到数据挖掘过程中的数据挖掘任务。在过去,许多研究工作已经证明了将领域知识纳入数据挖掘的好处。与此同时,知识工程的发展丰富了领域知识家族,特别是形式语义和语义Web本体。本体是一种明确的概念化规范,是定义知识和数据语义的形式化方法。本体的形式化结构使其成为数据挖掘领域知识编码的一种自然方式。在本文中,我们介绍了语义数据挖掘的一般概念。我们研究了本体为什么有潜力帮助语义数据挖掘,以及如何将本体中的形式语义纳入数据挖掘过程。我们详细讨论了基于本体论的方法的进展和现状,并介绍了基于其他形式的知识表示的方法。
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