DocumentCode :
1866780
Title :
Semantic data mining: A survey of ontology-based approaches
Author :
Dejing Dou ; Hao Wang ; Haishan Liu
Author_Institution :
Comput. & Inf. Sci., Univ. of Oregon, Eugene, OR, USA
fYear :
2015
fDate :
7-9 Feb. 2015
Firstpage :
244
Lastpage :
251
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.
Keywords :
data mining; ontologies (artificial intelligence); semantic Web; semantic networks; data mining tasks; domain knowledge; formal semantics; knowledge engineering; knowledge representations; ontology formal structure; ontology-based approaches; semantic Web ontologies; semantic data mining; Data mining; Ontologies;
fLanguage :
English
Publisher :
ieee
Conference_Titel :
Semantic Computing (ICSC), 2015 IEEE International Conference on
Conference_Location :
Anaheim, CA
Type :
conf
DOI :
10.1109/ICOSC.2015.7050814
Filename :
7050814
Link To Document :
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