DocumentCode :
3273561
Title :
A structured ontology construction by using data clustering and pattern tree mining
Author :
Yu, Yao-tang ; Hsu, Chien-chang
Author_Institution :
Dept. of Comput. Sci. & Inf. Eng., Fu Jen Catholic Univ., Taipei, Taiwan
Volume :
1
fYear :
2011
fDate :
10-13 July 2011
Firstpage :
45
Lastpage :
50
Abstract :
Ontology is used to express the concepts of domain knowledge. It can provide a common representation for different agents to share and communicate knowledge for conducting unified opinions. Nowadays ontology construction method is divided into man-made and machine-made mechanisms. The former constructs the ontology topology by domain expert. Generally the constructed ontology can fit human expectation but it needs more development time to construct the whole structure. The latter uses semi-automatic or automatic methods, such as statistic or machine learning, to build the ontology. The efficient ontology construction is the main advantage for machine-made method. However, the advantage is that it is easily influenced by the category and type of domain concepts to generate unbalanced or skewed ontology topology. This will increase the time complexity to search and retrieve the concept from the constructed ontology structure. The situation worsens from being unable to use the ontology properly. An important problem is constructing a reasonable and balanced ontology topology systematically and automatically. This paper proposes a structured ontology construction based on data clustering and pattern tree mining. The construction method uses data clustering and formal concept analysis to group similar documents for constructing ontology trees of each group individually. Then the method uses pattern tree mining to build an integrated ontology topology from partial ontology trees.
Keywords :
data mining; ontologies (artificial intelligence); pattern clustering; tree searching; data clustering; domain expert; domain knowledge; formal concept analysis; integrated ontology topology; machine learning; machine-made mechanism; man-made mechanism; ontology construction method; ontology structure; partial ontology trees; pattern tree mining; structured ontology construction; time complexity; Data mining; Machine learning; Matrix decomposition; Ontologies; Semantics; Skeleton; Data clustering; Formal concept analysis; Ontology; Sequence pattern mining;
fLanguage :
English
Publisher :
ieee
Conference_Titel :
Machine Learning and Cybernetics (ICMLC), 2011 International Conference on
Conference_Location :
Guilin
ISSN :
2160-133X
Print_ISBN :
978-1-4577-0305-8
Type :
conf
DOI :
10.1109/ICMLC.2011.6016746
Filename :
6016746
Link To Document :
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