DocumentCode :
2121034
Title :
New Algorithm for Building Ontology from Existing Rules: A Case Study
Author :
Kharbat, Faten ; Ghalayini, Haya
Author_Institution :
Dept. of Comput. Sci., Zarqa Private Univ., Zarqa
fYear :
2009
fDate :
3-5 April 2009
Firstpage :
12
Lastpage :
16
Abstract :
From the fact that ontologies can help in making sense of huge amount of content, this paper proposes a case study for building ontology via set of rules generated by rule-based learning system. The proposed algorithm utilises the extracted and representative rules generated from the original dataset in developing ontology elements. The proposed algorithm is applied to a well known dataset in the breast cancer domain. The results are encouraging and support the potential role that this approach can play in providing a suitable starting point for ontology development.
Keywords :
cancer; data mining; learning (artificial intelligence); medical computing; ontologies (artificial intelligence); Wisconsin breast cancer dataset; data mining; domain ontology; rule generation; rule-based learning system; Artificial intelligence; Breast cancer; Computer science; Information management; Knowledge representation; Learning systems; Logic; Ontologies; Semantic Web; Spine; Onrology; breast cancer; developing Ontology; knowldege-based systems;
fLanguage :
English
Publisher :
ieee
Conference_Titel :
Information Management and Engineering, 2009. ICIME '09. International Conference on
Conference_Location :
Kuala Lumpur
Print_ISBN :
978-0-7695-3595-1
Type :
conf
DOI :
10.1109/ICIME.2009.16
Filename :
5076989
Link To Document :
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