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
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;
Conference_Titel :
Information Management and Engineering, 2009. ICIME '09. International Conference on
Conference_Location :
Kuala Lumpur
Print_ISBN :
978-0-7695-3595-1
DOI :
10.1109/ICIME.2009.16