DocumentCode :
3532650
Title :
Collaborative ontology building using qualitative information collection methods
Author :
Sarraipa, João ; Jardim-Goncalves, Ricardo ; Gaspar, Tiago ; Steiger-Garcao, Adolfo
Author_Institution :
Dept. de Eng. Electrotec., Univ. Nova de Lisboa, Caparica, Portugal
fYear :
2010
fDate :
7-9 July 2010
Firstpage :
61
Lastpage :
66
Abstract :
In the actual competitive context, doing business globally has become critical to the survival of most enterprises. To achieve it, enterprises require the establishment of cooperation agreements among each other. Thus, there is a demand for intelligent solutions capable of reinforcing partnerships and collaborations. However, due to the worldwide diversity of communities, a high number of knowledge representation elements, as ontologies, which are not semantically coincident, have appeared representing the same segment of reality. Therefore, even in the same domain, enterprises do not understand each other, impeding various systems parties to seamless communicate. To solve this semantic interoperability problem, it has been suggested to build a reference ontology able to represent such cluster of interoperating entities. The authors propose a collaborative ontology building methodology, enriched with qualitative information collection methods, to effectively improve the approach to elicit knowledge from business domain experts, towards interoperable intelligent systems.
Keywords :
knowledge acquisition; ontologies (artificial intelligence); open systems; business domain experts; collaborative ontology building methodology; cooperation agreements; elicit knowledge; intelligent solutions; interoperable intelligent systems; knowledge representation elements; qualitative information collection methods; reference ontology; semantic interoperability problem; Buildings; Collaboration; Collaborative tools; Humans; Intelligent structures; Intelligent systems; Knowledge acquisition; Knowledge representation; Ontologies; Terminology; collaborative ontology building; knowledge representation; tacit knowledge acquisition;
fLanguage :
English
Publisher :
ieee
Conference_Titel :
Intelligent Systems (IS), 2010 5th IEEE International Conference
Conference_Location :
London
Print_ISBN :
978-1-4244-5163-0
Electronic_ISBN :
978-1-4244-5164-7
Type :
conf
DOI :
10.1109/IS.2010.5548355
Filename :
5548355
Link To Document :
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