Fuzzy Ontologies and Fuzzy Markup Language: A Novel Vision in Web Intelligence

Semantic Web and Ontologies has increased the interest in the use of Knowledge-based systems in order to allow automated processing of, and reasoning with, information on the Web. However, it is widely pointed out that standard ontologies are not sufficient to deal with imprecise and vague knowledge for some real world applications, but the fuzzy ontologies can effectively model data and knowledge with uncertainty. In particular, in this paper will be introduced a collection of real-world applications based on the integration of different web-oriented frameworks such as the

ontology

 − 

based

intelligent

fuzzy

agents

(

OIFAs

) and the

Fuzzy

Markup

Language

(

FML

) capable of generating fuzzy inference mechanisms and semantic decision making systems for an efficient modeling of real scenarios. In detail, hereafter our web intelligence approach will be applied to medical semantic decision making systems, computer go framework and so on.The experimental results show that the proposed method is feasible for different real-word scenarios.