Research Of Probabilistic Description Logics Based On Semantic Ant Colony Algorithm

Semantic network is considered as extension of World Wide Web. It can help thecomputer understand the network information, which can support much more complex dataintegration, navigation, and so. The main ideas behind the Semantic Web are to add meaning,which can make machines understand, into the web page. Semantic network containsuncertainty knowledge which is distributed in different nodes of network. This problem canbe solved by the uncertain knowledge of data integration technology in order to depict thetrue extent. This uncertain knowledge of data integration can produce uncertain knowledge ofthe facts.The uncertainty description logic knowledge base extends the traditional descriptionlogic knowledge base, especially with the introduction of uncertain knowledge aboutconcepts and roles, also the uncertainty knowledge about concepts and roles of individuals.The former is randomly selected, while the latter is discrete. The practical applications areurgent to deal with uncertain knowledge in the Ontology, especially in areas such as medicine,biology, astronomy and so on.As to traditional description logic reasoning, there are classic determine ontologyreasoning logics, such as SHIF (D) and SHOIN (D). They are corresponding to the networkontology language OWL Lite and OWL DL, and also have some successful applications.However, little actual projects are done for the uncertainty logic description reasoningalthough this kind of logic reasoning has the uncertain knowledge ontology reasoning logic.One of the uncertain logic description key issues is the method to calculate the upper andlower limits of the axiom of probability. In this paper, a improved ant colony algorithm basedon semantic ontology is proposed to meet this need. Finally, by a medical ontology case, thisalgorithm’s validity are verified.