A Contextual Reasoning Research Based on the Uncertain Context

With the explosive growth of information, as well as the development on a wide range, the demand of internet users is increasing rapidly, most of the contexts in the real world are uncertain, there is some ambiguity and uncertain relationship in the ontology knowledge. In order to solve this problem, this paper proposed an uncertain context ontology based contextual reasoning method. It adopts the traditional centroid localization algorithm and the improved weighted centroid localization algorithm to acquire the uncertain location context as well as acquires the user's related context information from the user interactive interface, then obtains membership degree of the variables by data fuzzy processing, and finally weighted sum the context variable by the attribute correlation between different ontology concepts and the similarity attribute correlation. Simulation result shows that the proposed method performed better than the traditional general context reasoning approach.