A Probabilistic Approach: A Model for the Uncertain Representation and Navigation of Uncertain Web Resources

Navigating through the web of uncertain data has become increasingly difficult. Unfortunately, the old techniques used in the classical web can not handle the navigation of uncertain web data or resources. Uncertain data published on the web can be heterogeneous, conflicting, inconsistent or in incompatible formats. This uncertainty is inherently related to many factors such as information extraction and data integration. In order to give the web user the best experience and provide him with the most relevant answer we have to consider the uncertainty of web data and model it. In this paper, we propose a probabilistic approach to model and interpret uncertain web resources. We present operators to compute the uncertainty for the response. Finally, we propose algorithms in order to validate resources and to achieve the uncertain navigation.