A Probabilistic Ontology for the Prediction of Author's Interests

摘要

The Bayesian network, a probabilistic model of knowledge representation, has the ability to represent and reason with uncertainty. It measures the dependencies between a set of variables and infer new knowledge. In this paper, we try to propose a method for building a probabilistic ontology, which models a list of publications (dblp base). We have used for this aim a Bayesian Network to measure dependencies between different instances of ontology and to infer new interests of authors from obtained Probabilistic Ontology.