BAYESIAN APPROACH TO INCOME INFERENCE IN A COMMUNICATION NETWORK

摘要

Users can be classified as belonging to one of multiple income categories. A communications graph can be generated based on call data records (CDRs), the graph including a subset of nodes representing users of a mobile telephony network whose income is estimated based on available banking records. For a node representing a user whose income is unknown (i.e., a node that is not within the subset of nodes), and which is connected by a link to at least one node within the subset of the nodes, a Bayesian prediction algorithm may be used to classify the selected node. The Bayesian prediction algorithm may include defining a prior probability distribution of a Bayesian inference with a parameter based on a number of outgoing communication sessions from the selected node to nodes associated a particular income category, and computing a value for a lowest N^th percentile of the prior probability distribution.