Michiaki Taniguchi

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Fraud detection refers to the attempt to detect illegitimate usage of a communications network. Three methods to detect fraud are presented. Firstly, a feed-forward neu-ral network based on supervised learning is used to learn a discriminative function to classify subscribers using summary statistics. Secondly, Gaussian mixture model is used to model the(More)
The topic of this thesis is fraud detection in mobile communications networks by means of user profiling and classification techniques. The goal is to first identify relevant user groups based on call data and then to assign a user to a relevant group. Fraud may be defined as a dishonest or illegal use of services, with the intention to avoid service(More)
Fraud detection refers to the attempt to detect illegitimate usage of a communications network. Three methods to detect fraud are presented. Firstly, a feed-forward neu-ral network based on supervised learning is used to learn a discriminative function to classify subscribers using summary statistics. Secondly, Gaussian mixture model is used to model the(More)
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