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Lecture Notes in Computer Science
Debt detection is important for improving payment accuracy in social security. Since debt detection from customer transactional data can be generally modelled as a fraud detection problem, a straightforward solution is to extract features from transaction sequences and build a sequence classifier for debts. The existing sequence classification methods based on sequential patterns consider only positive patterns. However, according to our experience in a large social security application,doi:10.1007/978-3-642-04174-7_42 fatcat:xqmm4citfjfifo7mra6hambtwy