Fundamentals of database systems (2nd ed.)
Fundamentals of database systems (2nd ed.)
The effectiveness of machine learning techniques for predicting time to case disposition
Proceedings of the 6th international conference on Artificial intelligence and law
Towards privacy preserving data reconciliation for criminal justice chains
Proceedings of the 10th Annual International Conference on Digital Government Research: Social Networks: Making Connections between Citizens, Data and Government
Preserving privacy whilst integrating data: Applied to criminal justice
Information Polity - Government 2.0: Making Connections between citizens, data and government
A method for explaining and predicting trends: an application to the Dutch justice system
Proceedings of the 13th International Conference on Artificial Intelligence and Law
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A reliable estimation of the capacity required for the Dutch justice chains in the near future is inevitable to implement a policy that is capable to handle forthcoming judicial cases in a society. To come up with reliable estimations, an understanding of the vital processes in the justice chains is required. However, the Dutch justice chains are complex with many more or less independent organisations. Therefore capturing the vital processes in a model is a challenging task. Research has pointed out that many variables are involved in these processes. Consequently, our model of the Dutch justice chain resulted in a large set of equations and variables. However, such a model is necessary for the prediction of the required capacity in the near future. Since the impact of a variable may evolve over time, this means that the model of the Dutch justice chains needs to be maintained. Otherwise, the model may result in poor prediction. Maintaining such a model manually is at best a laborious and error-prone process. Therefore, this paper is devoted to the design and implementation of a forecasting tool that is easy to maintain and that will help forecasters to reduce their workload and improve their forecasts.