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Automatic User Behavior Modeling

To achieve top customer satisfaction, your modern software factory should be able to: 1) detect bottlenecks in the user experience of your app; 2) build applications that anticipate user’s intentions; 3) generate a view of how your customers interact with your application; 4) offer mechanism against fraudulent behavior.

Although the interaction between customers and applications is conformed of several steps, most of current solutions for profiling users are based on snapshots of their status. In A-BeaM, we focus on the study of the implications of representing such user profile as a sequence of actions, enhance the current formalization and modelling of such user profiles, and the impact of the selected model in the visualization and the analytics.

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