The role of context in fair group recommendations: the student will investigate the role played by the context, i.e. the situation a group of people is experiencing, in the design of a system that recommends sequences of activities as a multi-objective optimization problem, where the satisfaction of the group and the available time interval are two of the functions to be optimized. The dynamic evolution of the group can be the key contextual feature that has to be considered to produce fair suggestions.
The use of context to tailor big datasets: the student will investigate how the context (temporal, spatial information) can be used for indexing data stored in NoSQL databases.
Integration of BPMN diagrams: the student will investigate the probelm of matching different process models to infer a more abstract representation that can be used to merge and integrate processes or analyze them.
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