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.
Web interfaces to store and query data produced in the ICE lab: the student will investigate how to design and realize user-friendly interfaces for data coming from sensors.
The sharing of context in IoT scenario: in IoT scenario different devices operate in various contexts. The student will investigate how the sharing of context between devices can help to discover new information and personalize behaviours.
Analysis of data produced by sensors: the student will study data-mining algorithms to infer new knowledge from big datasets produced by sensors (e.g. Fitbit) in order to discover temporal patterns, correlations and suggest more advanced functionalities in Apps.
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.
Strada le Grazie 15
VAT number 01541040232
Italian Fiscal Code 93009870234
© 2021 | Verona University | Credits