The objective of this class is to present models for the representation of uncertain data, as well as algorithms and tools to process this data, while maintaining information about its uncertainty.
Topics covered include:
● Sources of uncertain data
● Incomplete data models in closed-world assumptions: SQL NULLs and Codd tables, c-tables
● Data model for open-world data: consistent query answering, OBDA
● Possible world semantics
● Querying relational probabilistic databases: operators, lineage, hardness, practical implementations
● Social applications of uncertain data: probabilistic graphs, social influence, crowdsourcing
Labs will feature the MayBMS probabilistic relational database engine.
Topics covered include:
● Sources of uncertain data
● Incomplete data models in closed-world assumptions: SQL NULLs and Codd tables, c-tables
● Data model for open-world data: consistent query answering, OBDA
● Possible world semantics
● Querying relational probabilistic databases: operators, lineage, hardness, practical implementations
● Social applications of uncertain data: probabilistic graphs, social influence, crowdsourcing
Labs will feature the MayBMS probabilistic relational database engine.
- Enseignant: Mauro Sozio
- Enseignant responsable de l'UE: Fabian Suchanek