Contextual Personalization and Intensional Query Answering in Data Management

The current technological scenario is characterized by an extremely large variety
of information sources, which constitutes an unprecedented opportunity for the
users but at the same time risks to overwhelm them.

In this scenario, it is possible to partition Elisa Quintarelli's current research interests into two main lines:
context-aware data design and management application of data mining techniques.

The first line focuses on the definition of methodologies for managing (selection, tailoring and personalization)
data from heterogeneous sources in a context-aware scenario.

The second one proposes a summarized representation of XML data, based on the concept of
pattern, which are extracted with data mining techniques and can both provide succinct information and be directly queried.