Research

 

We are currently focusing in the following three research areas:

Core Database Technologies

The Core Database Technology project deals with fundamental research issues for the next generation of large high performance database and decision support systems. We develop new solutions to approximately match XML data, and to aggregate and visualize multi-dimensional data. Our focus is the design and implementation of scalable solutions for advanced data management. This includes core, applied and experimental research in data modelling, query languages and query processing. We design and implement systems for the approximate handling of data, the management of time-varying and heterogeneous information, and density-based clustering.

Temporal Database Systems

Although most real-world applications, e.g., in the financial, medical, and scientific domains, must deal with data with an associated time dimension, current database management systems offer little built-in support for temporal data management. The Temporal Database Systems project aims to progress the frontiers of standard relational database technology towards the support for temporal data management, thus broadening their applicability. The main focus is the generalization of existing temporal data models and query languages and the development of efficient evaluation algorithms.

Intelligent Information Systemsmoby search

The aim of this project is to research methodologies and techniques to better support complex information retrieval and decision making tasks, such as travel planning, product purchase in an eCommerce Web site or a service contract negotiation in an eBusiness marketplace. In particular we investigate methods and techniques to build systems that show an adaptive behavior – to the user and search characteristics, to the decision context – and are able to support cooperative (collaborative) human-computer interactions.

We focus on emerging Advisory Systems able to exploit various knowledge and data sources, including large amounts of information generated by web users. Advisory systems rely on a set of models – about the user, the information search and decision process, the content – and technologies developed in information and data retrieval, human-computer interaction, decision making and machine learning. A result of this project is a hi-tech spin off developing and marketing recommendation technologies for the travel and tourism market.