SIBILA - Towards Smart Interacting Blocks that Improve Learned Advice

Project Duration: 
01/2013 - 06/2015
Project Code: 
NORTE-07-0124-FEDER-000059
Funding: 
688.048,91 € (ap. 250.000 for CRACS)
Funding Entity: 
PIDAC & ERDF
PI
CRACS Member: 
Fernando Silva
Research team
from CRACS: 
Álvaro Figueira
from CRACS: 
David Aparício
from CRACS: 
Inês Dutra
from CRACS: 
José Paulo Leal
from CRACS: 
Ricardo Rocha
from CRACS: 
Teresa Almeida Costa
from CRACS: 
Theofrastos Mantadelis
from CRACS: 
Vítor Santos Costa
others: 
Alípio Jorge
others: 
Luís Torgo

The SIBILA project aims at developing a set of tools that will effectively support the decisionmaking process in organizations, and facilitate the process of building data-driven solutions. 

These tools will be able to process and represent complex sources of data, such as multirelational and/or web data, and to, given a user-defined task, semi-automatically select the best components at hand and compose them together. To do so, SIBILA will require progress at the level of knowledge representation and data mining techniques. 

Moreover, the complexity of SIBILA will require contributions in software engineering and language development. Next, we discuss in more detail the main challenges facing SIBILA: knowledge representation and inference, web data, learning technology, and system engineering.