e-LICO

Schematic depiction of the e-LICO platform

e-LICO platform is comprised of three layers: the e-Science layer, data mining layer and application domain layer. e-Science layer and data mining layer form a generic research environment that is adapted to different domains of science.

Project URL
http://www.e-lico.eu

The goal of the e-LICO project is to build a virtual laboratory for interdisciplinary collaborative research in data mining and data-intensive sciences. The proposed e-lab will comprise three layers: the e-science and data mining layers will form a generic research environment that can be adapted to different scientific domains by customizing the application layer.

The e-science layer, built on an open-source e-science infrastructure developed by one of the partners, will support content creation through collaboration at multiple scales and degrees of commitment — ranging from small, contract-bound teams to voluntary, constraint-free participation in dynamic virtual communities.

The data mining layer will be the distinctive core of e-LICO; it will provide comprehensive multimedia (structured records, text, images, signals) data mining tools. Standard tools will be augmented with preprocessing or learning algorithms developed specifically to meet challenges of data-intensive, knowledge rich sciences, such as ultra-high dimensionality or undersampled data. Methodologically sound use of these tools will be ensured by a knowledge-driven data mining assistant, which will rely on a data mining ontology and knowledge base to plan the mining process and propose ranked workflows for a given application problem. Extensive e-lab monitoring facilities will automate the accumulation of experimental meta-data to support replication and comparison of data mining experiments. These meta-data will be used by a meta-miner, which will combine probabilistic reasoning with kernel-based learning from complex structures to incrementally improve the assistant's workflow recommendations.

e-LICO is showcased in two pilot application areas: systems biology and digital multimedia repositories. 
RBI (Rudjer Boskovic Institute) group from Division of electronics leads activities in Workpackage 13: Personalization and recommendation services for digital multimedia repositories.

Project category
Sedmi okvirni program za razvoj i istraživanje
Project leader / principal investigator
Tomislav Šmuc

Tomislav Šmuc

Tomislav.Smuc@irb.hr
+385 1 456 1085
0981869605

Ugovoreni iznos financiranja
191,680 EUR
Associates

Dragan Gamberger (senior scientist)
Nino Antulov-Fantulin (PhD student)
Matija Piškorec (PhD student)

External collaborators:
Matko Bošnjak (PhD student)
Matej Mihelčić (PhD Student) 

Commercial potential

Know-how:

  • modern recommender systems technologies
  • building data mining and recommendation services
Project start date
01/06/2010
Project end date
31/01/2012