MAESTRA

Learning from Massive, Incompletely annotated, and Structured Data

Coordinatore	INSTITUT JOZEF STEFAN    more  Organization address address: Jamova 39 city: LJUBLJANA postcode: 1000 contact info Titolo: Prof. Nome: Jadran Cognome: Lenarcic Email: send email Telefono: +386 1 477 3513 Fax: +386 1 251 93 85
Nazionalità Coordinatore	Slovenia [SI]
Totale costo	2˙293˙310 €
EC contributo	1˙748˙295 €
Programma	FP7-ICT Specific Programme "Cooperation": Information and communication technologies
Code Call	FP7-ICT-2013-X
Funding Scheme	CP
Anno di inizio	2014
Periodo (anno-mese-giorno)	2014-02-01   -   2017-01-31

 Partecipanti

#	participant	country	role	EC contrib. [€]
1	INSTITUT JOZEF STEFAN  Organization address address: Jamova 39 city: LJUBLJANA postcode: 1000 contact info Titolo: Prof. Nome: Jadran Cognome: Lenarcic Email: send email Telefono: +386 1 477 3513 Fax: +386 1 251 93 85	SI (LJUBLJANA)	coordinator	0.00
2	INESC PORTO - INSTITUTO DE ENGENHARIA DE SISTEMAS E COMPUTADORES DO PORTO  Organization address address: Campus da FEUP, Rua Dr. Roberto Frias city: PORTO postcode: 4200 465 contact info Titolo: Ms. Nome: Marta Cognome: Barbas Email: send email Telefono: 351222000000 Fax: 351222000000	PT (PORTO)	participant	0.00
3	RUDER BOSKOVIC INSTITUTE  Organization address address: Bijenicka cesta city: ZAGREB postcode: 10000 contact info Titolo: Ms. Nome: Marijana Cognome: Klasnic Kozar Email: send email Telefono: +385 14571 342	HR (ZAGREB)	participant	0.00
4	Ss. CYRIL AND METHODIUS UNIVERSITY IN SKOPJE  Organization address address: Bul. Krste Misirkov city: SKOPJE postcode: 1000 contact info Titolo: Dr. Nome: Ivica Cognome: Dimitrovski Email: send email Telefono: 38977543253	MK (SKOPJE)	participant	0.00
5	UNIVERSITA DEGLI STUDI DI BARI ALDO MORO  Organization address address: Piazza Umberto I city: BARI postcode: 70121 contact info Titolo: Ms. Nome: Rosaria Cognome: LACALAMITA Email: send email Telefono: +39 0805443404 Fax: +39 0805443269	IT (BARI)	participant	0.00

Mappa

 Word cloud

Esplora la "nuvola delle parole (Word Cloud) per avere un'idea di massima del progetto.

 Obiettivo del progetto (Objective)

The need for machine learning (ML) and data mining (DM) is ever growing due to the increased pervasiveness of data analysis tasks in almost every area of life, including business, science and technology. Not only is the pervasiveness of data analysis tasks increasing, but so is their complexity. We are increasingly often facing predictive modelling tasks involving one or several of the following complexity aspects: (a)structured data as input or output of the prediction process, (b)very large/massive datasets, with many examples and/or many input/output dimensions, where data may be streaming at high rates, (c)incompletely/partially labelled data, and (d)data placed in a spatio-temporal or network context. Each of these is a major challenge to current ML/DM approaches and is the central topic of active research in areas such as structured-output prediction, mining data streams, semi-supervised learning, and mining network data. The simultaneous presence of several of them is a much harder, currently insurmountable, challenge and severely limits the applicability of ML/DM approaches.The proposed project will develop predictive modelling methods capable of simultaneously addressing several (ultimately all) of the above complexity aspects. In the most complex case, the methods would be able to address massive sets of network data incompletely labelled with structured outputs. We will develop the foundations (basic concepts and notions) for and the methodology (design and implementation of algorithms) of such approaches. We will demonstrate the potential and utility of the methods on showcase problems from a diverse set of application areas (molecular biology, sensor networks, mutimedia, and social networks). Some of these applications, such as relating the composition of microbiota to human health and the design of social media aggregators, have the potential of transformational impact on important aspects of society, such as personalized medicine and social media.