GoLocal

GoLocal: From monitoring global data streams to context-aware recommendations

Research teams: CMU; NOVA.ID.FCT; INESC ID; IT
Organizations: CML; Priberam; SAPO-LABS
Main Research Area: Data streams; Social-media; Context-aware recommendation; Media monitoring
CMU Portugal Program webpage: http://www.cmuportugal.org/tiercontent.aspx?id=6337
Principal Investigators: João Magalhães (FCT/UNL; NOVA.ID.FCT); Jamie Callan (CMU; CS)

Nowadays, streams of Web user data are mostly discarded by current Web information systems. User location, devices, services and other sensors hide specific information consumption patterns that could be identified by online services to better answer consumer needs. However, the scale of this data is too large to be archived or processed. Most of this data is only useful during a short period of time and is related to short-lived events, far shorter than the time a batch and non-distributed data mining algorithm needs to timely process largescale data.

The GoLocal project proposes to advance big data technology for supporting the development of new information businesses and services. Our long-term vision aims at making big data economically useful, by realizing the full potential of largescale data analysis technologies in the design of innovative services. An ecosystem of tools for big data, with several cutting edge technologies, will be released by the consortium.

To realize this vision, GoLocal will leverage the real-world needs and data from our non-academic partners, namely the Lisbon City Council, SAPO and Priberam. In particular, these partners will provide real-world consumer data: both language and behavioural data will be captured in online services and mobile apps. Based on this data, we shall leverage media monitoring and context-aware recommendation technologies.