GoLocal: From monitoring global data streams to context-aware recommendations
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"GoLocal aims to tame the massive, rapidly evolving streams of data that flow through many of today’s information systems. It develops data analytics technology for monitoring, analysing, and leveraging these streams to deliver information and services that are tailored for different individuals and contexts. This ERI brings together scientists from key areas to not only push the frontier of the state-of-the-art in this area, but also to support the development of data scientists that are fluent in research methods needed to channel, manage, and exploit massive, rapidly evolving data streams.
Partnerships ground this research endeavour in the real world and provide a path for technology transfer. The Lisbon City Council is keen on exploring the use of GoLocal for tourism applications, while Priberam and Portugal Telecom will provide data and support for the deployment of project prototypes." João Costa Magalhães and Jamie Callan
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Portuguese PI João Magalhães (NOVA.ID.FCT; FCT/UNL) |
CMU PI Jamie Callan (CS) |
Research teams: Carnegie Mellon University (CMU); Associação para a Inovação e Desenvolvimento da FCT (NOVA.ID.FCT); Instituto de Engenharia de Sistemas e Computadores, Investigação e Desenvolvimento em Lisboa (INESC ID); Instituto de Telecomunicações (IT)
Organizations: Câmara Municipal de Lisboa (CML); Priberam Informática, S.A. (Priberam); SAPO-LABS
Main Research Unit: Associação para a Inovação e Desenvolvimento da FCT (NOVA.ID.FCT)
Funding Reference: CMUP-ERI/TIC/0046/2014
Duration: 48 months
Keywords: Data streams; Social-media; Context-aware recommendation; Media monitoring
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 shortlived 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 from real-world use cases provided by the non-academic partners,
we shall leverage media monitoring and context-aware recommendation
technologies.
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The Phase II of the Carnegie Mellon Portugal Program emphasizes advanced
education and research that can lead to significant entrepreneurial
impact. The activities of the program are for the most part configured
in Entrepreneurial Research Initiatives (ERIs).
Research Opportunities more