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

/uploadedImages/ERIs/ERIs_2015/Joao-Magalhaes.jpg /uploadedImages/ERIs/ERIs_2015/Jamie Callan.jpg “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

Portuguese PI
João Magalhães
Jamie Callan

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.


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).

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