According to Teresa Andrade, the CTM researcher coordinating the project, “CAMR takes advantage of the existing sensors on mobile devices, such as accelerometer,  orientation, GPS, light or sound sensors, to obtain information about the use contexts. Simultaneously, the app monitors the users’ consumptions, building contextualised user profiles in an implicit way.” 

The app uses these profiles in a transparent way or when requested by the user in order to implement a non-invasive recommendation engine that is sensitive to the context. This way, the app extracts knowledge on the user (preferably the contents and the conditions in which those contents are consumed), making decisions on the contents to recommend according to the contexts (type of activity of the user, characteristics of the terminal, time of the day, day of the week, year, location, network connection, environmental conditions, among others), thus making the search for contents faster and more effective. The project was also developed by Abayomi Otebolaku, researcher at CTM.

This project is funded by the North Portugal Regional Operational Programme ("ON.2 - O Novo Norte"), of the National Strategic Reference Framework (NSRF), through the European Regional Development Fund (ERDF), and also by National Funds from the Foundation for Science and Technology (FCT).

The INESC TEC researchers mentioned in this article are associated with the following partner institutions: INESC Porto and FEUP.

INESC TEC, March 2015