Faveeo is a community-oriented social content recommendation system that will help users around the world easily access the real time pulse of their community. The idea of faveeo.com is to observe and analyse interactions between users and the aggregated content regarding their community to then be able to automatically organize information so that anyone can see what matters most to a certain community.

These social community-based recommendations would allow users to get more precise local news, and also to see what topics are getting the attention of fellow community members. For local communities, this means that Faveeo.com will allow each local community to have a specific mini-site where they can filter "together" important and quality information in the pool of real-time information related to their community.

Since the content recommendations are based on user habits and geographical conditions, and are calculated automatically, faveeo.com will encourage the natural and organic formation of community-oriented groups. This is a way for anyone to actually get a feeling of not only what's happening in his community, but also to witness what are the general mindsets, opinions and interests of the members of his local community! Users can then use these relations to interact with fellow neighboors!

Faveeo.com innovates by allowing *automatic* creation of community-based topic and interests groups! There is no better way to learn about a community than by automatically discovering what they are browsing and what concerns and entertains them! By geolocating the users of our site, we will be able to actually understand not only what's happening in a specific community (using content agregation), but also what matters to any community, in real time! Another innovation, is that Faveeo.com will actually connecting itself to other social networks, like, Facebook and Twitter to build more accurate recommendations based on the behaviour of the users everywhere on the web, providing the "context" needed for accurate recommendations!

To achieve this, faveeo.com will mashup several open source web technologies like click and vote-based personalized content recommendation, geo-localization, semantics , and real time web. By using these technologies in conjuction, we can observe a user's reading patterns and then provide quality content that is interesting for a user, based not only on his habits, but also related to -and recommended by- his local community!

This mashup and connection to several other networks makes us feel that is more web 3.0 than web 2.0 since we're really trying to mix up the web 2.0 user-centered universe to work with the more modern web 3.0 data-centered web!