The following diagram demonstrates the authentication/authorization and data retrieval flow that OpenRecommender will undertake on behalf of a user who is looking for Recommendations:

The first demo of the Recommendation Engine widget is available as a preview here:

It is currently used for recommending user-generated content (videos) on a small test video sharing community dataset with 2000 videos and 500 users, a modest testbed for an ambitious project, but we believe our unique multi-faceted approach to recommendations will scale to much larger systems and datasets in the future.

The following is the approximate Roadmap for development of OpenRecommender (with release dates in brackets):

1. Schemas (COMPLETED: 2011-01-26)

• XML Schema
• JSON Schema
• RDF Schema

2. Semantics (COMPLETED: 2011-11-11)

FINAL DRAFT

Imagine a world where we didn’t have to go looking for what we wanted to see (in other words, where we were able to "discover" new things that we didn’t yet know we wanted to see, but end up loving the new things and learning or gaining a new interest). Such is the premise of the OpenRecommender project, suggesting a recommendation-based solution to the growing information problem.

In order to accomplish this vision, we will be releasing a number of technologies and related data exchange formats which we hope the open source developer community will incorporate into their existing applications, whenever they have a need to work with or serve up recommendations to their users.

Welcome to the new home of OpenRecommender, an initiative to create the world's leading open source Recommendation Engine.