A major precondition for a sustainable application of knowledge-based recommendation technologies is the integration of end-users in corresponding development and maintenance processes. This goal has to be achieved for the following reasons:

1. the scalability (the more recommender applications are implemented, the more maintenance efforts are needed).
2. the enormous potential for the dissemination of knowledge-based recommendation technologies on a broader basis.

The goal of the research project PeopleViews (Recommendation Technologies based on Human Computation) is to develop “Human Computation” concepts that can be applied in the context of knowledge acquisition processes of recommender applications. The basic idea of “Human Computation” is to let people solve computation problems that are not solvable or at least not easy to solve by computers. In this context, the technical objectives of PeopleViews are the following:

1. Concepts for end-user oriented knowledge acquisition based on technologies from the areas of “Human Computation” and “Games with a Purpose”
2. Approaches for the semi-automated consolidation of community-based recommendation knowledge.
3. Community-based techniques for diagnosis, redundancy detection, and manipulation detection in recommendation knowledge bases.