DISCOVR

Like its predecessor SPREADR, DISCOVR is a showcase of a shopping portal that aims at providing the visitor with better user- and context-aware recommendations for products and events than is possible with traditional recommendation algorithms such as collaborative filtering. In contrast to SPREADR, however, DISCOVR does not focus on spreading activation-based recommendation generation. While a first prototype of the shop was constructed from building blocks of an integrated architecture called “Context-aware Recommendations on Rails”, the current version now leverages the full power of the Hybreed Framework to create hybrid recommenders based upon a variety of different recommendation techniques. As in its predecessor, DISCOVR incorporates a number of internal and external context factors such as the user’s click history, the current location or the current weather to generate adequate recommendations.

Technology

• Hybreed Framework
• JSF
• Java

Publications

Improving collaboration by using context views

Hussein, T., Gaulke, W., Linder, T., & Ziegler, J. (2010). In Context-Adaptive Interaction for Collaborative Work (CAICOLL), 1st Workshop in conjunction with the ACM Conference on Human Factors in Computing Systems (CHI) 2010 (pp. 1–6).

Context-aware Recommendations

Hussein, T. (2010). In N. Baloian, W. Luther, D. Söffker, & Y. Urano (Eds.), Interfaces and Interaction Design for Learning and Simulation Environments. Logos.

Automated Generation of a Faceted Navigation Interface Using Semantic Models

Hussein, T., & Münter, D. (2010). Semantic Models for Adaptive Interactive Systems (SEMAIS), 1st Workshop in Conjunction with the International Conference on Intelligent User Interfaces (IUI) 2010.

Context-aware Recommendations on Rails

Hussein, T., Linder, T., Gaulke, W., & Ziegler, J. (2009). In L. Bergmann (Ed.), Proceedings of the 2009 Workshop on Context-aware Recommender Systems (CARS 2009).