User-Item Reciprocity in Recommender Systems: Incentivizing the Crowd

Said, A., Larson, M., Tikk, D., Cremonesi, P., Karatzoglou, A., Hopfgartner, F. , Turrin, R. and Geurtz, J. (2014) User-Item Reciprocity in Recommender Systems: Incentivizing the Crowd. In: UMAP ProS'14: Proceedings of the UMAP Project Synergy Workshop, Aalborg, Denmark, 7-11 Jul 2014, pp. 23-26.

Abstract

Data consumption has changed significantly in the last 10 years. The digital revolution and the Internet has brought an abundance of information to users. Recommender systems are a popular means of finding content that is both relevant and personalized. However, today’s users require better recommender systems, able of producing continuous data feeds keeping up with their instantaneous and mobile needs. The CrowdRec project addresses this demand by providing context-aware, resource-combining, socially-informed, interactive and scalable recommendations. The key insight of CrowdRec is that, in order to achieve the dense, high-quality, timely information required for such systems, it is necessary to move from passive user data collection, to more active techniques fostering user engagement. For this purpose, CrowdRec activates the crowd, soliciting input and feedback from the wider community

• Item Type: Conference Proceedings
• Status: Published
• Refereed: Yes
• Glasgow Author(s) Enlighten ID: Hopfgartner, Dr Frank
• Authors: Said, A., Larson, M., Tikk, D., Cremonesi, P., Karatzoglou, A., Hopfgartner, F., Turrin, R., and Geurtz, J.
• College/School: College of Arts & Humanities > School of Humanities > Information Studies
• Publisher: CEUR
• Copyright Holders: Copyright © 2014 CEUR
• Publisher Policy: Reproduced in accordance with the copyright policy of the publisher