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» Managing Collaboration in the nanoManipulator
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KDD
2007
ACM
191views Data Mining» more  KDD 2007»
14 years 8 months ago
Modeling relationships at multiple scales to improve accuracy of large recommender systems
The collaborative filtering approach to recommender systems predicts user preferences for products or services by learning past useritem relationships. In this work, we propose no...
Robert M. Bell, Yehuda Koren, Chris Volinsky
SENSYS
2009
ACM
14 years 2 months ago
Integrated distributed energy awareness for wireless sensor networks
Energy in sensor networks is a distributed, non-transferable resource. Over time, differences in energy availability are likely to arise. Protocols like routing trees may concent...
Geoffrey Werner Challen, Jason Waterman, Matt Wels...
MDM
2009
Springer
269views Communications» more  MDM 2009»
14 years 2 months ago
R-U-In? - Exploiting Rich Presence and Converged Communications for Next-Generation Activity-Oriented Social Networking
—With the growing popularity of social networking, traditional Internet Service Providers (ISPs) and Telecom operators have both started exploring new opportunities to boost thei...
Nilanjan Banerjee, Dipanjan Chakraborty, Koustuv D...
MSR
2009
ACM
14 years 2 months ago
The promises and perils of mining git
We are now witnessing the rapid growth of decentralized source code management (DSCM) systems, in which every developer has her own repository. DSCMs facilitate a style of collabo...
Christian Bird, Peter C. Rigby, Earl T. Barr, Davi...
CISS
2008
IEEE
14 years 2 months ago
A lower-bound on the number of rankings required in recommender systems using collaborativ filtering
— We consider the situation where users rank items from a given set, and each user ranks only a (small) subset of all items. We assume that users can be classified into C classe...
Peter Marbach