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» Modeling the Propagation of User Preferences
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WWW
2011
ACM
13 years 5 months ago
Track globally, deliver locally: improving content delivery networks by tracking geographic social cascades
Providers such as YouTube offer easy access to multimedia content to millions, generating high bandwidth and storage demand on the Content Delivery Networks they rely upon. More ...
Salvatore Scellato, Cecilia Mascolo, Mirco Musoles...
ACMICEC
2003
ACM
182views ECommerce» more  ACMICEC 2003»
14 years 4 months ago
eNcentive: a framework for intelligent marketing in mobile peer-to-peer environments
In recent years, the growth of Mobile Computing, Electronic Commerce and Mobile Electronic Commerce has created a new concept of Mobile Electronic Marketing. New marketing models ...
Olga Ratsimor, Timothy W. Finin, Anupam Joshi, Yel...
PERCOM
2009
ACM
14 years 11 months ago
iLamp: A Sensor-Enhanced Lamp with Surface-Tracking Capability Based on Light Intensity
The iLamp1 system is a sensor-enhanced desk lamp with surface-tracking capability based on received light intensity. It consists of two components: lamp and bookmark. The bookmark ...
Lun-Wu Yeh, Che-Yen Lu, Yu-Hsuan Lin, Jia-Liang Li...
WWW
2010
ACM
14 years 5 months ago
Sampling high-quality clicks from noisy click data
Click data captures many users’ document preferences for a query and has been shown to help significantly improve search engine ranking. However, most click data is noisy and of...
Adish Singla, Ryen W. White
SSDBM
2008
IEEE
177views Database» more  SSDBM 2008»
14 years 5 months ago
Prioritized Evaluation of Continuous Moving Queries over Streaming Locations
Abstract. Existing approaches to the management of streaming positional updates generally assume that all active user requests have equal importance, ignoring the possibility of an...
Kostas Patroumpas, Timos K. Sellis