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» Grid Differentiated Services: A Reinforcement Learning Appro...
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WWW
2009
ACM
14 years 6 months ago
Learning to recognize reliable users and content in social media with coupled mutual reinforcement
Community Question Answering (CQA) has emerged as a popular forum for users to pose questions for other users to answer. Over the last few years, CQA portals such as Naver and Yah...
Jiang Bian, Yandong Liu, Ding Zhou, Eugene Agichte...
FGCS
2006
114views more  FGCS 2006»
13 years 5 months ago
A semantic approach to discovering learning services in grid-based collaborative systems
CSCL systems can benefit from using grids since they offer a common infrastructure enabling the access to an extended pool of resources that can provide supercomputing capabilitie...
Guillermo Vega-Gorgojo, Miguel L. Bote-Lorenzo, Ed...
RAS
2010
164views more  RAS 2010»
13 years 4 months ago
Bridging the gap between feature- and grid-based SLAM
One important design decision for the development of autonomously navigating mobile robots is the choice of the representation of the environment. This includes the question which...
Kai M. Wurm, Cyrill Stachniss, Giorgio Grisetti
SIGIR
2003
ACM
13 years 11 months ago
ReCoM: reinforcement clustering of multi-type interrelated data objects
Most existing clustering algorithms cluster highly related data objects such as Web pages and Web users separately. The interrelation among different types of data objects is eith...
Jidong Wang, Hua-Jun Zeng, Zheng Chen, Hongjun Lu,...
ATAL
2007
Springer
13 years 9 months ago
On Choosing an Efficient Service Selection Mechanism in Dynamic Environments
Consumers use service selection mechanisms to decide on a service provider to interact with. Although there are various service selection mechanisms, each mechanism has different s...
Murat Sensoy, Pinar Yolum