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» Evaluating algorithms that learn from data streams
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SIGIR
2012
ACM
13 years 10 months ago
TFMAP: optimizing MAP for top-n context-aware recommendation
In this paper, we tackle the problem of top-N context-aware recommendation for implicit feedback scenarios. We frame this challenge as a ranking problem in collaborative filterin...
Yue Shi, Alexandros Karatzoglou, Linas Baltrunas, ...
SIGIR
2003
ACM
16 years 25 days ago
Collaborative filtering via gaussian probabilistic latent semantic analysis
Collaborative filtering aims at learning predictive models of user preferences, interests or behavior from community data, i.e. a database of available user preferences. In this ...
Thomas Hofmann
UM
2009
Springer
16 years 2 months ago
Recognition of Users' Activities Using Constraint Satisfaction
Ideally designed software allow users to explore and pursue interleaving plans, making it challenging to automatically recognize user interactions. The recognition algorithms prese...
Swapna Reddy, Ya'akov Gal, Stuart M. Shieber
184
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DEXA
2003
Springer
115views Database» more  DEXA 2003»
16 years 24 days ago
On Mining Group Patterns of Mobile Users
In this paper, we present a group pattern mining approach to derive the grouping information of mobile device users based on the spatio-temporal distances among them. Group pattern...
Yida Wang, Ee-Peng Lim, San-Yih Hwang
CLUSTER
2004
IEEE
15 years 11 months ago
XChange: coupling parallel applications in a dynamic environment
Modern computational science applications are becoming increasingly multi-disciplinaty involving widely distributed research teams and their underlying computational platforms. A ...
Hasan Abbasi, Matthew Wolf, Karsten Schwan, Greg E...