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» Evaluating algorithms that learn from data streams
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IJCAI
2003
15 years 1 months ago
Statistics Gathering for Learning from Distributed, Heterogeneous and Autonomous Data Sources
With the growing use of distributed information networks, there is an increasing need for algorithmic and system solutions for data-driven knowledge acquisition using distributed,...
Doina Caragea, Jaime Reinoso, Adrian Silvescu, Vas...
SIGIR
2008
ACM
15 years 14 days ago
Learning to rank with partially-labeled data
Ranking algorithms, whose goal is to appropriately order a set of objects/documents, are an important component of information retrieval systems. Previous work on ranking algorith...
Kevin Duh, Katrin Kirchhoff
OTM
2009
Springer
15 years 7 months ago
Evaluating Transport Protocols for Real-Time Event Stream Processing Middleware and Applications
Real-time event stream processing (RT-ESP) applications must synchronize continuous data streams despite fluctuations in resource availability. Satisfying these needs of RT-ESP ap...
Joe Hoffert, Douglas C. Schmidt, Aniruddha S. Gokh...
SIGMOD
2006
ACM
158views Database» more  SIGMOD 2006»
16 years 20 days ago
Continuous query processing in data streams using duality of data and queries
Recent data stream systems such as TelegraphCQ have employed the well-known property of duality between data and queries. In these systems, query processing methods are classified...
Hyo-Sang Lim, Jae-Gil Lee, Min-Jae Lee, Kyu-Young ...
ISMIS
2005
Springer
15 years 6 months ago
Scalable Inductive Learning on Partitioned Data
With the rapid advancement of information technology, scalability has become a necessity for learning algorithms to deal with large, real-world data repositories. In this paper, sc...
Qijun Chen, Xindong Wu, Xingquan Zhu