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CORR
2000
Springer
120views Education» more  CORR 2000»
13 years 8 months ago
Scaling Up Inductive Logic Programming by Learning from Interpretations
When comparing inductive logic programming (ILP) and attribute-value learning techniques, there is a trade-off between expressive power and efficiency. Inductive logic programming ...
Hendrik Blockeel, Luc De Raedt, Nico Jacobs, Bart ...
KDD
2007
ACM
153views Data Mining» more  KDD 2007»
14 years 9 months ago
Exploiting duality in summarization with deterministic guarantees
Summarization is an important task in data mining. A major challenge over the past years has been the efficient construction of fixed-space synopses that provide a deterministic q...
Panagiotis Karras, Dimitris Sacharidis, Nikos Mamo...
KDD
2008
ACM
259views Data Mining» more  KDD 2008»
14 years 9 months ago
Using ghost edges for classification in sparsely labeled networks
We address the problem of classification in partially labeled networks (a.k.a. within-network classification) where observed class labels are sparse. Techniques for statistical re...
Brian Gallagher, Hanghang Tong, Tina Eliassi-Rad, ...
WWW
2005
ACM
14 years 9 months ago
Executing incoherency bounded continuous queries at web data aggregators
Continuous queries are used to monitor changes to time varying data and to provide results useful for online decision making. Typically a user desires to obtain the value of some ...
Rajeev Gupta, Ashish Puri, Krithi Ramamritham
EUROPAR
2000
Springer
14 years 6 days ago
On the Performance of Fetch Engines Running DSS Workloads
Abstract This paper examines the behavior of current and next generation microprocessors' fetch engines while running Decision Support Systems (DSS) workloads. We analyze the ...
Carlos Navarro, Alex Ramírez, Josep-Lluis L...