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KDD
2003
ACM
175views Data Mining» more  KDD 2003»
14 years 10 months ago
Time and sample efficient discovery of Markov blankets and direct causal relations
Data Mining with Bayesian Network learning has two important characteristics: under broad conditions learned edges between variables correspond to causal influences, and second, f...
Ioannis Tsamardinos, Constantin F. Aliferis, Alexa...
POPL
2008
ACM
14 years 10 months ago
From dirt to shovels: fully automatic tool generation from ad hoc data
An ad hoc data source is any semistructured data source for which useful data analysis and transformation tools are not readily available. Such data must be queried, transformed a...
Kathleen Fisher, David Walker, Kenny Qili Zhu, Pet...
SIGMOD
2009
ACM
161views Database» more  SIGMOD 2009»
14 years 10 months ago
Automated SQL tuning through trial and (sometimes) error
SQL tuning--the attempt to improve a poorly-performing execution plan produced by the database query optimizer-is a critical aspect of database performance tuning. Ironically, as ...
Herodotos Herodotou, Shivnath Babu
SIGMOD
2006
ACM
232views Database» more  SIGMOD 2006»
14 years 10 months ago
To search or to crawl?: towards a query optimizer for text-centric tasks
Text is ubiquitous and, not surprisingly, many important applications rely on textual data for a variety of tasks. As a notable example, information extraction applications derive...
Panagiotis G. Ipeirotis, Eugene Agichtein, Pranay ...
PODS
2005
ACM
151views Database» more  PODS 2005»
14 years 10 months ago
Estimating arbitrary subset sums with few probes
Suppose we have a large table T of items i, each with a weight wi, e.g., people and their salary. In a general preprocessing step for estimating arbitrary subset sums, we assign e...
Noga Alon, Nick G. Duffield, Carsten Lund, Mikkel ...