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KDD
2008
ACM
140views Data Mining» more  KDD 2008»
14 years 8 months ago
Semi-supervised approach to rapid and reliable labeling of large data sets
Supervised classification methods have been shown to be very effective for a large number of applications. They require a training data set whose instances are labeled to indicate...
György J. Simon, Vipin Kumar, Zhi-Li Zhang
ICDE
2007
IEEE
111views Database» more  ICDE 2007»
14 years 9 months ago
Scoop: An Adaptive Indexing Scheme for Stored Data in Sensor Networks
We present the design of Scoop, a system for indexing and querying stored data in sensor networks. Scoop works by collecting statistics about the rate of queries and distribution ...
Thomer M. Gil, Samuel Madden
MST
2010
106views more  MST 2010»
13 years 6 months ago
Constrained-Path Labellings on Graphs of Bounded Clique-Width
Given a graph G we consider the problem of preprocessing it so that given two vertices x,y and a set X of vertices, we can efficiently report the shortest path (or just its length...
Bruno Courcelle, Andrew Twigg
IJISMD
2010
135views more  IJISMD 2010»
13 years 5 months ago
On the Usage of Labels and Icons in Business Process Modeling
The value of business process models is dependent not only on the choice of graphical elements in the model, but also on their annotation with additional textual and graphical inf...
Jan Mendling, Jan Recker, Hajo A. Reijers
ACL
2009
13 years 5 months ago
Semi-Supervised Active Learning for Sequence Labeling
While Active Learning (AL) has already been shown to markedly reduce the annotation efforts for many sequence labeling tasks compared to random selection, AL remains unconcerned a...
Katrin Tomanek, Udo Hahn