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» Evaluating algorithms that learn from data streams
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DAWAK
2004
Springer
15 years 3 months ago
SCLOPE: An Algorithm for Clustering Data Streams of Categorical Attributes
Clustering is a difficult problem especially when we consider the task in the context of a data stream of categorical attributes. In this paper, we propose SCLOPE, a novel algorith...
Kok-Leong Ong, Wenyuan Li, Wee Keong Ng, Ee-Peng L...
CIKM
2006
Springer
15 years 1 months ago
Incremental hierarchical clustering of text documents
Incremental hierarchical text document clustering algorithms are important in organizing documents generated from streaming on-line sources, such as, Newswire and Blogs. However, ...
Nachiketa Sahoo, Jamie Callan, Ramayya Krishnan, G...
CIKM
2006
Springer
15 years 1 months ago
Matching and evaluation of disjunctive predicates for data stream sharing
New optimization techniques, e. g., in data stream management systems (DSMSs), make the treatment of disjunctive predicates a necessity. In this paper, we introduce and compare me...
Richard Kuntschke, Alfons Kemper
EUROGP
2010
Springer
166views Optimization» more  EUROGP 2010»
15 years 3 months ago
Learning a Lot from Only a Little: Genetic Programming for Panel Segmentation on Sparse Sensory Evaluation Data
We describe a data mining framework that derives panelist information from sparse flavour survey data. One component of the framework executes genetic programming ensemble based s...
Katya Vladislavleva, Kalyan Veeramachaneni, Una-Ma...
NIPS
2003
14 years 11 months ago
Learning a Distance Metric from Relative Comparisons
This paper presents a method for learning a distance metric from relative comparison such as “A is closer to B than A is to C”. Taking a Support Vector Machine (SVM) approach,...
Matthew Schultz, Thorsten Joachims