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» Evaluating algorithms that learn from data streams
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DAWAK
2004
Springer
15 years 12 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 10 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 10 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 11 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
15 years 7 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