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ICDE
2008
IEEE
195views Database» more  ICDE 2008»
14 years 9 months ago
LOCUST: An Online Analytical Processing Framework for High Dimensional Classification of Data Streams
Abstract-- In recent years, data streams have become ubiquitous because of advances in hardware and software technology. The ability to adapt conventional mining problems to data s...
Charu C. Aggarwal, Philip S. Yu
DAWAK
2008
Springer
13 years 9 months ago
Efficient Approximate Mining of Frequent Patterns over Transactional Data Streams
Abstract. We investigate the problem of finding frequent patterns in a continuous stream of transactions. It is recognized that the approximate solutions are usually sufficient and...
Willie Ng, Manoranjan Dash
PAKDD
2010
ACM
212views Data Mining» more  PAKDD 2010»
14 years 9 days ago
Fast Perceptron Decision Tree Learning from Evolving Data Streams
Abstract. Mining of data streams must balance three evaluation dimensions: accuracy, time and memory. Excellent accuracy on data streams has been obtained with Naive Bayes Hoeffdi...
Albert Bifet, Geoffrey Holmes, Bernhard Pfahringer...
KDD
2009
ACM
191views Data Mining» more  KDD 2009»
14 years 8 months ago
Efficient methods for topic model inference on streaming document collections
Topic models provide a powerful tool for analyzing large text collections by representing high dimensional data in a low dimensional subspace. Fitting a topic model given a set of...
Limin Yao, David M. Mimno, Andrew McCallum
CIKM
2001
Springer
13 years 11 months ago
Sliding-Window Filtering: An Efficient Algorithm for Incremental Mining
We explore in this paper an effective sliding-window filtering (abbreviatedly as SWF) algorithm for incremental mining of association rules. In essence, by partitioning a transact...
Chang-Hung Lee, Cheng-Ru Lin, Ming-Syan Chen