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» Opportunistic Data Structures with Applications
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151
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SODA
2008
ACM
110views Algorithms» more  SODA 2008»
15 years 6 months ago
Why simple hash functions work: exploiting the entropy in a data stream
Hashing is fundamental to many algorithms and data structures widely used in practice. For theoretical analysis of hashing, there have been two main approaches. First, one can ass...
Michael Mitzenmacher, Salil P. Vadhan
ICDE
2008
IEEE
195views Database» more  ICDE 2008»
16 years 6 months ago
Scalable Rule-Based Gene Expression Data Classification
Abstract-- Current state-of-the-art association rule-based classifiers for gene expression data operate in two phases: (i) Association rule mining from training data followed by (i...
Mark A. Iwen, Willis Lang, Jignesh M. Patel
WWW
2008
ACM
16 years 5 months ago
Efficiently querying rdf data in triple stores
Efficiently querying RDF [1] data is being an important factor in applying Semantic Web technologies to real-world applications. In this context, many efforts have been made to st...
Ying Yan, Chen Wang, Aoying Zhou, Weining Qian, Li...
KDD
2002
ACM
152views Data Mining» more  KDD 2002»
16 years 5 months ago
Multimedia Data Mining Framework For Raw Video Sequences
In this paper, we propose a general framework for real time video data mining to be applied to the raw videos (traffic videos, surveillance videos, etc.). We investigate whether t...
Jung-Hwan Oh, Babitha Bandi
SIGMOD
2008
ACM
158views Database» more  SIGMOD 2008»
16 years 5 months ago
Sampling cube: a framework for statistical olap over sampling data
Sampling is a popular method of data collection when it is impossible or too costly to reach the entire population. For example, television show ratings in the United States are g...
Xiaolei Li, Jiawei Han, Zhijun Yin, Jae-Gil Lee, Y...