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» REDUS: finding reducible subspaces in high dimensional data
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VLDB
2004
ACM
163views Database» more  VLDB 2004»
13 years 10 months ago
Compressing Large Boolean Matrices using Reordering Techniques
Large boolean matrices are a basic representational unit in a variety of applications, with some notable examples being interactive visualization systems, mining large graph struc...
David S. Johnson, Shankar Krishnan, Jatin Chhugani...
SIGMOD
2008
ACM
158views Database» more  SIGMOD 2008»
14 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...
JMLR
2010
111views more  JMLR 2010»
13 years 3 days ago
Single versus Multiple Sorting in All Pairs Similarity Search
To save memory and improve speed, vectorial data such as images and signals are often represented as strings of discrete symbols (i.e., sketches). Chariker (2002) proposed a fast ...
Yasuo Tabei, Takeaki Uno, Masashi Sugiyama, Koji T...
DATAMINE
2006
224views more  DATAMINE 2006»
13 years 5 months ago
Characteristic-Based Clustering for Time Series Data
With the growing importance of time series clustering research, particularly for similarity searches amongst long time series such as those arising in medicine or finance, it is cr...
Xiaozhe Wang, Kate A. Smith, Rob J. Hyndman
EWCBR
2006
Springer
13 years 9 months ago
Rough Set Feature Selection Algorithms for Textual Case-Based Classification
Feature selection algorithms can reduce the high dimensionality of textual cases and increase case-based task performance. However, conventional algorithms (e.g., information gain)...
Kalyan Moy Gupta, David W. Aha, Philip Moore