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» Approximation Algorithms for Hamming Clustering Problems
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CSDA
2006
84views more  CSDA 2006»
14 years 9 months ago
Three-mode partitioning
The three-mode partitioning model is a clustering model for three-way three-mode data sets that implies a simultaneous partitioning of all three modes involved in the data. In the...
Jan Schepers, Iven Van Mechelen, Eva Ceulemans
BIOCOMP
2008
14 years 11 months ago
Prediction of Protein Function Using Graph Container and Message Passing
We introduce a novel parameter called container flux, which is used to measure the information sharing capacity between two distinct nodes in a graph. Other useful information, bot...
Hongbo Zhou, Qiang Shawn Cheng, Mehdi Zargham
FOCS
2000
IEEE
15 years 2 months ago
The Randomness Recycler: A New Technique for Perfect Sampling
For many probability distributions of interest, it is quite difficult to obtain samples efficiently. Often, Markov chains are employed to obtain approximately random samples fro...
James Allen Fill, Mark Huber
SIGMOD
1998
ACM
150views Database» more  SIGMOD 1998»
15 years 1 months ago
Extracting Schema from Semistructured Data
Semistructured data is characterized by the lack of any fixed and rigid schema, although typically the data hassomeimplicitstructure. While thelack offixedschemamakesextracting ...
Svetlozar Nestorov, Serge Abiteboul, Rajeev Motwan...
ICDM
2009
IEEE
121views Data Mining» more  ICDM 2009»
15 years 4 months ago
Finding Time Series Motifs in Disk-Resident Data
—Time series motifs are sets of very similar subsequences of a long time series. They are of interest in their own right, and are also used as inputs in several higher-level data...
Abdullah Mueen, Eamonn J. Keogh, Nima Bigdely Sham...