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» Measuring Similarity between Sets of Overlapping Clusters
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ICDT
2001
ACM
147views Database» more  ICDT 2001»
15 years 2 months ago
Parallelizing the Data Cube
This paper presents a general methodology for the efficient parallelization of existing data cube construction algorithms. We describe two different partitioning strategies, one f...
Frank K. H. A. Dehne, Todd Eavis, Susanne E. Hambr...
KDD
2005
ACM
161views Data Mining» more  KDD 2005»
15 years 10 months ago
Combining email models for false positive reduction
Machine learning and data mining can be effectively used to model, classify and discover interesting information for a wide variety of data including email. The Email Mining Toolk...
Shlomo Hershkop, Salvatore J. Stolfo
STOC
2004
ACM
145views Algorithms» more  STOC 2004»
15 years 10 months ago
Using mixture models for collaborative filtering
A collaborative filtering system at an e-commerce site or similar service uses data about aggregate user behavior to make recommendations tailored to specific user interests. We d...
Jon M. Kleinberg, Mark Sandler
ISVLSI
2007
IEEE
184views VLSI» more  ISVLSI 2007»
15 years 4 months ago
Activity-Aware Registers Placement for Low Power Gated Clock Tree Construction
As power consumption of the clock tree dominates over 40% of the total power in modern high performance VLSI designs, measures must be taken to keep it under control. One of the m...
Weixiang Shen, Yici Cai, Xianlong Hong, Jiang Hu
BMCBI
2010
110views more  BMCBI 2010»
14 years 9 months ago
Discovering local patterns of co - evolution: computational aspects and biological examples
Background: Co-evolution is the process in which two (or more) sets of orthologs exhibit a similar or correlative pattern of evolution. Co-evolution is a powerful way to learn abo...
Tamir Tuller, Yifat Felder, Martin Kupiec