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ICDM
2006
IEEE
161views Data Mining» more  ICDM 2006»
14 years 1 months ago
Hierarchical Density Shaving: A clustering and visualization framework for large biological datasets
In many clustering applications for bioinformatics, only part of the data clusters into one or more groups while the rest needs to be pruned. For such situations, we present Hiera...
Gunjan Gupta, Alexander Liu, Joydeep Ghosh
SDM
2010
SIAM
181views Data Mining» more  SDM 2010»
13 years 9 months ago
Making k-means Even Faster
The k-means algorithm is widely used for clustering, compressing, and summarizing vector data. In this paper, we propose a new acceleration for exact k-means that gives the same a...
Greg Hamerly
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
WWW
2010
ACM
13 years 7 months ago
Mining advertiser-specific user behavior using adfactors
Consider an online ad campaign run by an advertiser. The ad serving companies that handle such campaigns record users' behavior that leads to impressions of campaign ads, as ...
Nikolay Archak, Vahab S. Mirrokni, S. Muthukrishna...
GECCO
2004
Springer
102views Optimization» more  GECCO 2004»
14 years 1 months ago
Dynamic and Scalable Evolutionary Data Mining: An Approach Based on a Self-Adaptive Multiple Expression Mechanism
Data mining has recently attracted attention as a set of efficient techniques that can discover patterns from huge data. More recent advancements in collecting massive evolving da...
Olfa Nasraoui, Carlos Rojas, Cesar Cardona