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ICDM
2007
IEEE
175views Data Mining» more  ICDM 2007»
14 years 2 months ago
gApprox: Mining Frequent Approximate Patterns from a Massive Network
Recently, there arise a large number of graphs with massive sizes and complex structures in many new applications, such as biological networks, social networks, and the Web, deman...
Chen Chen, Xifeng Yan, Feida Zhu, Jiawei Han
SIGMOD
2010
ACM
186views Database» more  SIGMOD 2010»
14 years 14 days ago
Fast approximate correlation for massive time-series data
We consider the problem of computing all-pair correlations in a warehouse containing a large number (e.g., tens of thousands) of time-series (or, signals). The problem arises in a...
Abdullah Mueen, Suman Nath, Jie Liu
RTCSA
2005
IEEE
14 years 1 months ago
Approximation Algorithms for Scheduling Multiple Feasible Interval Jobs
Abstract— Time-critical jobs in many real-time applications have multiple feasible intervals. Such a job is constrained to execute from start to completion in one of its feasible...
Jian-Jia Chen, Jun Wu, Chi-Sheng Shih, Tei-Wei Kuo
SDM
2003
SIAM
183views Data Mining» more  SDM 2003»
13 years 9 months ago
ApproxMAP: Approximate Mining of Consensus Sequential Patterns
Conventional sequential pattern mining methods may meet inherent difficulties in mining databases with long sequences and noise. They may generate a huge number of short and trivi...
Hye-Chung Kum, Jian Pei, Wei Wang 0010, Dean Dunca...
FOGA
2011
12 years 11 months ago
Approximating the distribution of fitness over hamming regions
The distribution of fitness values across a set of states sharply influences the dynamics of evolutionary processes and heuristic search in combinatorial optimization. In this p...
Andrew M. Sutton, Darrell Whitley, Adele E. Howe