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» Approximate data mining in very large relational data
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KDD
2004
ACM
195views Data Mining» more  KDD 2004»
16 years 1 months ago
Improved robustness of signature-based near-replica detection via lexicon randomization
Detection of near duplicate documents is an important problem in many data mining and information filtering applications. When faced with massive quantities of data, traditional d...
Aleksander Kolcz, Abdur Chowdhury, Joshua Alspecto...
INFOCOM
2010
IEEE
15 years 17 hour ago
Tracking Quantiles of Network Data Streams with Dynamic Operations
— Quantiles are very useful in characterizing the data distribution of an evolving dataset in the process of data mining or network monitoring. The method of Stochastic Approxima...
Jin Cao, Li (Erran) Li, Aiyou Chen, Tian Bu
CCGRID
2010
IEEE
15 years 2 months ago
High Performance Dimension Reduction and Visualization for Large High-Dimensional Data Analysis
Abstract--Large high dimension datasets are of growing importance in many fields and it is important to be able to visualize them for understanding the results of data mining appro...
Jong Youl Choi, Seung-Hee Bae, Xiaohong Qiu, Geoff...
ICDE
2006
IEEE
222views Database» more  ICDE 2006»
16 years 2 months ago
CLAN: An Algorithm for Mining Closed Cliques from Large Dense Graph Databases
Most previously proposed frequent graph mining algorithms are intended to find the complete set of all frequent, closed subgraphs. However, in many cases only a subset of the freq...
Jianyong Wang, Zhiping Zeng, Lizhu Zhou
ICDE
2002
IEEE
146views Database» more  ICDE 2002»
16 years 2 months ago
Data Mining Meets Performance Evaluation: Fast Algorithms for Modeling Bursty Traffic
Network, web, and disk I/O traffic are usually bursty, self-similar [9, 3, 5, 6] and therefore can not be modeled adequately with Poisson arrivals[9]. However, we do want to model...
Mengzhi Wang, Ngai Hang Chan, Spiros Papadimitriou...