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ICDM
2003
IEEE
140views Data Mining» more  ICDM 2003»
15 years 3 months ago
Mining Frequent Itemsets in Distributed and Dynamic Databases
Traditional methods for frequent itemset mining typically assume that data is centralized and static. Such methods impose excessive communication overhead when data is distributed...
Matthew Eric Otey, Chao Wang, Srinivasan Parthasar...
KDD
2005
ACM
125views Data Mining» more  KDD 2005»
15 years 10 months ago
Email data cleaning
Addressed in this paper is the issue of `email data cleaning' for text mining. Many text mining applications need take emails as input. Email data is usually noisy and thus i...
Jie Tang, Hang Li, Yunbo Cao, ZhaoHui Tang
FGCS
2007
86views more  FGCS 2007»
14 years 9 months ago
A grid-based approach for enterprise-scale data mining
Abstract— We describe a grid-based approach for enterprisescale data mining that leverages database technology for I/O parallelism, and on-demand compute servers for compute para...
Ramesh Natarajan, Radu Sion, Thomas Phan
GFKL
2004
Springer
135views Data Mining» more  GFKL 2004»
15 years 3 months ago
KMC/EDAM: A New Approach for the Visualization of K-Means Clustering Results
In this work we introduce a method for classification and visualization. In contrast to simultaneous methods like e.g. Kohonen SOM this new approach, called KMC/EDAM, runs through...
Nils Raabe, Karsten Luebke, Claus Weihs
ICDM
2006
IEEE
149views Data Mining» more  ICDM 2006»
15 years 3 months ago
Pattern Mining in Frequent Dynamic Subgraphs
Graph-structured data is becoming increasingly abundant in many application domains. Graph mining aims at finding interesting patterns within this data that represent novel knowl...
Karsten M. Borgwardt, Hans-Peter Kriegel, Peter Wa...