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KDD
2002
ACM
138views Data Mining» more  KDD 2002»
16 years 4 months ago
Learning to match and cluster large high-dimensional data sets for data integration
Part of the process of data integration is determining which sets of identifiers refer to the same real-world entities. In integrating databases found on the Web or obtained by us...
William W. Cohen, Jacob Richman
ICDM
2007
IEEE
175views Data Mining» more  ICDM 2007»
15 years 10 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
ICDM
2010
IEEE
217views Data Mining» more  ICDM 2010»
15 years 2 months ago
iSAX 2.0: Indexing and Mining One Billion Time Series
There is an increasingly pressing need, by several applications in diverse domains, for developing techniques able to index and mine very large collections of time series. Examples...
Alessandro Camerra, Themis Palpanas, Jin Shieh, Ea...
AI
2003
Springer
15 years 9 months ago
Efficient Mining of Indirect Associations Using HI-Mine
Discovering association rules is one of the important tasks in data mining. While most of the existing algorithms are developed for efficient mining of frequent patterns, it has be...
Qian Wan, Aijun An
JIIS
2006
124views more  JIIS 2006»
15 years 4 months ago
An efficient approach to mining indirect associations
Discovering association rules is one of the important tasks in data mining. While most of the existing algorithms are developed for efficient mining of frequent patterns, it has be...
Qian Wan, Aijun An