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» Theoretical Frameworks for Data Mining
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ICASSP
2011
IEEE
12 years 11 months ago
Belief theoretic methods for soft and hard data fusion
In many contexts, one is confronted with the problem of extracting information from large amounts of different types soft data (e.g., text) and hard data (from e.g., physics-based...
Thanuka Wickramarathne, Kamal Premaratne, Manohar ...
PAKDD
2004
ACM
127views Data Mining» more  PAKDD 2004»
14 years 1 months ago
Separating Structure from Interestingness
Condensed representations of pattern collections have been recognized to be important building blocks of inductive databases, a promising theoretical framework for data mining, and...
Taneli Mielikäinen
SDM
2009
SIAM
107views Data Mining» more  SDM 2009»
14 years 4 months ago
A Semi-Supervised Framework for Feature Mapping and Multiclass Classification.
Bo Chen, Ivor Tsang, Tak-Lam Wong, Wai Lam
ADMI
2009
Springer
14 years 2 months ago
Agent-Enriched Data Mining Using an Extendable Framework
An extendable and generic Agent Enriched Data Mining (AEDM) framework, EMADS (the Extendable Multi-Agent Data mining System) is described. The central feature of the framework is ...
Kamal Ali Albashiri, Frans Coenen
ACMSE
2008
ACM
13 years 9 months ago
Mining frequent sequential patterns with first-occurrence forests
In this paper, a new pattern-growth algorithm is presented to mine frequent sequential patterns using First-Occurrence Forests (FOF). This algorithm uses a simple list of pointers...
Erich Allen Peterson, Peiyi Tang