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DAWAK
2007
Springer
15 years 6 months ago
Mining Top-K Multidimensional Gradients
Several business applications such as marketing basket analysis, clickstream analysis, fraud detection and churning migration analysis demand gradient data analysis. By employing g...
Ronnie Alves, Orlando Belo, Joel Ribeiro
SDM
2004
SIAM
123views Data Mining» more  SDM 2004»
15 years 1 months ago
Nonlinear Manifold Learning for Data Stream
There has been a renewed interest in understanding the structure of high dimensional data set based on manifold learning. Examples include ISOMAP [25], LLE [20] and Laplacian Eige...
Martin H. C. Law, Nan Zhang 0002, Anil K. Jain
KDD
2000
ACM
77views Data Mining» more  KDD 2000»
15 years 3 months ago
Small is beautiful: discovering the minimal set of unexpected patterns
A drawback of most traditional data mining methods is that they do not leverage prior knowledge of users. In many business settings, managers and analysts have significant intuiti...
Balaji Padmanabhan, Alexander Tuzhilin
ESWA
2008
128views more  ESWA 2008»
14 years 12 months ago
Mining the data from a hyperheuristic approach using associative classification
Associative classification is a promising classification approach that utilises association rule mining to construct accurate classification models. In this paper, we investigate ...
Fadi A. Thabtah, Peter I. Cowling
APBC
2004
132views Bioinformatics» more  APBC 2004»
15 years 1 months ago
Identifying Character Non-Independence in Phylogenetic Data Using Data Mining Techniques
Undiscovered relationships in a data set may confound analyses, particularly those that assume data independence. Such problems occur when characters used for phylogenetic analyse...
Anne M. Maglia, Jennifer L. Leopold, Venkat Ram Gh...