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KDD
2006
ACM
156views Data Mining» more  KDD 2006»
16 years 2 months ago
Unsupervised learning on k-partite graphs
Various data mining applications involve data objects of multiple types that are related to each other, which can be naturally formulated as a k-partite graph. However, the resear...
Bo Long, Xiaoyun Wu, Zhongfei (Mark) Zhang, Philip...
KDD
2006
ACM
213views Data Mining» more  KDD 2006»
16 years 2 months ago
Learning sparse metrics via linear programming
Calculation of object similarity, for example through a distance function, is a common part of data mining and machine learning algorithms. This calculation is crucial for efficie...
Glenn Fung, Rómer Rosales
KDD
2004
ACM
173views Data Mining» more  KDD 2004»
16 years 2 months ago
A microeconomic data mining problem: customer-oriented catalog segmentation
The microeconomic framework for data mining [7] assumes that an enterprise chooses a decision maximizing the overall utility over all customers where the contribution of a custome...
Martin Ester, Rong Ge, Wen Jin, Zengjian Hu
KDD
2001
ACM
203views Data Mining» more  KDD 2001»
16 years 2 months ago
Ensemble-index: a new approach to indexing large databases
The problem of similarity search (query-by-content) has attracted much research interest. It is a difficult problem because of the inherently high dimensionality of the data. The ...
Eamonn J. Keogh, Selina Chu, Michael J. Pazzani
RECOMB
2004
Springer
16 years 2 months ago
The Statistical Significance of Max-Gap Clusters
Identifying gene clusters, genomic regions that share local similarities in gene organization, is a prerequisite for many different types of genomic analyses, including operon pred...
Rose Hoberman, David Sankoff, Dannie Durand