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KDD
2007
ACM
165views Data Mining» more  KDD 2007»
14 years 10 months ago
Efficient and effective explanation of change in hierarchical summaries
Dimension attributes in data warehouses are typically hierarchical (e.g., geographic locations in sales data, URLs in Web traffic logs). OLAP tools are used to summarize the measu...
Deepak Agarwal, Dhiman Barman, Dimitrios Gunopulos...
KDD
2006
ACM
156views Data Mining» more  KDD 2006»
14 years 10 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
115views Data Mining» more  KDD 2006»
14 years 10 months ago
Supervised probabilistic principal component analysis
Principal component analysis (PCA) has been extensively applied in data mining, pattern recognition and information retrieval for unsupervised dimensionality reduction. When label...
Shipeng Yu, Kai Yu, Volker Tresp, Hans-Peter Krieg...
CHI
2007
ACM
14 years 10 months ago
A cognitive constraint model of dual-task trade-offs in a highly dynamic driving task
The paper describes an approach to modeling the strategic variations in performing secondary tasks while driving. In contrast to previous efforts that are based on simulation of a...
Duncan P. Brumby, Andrew Howes, Dario D. Salvucci
POPL
2008
ACM
14 years 10 months ago
Imperative self-adjusting computation
Self-adjusting computation enables writing programs that can automatically and efficiently respond to changes to their data (e.g., inputs). The idea behind the approach is to stor...
Umut A. Acar, Amal Ahmed, Matthias Blume