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» Discovering Frequent Closed Itemsets for Association Rules
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PARMA
2004
191views Database» more  PARMA 2004»
13 years 9 months ago
Identifying Most Predictive Items
Abstract. Frequent itemsets and association rules are generally accepted concepts in analyzing item-based databases. The Apriori-framework was developed for analyzing categorical d...
Markus Wawryniuk, Daniel A. Keim
KDD
2002
ACM
196views Data Mining» more  KDD 2002»
14 years 8 months ago
Comparing Two Recommender Algorithms with the Help of Recommendations by Peers
Abstract. Since more and more Web sites, especially sites of retailers, offer automatic recommendation services using Web usage mining, evaluation of recommender algorithms has bec...
Andreas Geyer-Schulz, Michael Hahsler
ICDM
2006
IEEE
130views Data Mining» more  ICDM 2006»
14 years 1 months ago
A Framework for Regional Association Rule Mining in Spatial Datasets
The immense explosion of geographically referenced data calls for efficient discovery of spatial knowledge. One critical requirement for spatial data mining is the capability to ...
Wei Ding 0003, Christoph F. Eick, Jing Wang 0007, ...
ICMCS
2009
IEEE
199views Multimedia» more  ICMCS 2009»
13 years 5 months ago
Association rule mining in multiple, multidimensional time series medical data
Time series pattern mining (TSPM) finds correlations or dependencies in same series or in multiple time series. When the numerous instances of multiple time series data are associ...
Gaurav N. Pradhan, B. Prabhakaran
ICMCS
2007
IEEE
124views Multimedia» more  ICMCS 2007»
14 years 2 months ago
Video Semantic Concept Discovery using Multimodal-Based Association Classification
Digital audio and video have recently taken a center stage in the communication world, which highlights the importance of digital media information management and indexing. It is ...
Lin Lin, Guy Ravitz, Mei-Ling Shyu, Shu-Ching Chen