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ADC
2003
Springer
182views Database» more  ADC 2003»
14 years 18 days ago
CT-ITL : Efficient Frequent Item Set Mining Using a Compressed Prefix Tree with Pattern Growth
Discovering association rules that identify relationships among sets of items is an important problem in data mining. Finding frequent item sets is computationally the most expens...
Yudho Giri Sucahyo, Raj P. Gopalan
CVPR
2010
IEEE
14 years 3 months ago
Object-Graphs for Context-Aware Category Discovery
How can knowing about some categories help us to discover new ones in unlabeled images? Unsupervised visual category discovery is useful to mine for recurring objects without huma...
Yong Jae Lee, Kristen Grauman
IDEAL
2003
Springer
14 years 17 days ago
Experiences of Using a Quantitative Approach for Mining Association Rules
In recent years interest has grown in “mining” large databases to extract novel and interesting information. Knowledge Discovery in Databases (KDD) has been recognised as an em...
L. Dong, Christos Tjortjis
CINQ
2004
Springer
125views Database» more  CINQ 2004»
14 years 23 days ago
The Hows, Whys, and Whens of Constraints in Itemset and Rule Discovery
Many researchers in our community (this author included) regularly emphasize the role constraints play in improving performance of data-mining algorithms. This emphasis has led to ...
Roberto J. Bayardo
GECCO
2006
Springer
159views Optimization» more  GECCO 2006»
13 years 11 months ago
Identification of weak motifs in multiple biological sequences using genetic algorithm
Recognition of motifs in multiple unaligned sequences provides an insight into protein structure and function. The task of discovering these motifs is very challenging because mos...
Topon Kumar Paul, Hitoshi Iba