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SAC
2010
ACM
14 years 10 months ago
A study on interestingness measures for associative classifiers
Associative classification is a rule-based approach to classify data relying on association rule mining by discovering associations between a set of features and a class label. Su...
Mojdeh Jalali Heravi, Osmar R. Zaïane
126
Voted
KDD
2007
ACM
159views Data Mining» more  KDD 2007»
16 years 3 months ago
Local decomposition for rare class analysis
Given its importance, the problem of predicting rare classes in large-scale multi-labeled data sets has attracted great attentions in the literature. However, the rare-class probl...
Junjie Wu, Hui Xiong, Peng Wu, Jian Chen
133
Voted
SIGIR
2010
ACM
15 years 7 months ago
Self-taught hashing for fast similarity search
The ability of fast similarity search at large scale is of great importance to many Information Retrieval (IR) applications. A promising way to accelerate similarity search is sem...
Dell Zhang, Jun Wang, Deng Cai, Jinsong Lu
CVPR
2009
IEEE
16 years 10 months ago
Picking the best DAISY
Local image descriptors that are highly discriminative, computational efficient, and with low storage footprint have long been a dream goal of computer vision research. In this ...
Gang Hua, Matthew Brown, Simon A. J. Winder
PVLDB
2010
129views more  PVLDB 2010»
15 years 1 months ago
AXART - Enabling Collaborative Work with AXML Artifacts
The workflow models have been essentially operation-centric for many years, ignoring almost completely the data aspects. Recently, a new paradigm of data-centric workflows, call...
Bogdan Marinoiu, Serge Abiteboul, Pierre Bourhis, ...