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139
Voted
KDD
2005
ACM
127views Data Mining» more  KDD 2005»
16 years 5 months ago
Detection of emerging space-time clusters
We propose a new class of spatio-temporal cluster detection methods designed for the rapid detection of emerging space-time clusters. We focus on the motivating application of pro...
Daniel B. Neill, Andrew W. Moore, Maheshkumar Sabh...
KDD
2004
ACM
134views Data Mining» more  KDD 2004»
16 years 5 months ago
Exploiting a support-based upper bound of Pearson's correlation coefficient for efficiently identifying strongly correlated pair
Given a user-specified minimum correlation threshold and a market basket database with N items and T transactions, an all-strong-pairs correlation query finds all item pairs with...
Hui Xiong, Shashi Shekhar, Pang-Ning Tan, Vipin Ku...
144
Voted
KDD
2004
ACM
166views Data Mining» more  KDD 2004»
16 years 5 months ago
Predicting prostate cancer recurrence via maximizing the concordance index
In order to effectively use machine learning algorithms, e.g., neural networks, for the analysis of survival data, the correct treatment of censored data is crucial. The concordan...
Lian Yan, David Verbel, Olivier Saidi
SAC
2009
ACM
15 years 11 months ago
Applying latent dirichlet allocation to group discovery in large graphs
This paper introduces LDA-G, a scalable Bayesian approach to finding latent group structures in large real-world graph data. Existing Bayesian approaches for group discovery (suc...
Keith Henderson, Tina Eliassi-Rad
ICMCS
2007
IEEE
164views Multimedia» more  ICMCS 2007»
15 years 11 months ago
Medical Visual Information Retrieval: State of the Art and Challenges Ahead
Today’s medical institutions produce enormous amounts of data on patients, including multimedia data, which is increasingly produced in digital form. These data in their clinica...
Henning Müller, Xin Zhou, Adrien Depeursinge,...