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» Scalable Parallel Data Mining for Association Rules
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KDD
2005
ACM
153views Data Mining» more  KDD 2005»
14 years 9 months ago
Improving discriminative sequential learning with rare--but--important associations
Discriminative sequential learning models like Conditional Random Fields (CRFs) have achieved significant success in several areas such as natural language processing, information...
Xuan Hieu Phan, Minh Le Nguyen, Tu Bao Ho, Susumu ...
PKDD
2009
Springer
134views Data Mining» more  PKDD 2009»
14 years 3 months ago
Mining Graph Evolution Rules
In this paper we introduce graph-evolution rules, a novel type of frequency-based pattern that describe the evolution of large networks over time, at a local level. Given a sequenc...
Michele Berlingerio, Francesco Bonchi, Björn ...
ECAI
2008
Springer
13 years 10 months ago
Extracting Semantic Annotations from Moodle Data
The purpose of this paper is to provide a solution which allows automatic reasoning processes over Moodle activities logs, in order to obtain user-personalized recommendations. Act...
Mihai Gabroveanu, Ion-Mircea Diaconescu
IQIS
2004
ACM
14 years 2 months ago
Mining for Patterns in Contradictory Data
Information integration is often faced with the problem that different data sources represent the same set of the real-world objects, but give conflicting values for specific prop...
Heiko Müller, Ulf Leser, Johann Christoph Fre...
KDD
2005
ACM
89views Data Mining» more  KDD 2005»
14 years 9 months ago
Mining risk patterns in medical data
In this paper, we discuss a problem of finding risk patterns in medical data. We define risk patterns by a statistical metric, relative risk, which has been widely used in epidemi...
Jiuyong Li, Ada Wai-Chee Fu, Hongxing He, Jie Chen...