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» Phenomenal Data Mining: From Data to Phenomena
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PAKDD
2005
ACM
63views Data Mining» more  PAKDD 2005»
16 years 1 days ago
Pruning Derivative Partial Rules During Impact Rule Discovery
Because exploratory rule discovery works with data that is only a sample of the phenomena to be investigated, some resulting rules may appear interesting only by chance. Techniques...
Shiying Huang, Geoffrey I. Webb
APBC
2006
181views Bioinformatics» more  APBC 2006»
15 years 8 months ago
Analyzing Inconsistency Toward Enhancing Integration of Biological Molecular Databases
: The rapid growth of biological databases not only provides biologists with abundant data but also presents a big challenge in relation to the analysis of data. Many data analysis...
Yi-Ping Phoebe Chen, Qingfeng Chen
ICTAI
2005
IEEE
16 years 5 days ago
ACE: An Aggressive Classifier Ensemble with Error Detection, Correction, and Cleansing
Learning from noisy data is a challenging and reality issue for real-world data mining applications. Common practices include data cleansing, error detection and classifier ensemb...
Yan Zhang, Xingquan Zhu, Xindong Wu, Jeffrey P. Bo...
KDD
2005
ACM
147views Data Mining» more  KDD 2005»
16 years 2 days ago
Combining proactive and reactive predictions for data streams
Mining data streams is important in both science and commerce. Two major challenges are (1) the data may grow without limit so that it is difficult to retain a long history; and (...
Ying Yang, Xindong Wu, Xingquan Zhu
DEXA
2006
Springer
102views Database» more  DEXA 2006»
15 years 10 months ago
Mining RDF Metadata for Generalized Association Rules
In this paper, we present a novel frequent generalized pattern mining algorithm, called GP-Close, for mining generalized associations from RDF metadata. To solve the overgeneraliz...
Tao Jiang, Ah-Hwee Tan