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IDA
2008
Springer
13 years 8 months ago
Symbolic methodology for numeric data mining
Currently statistical and artificial neural network methods dominate in data mining applications. Alternative relational (symbolic) data mining methods have shown their effectivene...
Boris Kovalerchuk, Evgenii Vityaev
KDD
2010
ACM
245views Data Mining» more  KDD 2010»
13 years 10 months ago
Learning incoherent sparse and low-rank patterns from multiple tasks
We consider the problem of learning incoherent sparse and lowrank patterns from multiple tasks. Our approach is based on a linear multi-task learning formulation, in which the spa...
Jianhui Chen, Ji Liu, Jieping Ye
KDD
2000
ACM
121views Data Mining» more  KDD 2000»
14 years 8 days ago
Mining high-speed data streams
Many organizations today have more than very large databases; they have databases that grow without limit at a rate of several million records per day. Mining these continuous dat...
Pedro Domingos, Geoff Hulten
EDM
2010
154views Data Mining» more  EDM 2010»
13 years 7 months ago
Can We Get Better Assessment From A Tutoring System Compared to Traditional Paper Testing? Can We Have Our Cake (Better Assessme
Dynamic assessment (DA) has been advocated as an interactive approach to conduct assessments to students in the learning systems as it can differentiate student proficiency at a fi...
Mingyu Feng, Neil T. Heffernan
KDD
2005
ACM
139views Data Mining» more  KDD 2005»
14 years 2 months ago
Learning to predict train wheel failures
This paper describes a successful but challenging application of data mining in the railway industry. The objective is to optimize maintenance and operation of trains through prog...
Chunsheng Yang, Sylvain Létourneau