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» Sequential Inductive Learning
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WWW
2010
ACM
15 years 4 months ago
Factorizing personalized Markov chains for next-basket recommendation
Recommender systems are an important component of many websites. Two of the most popular approaches are based on matrix factorization (MF) and Markov chains (MC). MF methods learn...
Steffen Rendle, Christoph Freudenthaler, Lars Schm...
ATAL
2007
Springer
15 years 4 months ago
Learning consumer preferences using semantic similarity
In online, dynamic environments, the services requested by consumers may not be readily served by the providers. This requires the service consumers and providers to negotiate the...
Reyhan Aydogan, Pinar Yolum
SAC
2006
ACM
15 years 3 months ago
The impact of sample reduction on PCA-based feature extraction for supervised learning
“The curse of dimensionality” is pertinent to many learning algorithms, and it denotes the drastic raise of computational complexity and classification error in high dimension...
Mykola Pechenizkiy, Seppo Puuronen, Alexey Tsymbal
CORR
2002
Springer
142views Education» more  CORR 2002»
14 years 9 months ago
Learning Algorithms for Keyphrase Extraction
Many academic journals ask their authors to provide a list of about five to fifteen keywords, to appear on the first page of each article. Since these key words are often phrases ...
Peter D. Turney
GECCO
2003
Springer
112views Optimization» more  GECCO 2003»
15 years 3 months ago
Limits in Long Path Learning with XCS
The development of the XCS Learning Classifier System [26] has produced a stable implementation, able to consistently identify the accurate and optimally general population of cla...
Alwyn Barry