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KDD
2005
ACM
153views Data Mining» more  KDD 2005»
16 years 5 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 ...
188
Voted
DAGSTUHL
2009
15 years 6 months ago
Learning Highly Structured Manifolds: Harnessing the Power of SOMs
Abstract. In this paper we elaborate on the challenges of learning manifolds that have many relevant clusters, and where the clusters can have widely varying statistics. We call su...
Erzsébet Merényi, Kadim Tasdemir, Li...
164
Voted
AIRWEB
2008
Springer
15 years 7 months ago
Web spam identification through content and hyperlinks
We present an algorithm, witch, that learns to detect spam hosts or pages on the Web. Unlike most other approaches, it simultaneously exploits the structure of the Web graph as we...
Jacob Abernethy, Olivier Chapelle, Carlos Castillo
ECTEL
2006
Springer
15 years 8 months ago
Getting to Know Your Student in Distance Learning Contexts
Abstract. Good teachers know their students, and exploit this knowledge to adapt or optimise their instruction. Teachers know their students because they interact with them face-to...
Claus Zinn, Oliver Scheuer
146
Voted
KDD
2005
ACM
139views Data Mining» more  KDD 2005»
15 years 10 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