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» A Model of Inductive Bias Learning
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KDD
2005
ACM
109views Data Mining» more  KDD 2005»
14 years 5 months ago
Overcoming Incomplete User Models in Recommendation Systems Via an Ontology
Abstract. To make accurate recommendations, recommendation systems currently require more data about a customer than is usually available. We conjecture that the weaknesses are due...
Vincent Schickel-Zuber, Boi Faltings
KDD
1994
ACM
96views Data Mining» more  KDD 1994»
13 years 9 months ago
DICE: A Discovery Environment Integrating Inductive Bias
: Most of Knowledge Discovery in Database (KDD) systems are integrating efficient Machine Learning techniques. In fact issues in Machine Learning and KDD are very close allowing fo...
Jean-Daniel Zucker, Vincent Corruble, J. Thomas, G...
ACL
2008
13 years 6 months ago
Analyzing the Errors of Unsupervised Learning
We identify four types of errors that unsupervised induction systems make and study each one in turn. Our contributions include (1) using a meta-model to analyze the incorrect bia...
Percy Liang, Dan Klein
GIS
2008
ACM
14 years 5 months ago
Pedestrian flow prediction in extensive road networks using biased observational data
In this paper, we discuss an application of spatial data mining to predict pedestrian flow in extensive road networks using a large biased sample. Existing out-of-the-box techniqu...
Michael May, Simon Scheider, Roberto Rösler, ...
EMNLP
2010
13 years 2 months ago
Unsupervised Induction of Tree Substitution Grammars for Dependency Parsing
Inducing a grammar directly from text is one of the oldest and most challenging tasks in Computational Linguistics. Significant progress has been made for inducing dependency gram...
Phil Blunsom, Trevor Cohn