1344 search results - page 123 / 269 » Learning Classifiers from Semantically Heterogeneous Data |
KDD
2009
ACM
14 years 10 months ago
2009
ACM
In this study, we formalize a multi-focal learning problem, where training data are partitioned into several different focal groups and the prediction model will be learned within...
MCS
2002
Springer
13 years 9 months ago
2002
Springer
Bagging and boosting are two popular ensemble methods that achieve better accuracy than a single classifier. These techniques have limitations on massive datasets, as the size of t...
SEMWEB
2007
Springer
14 years 4 months ago
2007
Springer
This document describes an ongoing commercial project that aims to model the cultural heritage domain in an ontology, containing data from eleven types of heritages, from bibliogra...
EMNLP
2004
13 years 11 months ago
2004
Anticipating the availability of large questionanswer datasets, we propose a principled, datadriven Instance-Based approach to Question Answering. Most question answering systems ...
WEBI
2005
Springer
14 years 3 months ago
2005
Springer
Schema matching is a complex process focusing on matching between concepts describing the data in heterogeneous data sources. There is a shift from manual schema matching, done by...