Sciweavers

IJCAI
2003
13 years 6 months ago
Multiset Ordering Constraints
We identify a new and important global (or nonbinary) constraint which ensures that the values taken by two vectors of variables, when viewed as multisets, are ordered. This const...
Alan M. Frisch, Ian Miguel, Zeynep Kiziltan, Brahi...
IJCAI
2003
13 years 6 months ago
An Ontology-based Architecture for Cooperative Information Agents
Frederico Luiz Gonçalves de Freitas, Guilhe...
IJCAI
2003
13 years 6 months ago
Extending DTGOLOG with Options
Alexander Ferrein, Christian Fritz, Gerhard Lakeme...
IJCAI
2003
13 years 6 months ago
Qualitative Decision under Uncertainty: Back to Expected Utility
Different qualitative models have been proposed for decision under uncertainty in Artificial Intelli­ gence, but they generally fail to satisfy the princi­ ple of strict Pareto ...
Hélène Fargier, Régis Sabbadi...
IJCAI
2003
13 years 6 months ago
Spaces of Theories with Ideal Refinement Operators
Refinement operators for theories avoid the problems related to the myopia of many relational learning algorithms based on the operators that refine single clauses. However, the n...
Nicola Fanizzi, Stefano Ferilli, Nicola Di Mauro, ...
IJCAI
2003
13 years 6 months ago
Inductive Learning in Less Than One Sequential Data Scan
Most recent research of scalable inductive learning on very large dataset, decision tree construction in particular, focuses on eliminating memory constraints and reducing the num...
Wei Fan, Haixun Wang, Philip S. Yu, Shaw-hwa Lo
IJCAI
2003
13 years 6 months ago
The Knowledge Required to Interpret Noun Compounds
Noun compound interpretation is the task of determining the semantic relations among the constituents of a noun compound. For example, "concrete floor" means a floor mad...
James Fan, Ken Barker, Bruce W. Porter
IJCAI
2003
13 years 6 months ago
A semantic framework for multimedia document adaptation
With the proliferation of heterogeneous devices (desktop computers, personal digital assistants, phones), multimedia documents must be played under various constraints (small scre...
Jérôme Euzenat, Nabil Layaïda, V...
IJCAI
2003
13 years 6 months ago
Monte Carlo Theory as an Explanation of Bagging and Boosting
In this paper we propose the framework of Monte Carlo algorithms as a useful one to analyze ensemble learning. In particular, this framework allows one to guess when bagging will ...
Roberto Esposito, Lorenza Saitta