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» Learning Rules and Their Exceptions
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ANLP
1997
111views more  ANLP 1997»
14 years 11 months ago
An Improvement in the Selection Process of Machine Translation Using Inductive Learning with Genetic Algorithms
We proposed a method of machine translation using inductive learning with genetic algorithms, and confirmed the effectiveness of applying genetic algorithms. However, the system b...
Hiroshi Echizen-ya, Kenji Araki, Yoshikazu Miyanag...
NEUROSCIENCE
2001
Springer
15 years 2 months ago
Analysis and Synthesis of Agents That Learn from Distributed Dynamic Data Sources
We propose a theoretical framework for specification and analysis of a class of learning problems that arise in open-ended environments that contain multiple, distributed, dynamic...
Doina Caragea, Adrian Silvescu, Vasant Honavar
CIKM
2005
Springer
15 years 3 months ago
A hybrid approach to NER by MEMM and manual rules
This paper describes a framework for defining domain specific Feature Functions in a user friendly form to be used in a Maximum Entropy Markov Model (MEMM) for the Named Entity Re...
Moshe Fresko, Binyamin Rosenfeld, Ronen Feldman
CORR
2008
Springer
216views Education» more  CORR 2008»
14 years 10 months ago
Building an interpretable fuzzy rule base from data using Orthogonal Least Squares Application to a depollution problem
In many fields where human understanding plays a crucial role, such as bioprocesses, the capacity of extracting knowledge from data is of critical importance. Within this framewor...
Sébastien Destercke, Serge Guillaume, Brigi...
EUSFLAT
2003
115views Fuzzy Logic» more  EUSFLAT 2003»
14 years 11 months ago
A hierarchical fuzzy rule-based learning system based on an information theoretic
This paper proposes a new novel method for the online construction of a Hierarchical Fuzzy Rule Based System (FRBS) to accurately model a function while retaining a level of human...
Antony Waldock, Brian Carse, Chris Melhuish