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...
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...
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...
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...
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...