Title :
An adaptive function neural network (ADFUNN) for phrase recognition
Author :
Kang, Miao ; Palmer-Brown, Dominic
Author_Institution :
Sch. of Comput., Leeds Metropolitan Univ., UK
fDate :
31 July-4 Aug. 2005
Abstract :
We describe an adaptive function neural network (ADFUNN) by the authors (2005), and apply it to the natural language processing task of phrase recognition. ADFUNN is based on a linear piecewise neuron activation function that is modified by a novel gradient descent supervised learning algorithm. Linearly inseparable problems can he learned with ADFUNN, rapidly and without hidden neurons. We perform phrase recognition on a set of phrases from the Lancaster parsed corpus (LPC) by R. Garside, et al. (1987). Generalisation rises to 100% with 150 training patterns (out of a total of 254).
Keywords :
generalisation (artificial intelligence); gradient methods; learning (artificial intelligence); natural languages; neural nets; Lancaster parsed corpus; adaptive function neural network; generalisation; gradient descent supervised learning algorithm; linear piecewise neuron activation function; natural language processing; phrase recognition; Adaptive systems; Biological neural networks; Biology computing; Computational intelligence; Computer networks; Electronic mail; Multilayer perceptrons; Neural networks; Neurons; Testing;
Conference_Titel :
Neural Networks, 2005. IJCNN '05. Proceedings. 2005 IEEE International Joint Conference on
Print_ISBN :
0-7803-9048-2
DOI :
10.1109/IJCNN.2005.1555898