Issues in the Use of Neural Networks in Information Retrieval

Iuliana F. Iatan

ISBN 10: 3319438700 / ISBN 13: 9783319438702

Editore: Springer International Publishing, 2016

Riguardo questo articolo

Druck auf Anfrage Neuware - Printed after ordering - This book highlights the ability of neural networks (NNs) to be excellent pattern matchers and their importance in information retrieval (IR), which is based on index term matching. The book defines a new NN-based method for learning image similarity and describes how to use fuzzy Gaussian neural networks to predict personality.It introduces the fuzzy Clifford Gaussian network, and two concurrent neural models: (1) concurrent fuzzy nonlinear perceptron modules, and (2) concurrent fuzzy Gaussian neural network modules.Furthermore, it explains the design of a new model of fuzzy nonlinear perceptron based on alpha level sets and describes a recurrent fuzzy neural network model with a learning algorithm based on the improved particle swarm optimization method.

Codice articolo 9783319438702

Dati bibliografici

• Titolo: Issues in the Use of Neural Networks in Information Retrieval
• Editore: Springer International Publishing
• Data di pubblicazione: 2016
• Lingua: Inglese
• ISBN 10: 3319438700
• ISBN 13: 9783319438702
• Rilegatura: Buch
• Condizione: Neu
• Dimensioni: 241 L x 160 A x 18 P (millimetri) 241 millimetri di larghezza per 160 millimetri di altezza per 18 millimetri di profondità
• Peso: 500 grammi

Descrizione articolo

Riassunto

This book highlights the ability of neural networks (NNs) to be excellent pattern matchers and their importance in information retrieval (IR), which is based on index term matching. The book defines a new NN-based method for learning image similarity and describes how to use fuzzy Gaussian neural networks to predict personality.

It introduces the fuzzy Clifford Gaussian network, and two concurrent neural models: (1) concurrent fuzzy nonlinear perceptron modules, and (2) concurrent fuzzy Gaussian neural network modules.

Furthermore, it explains the design of a new model of fuzzy nonlinear perceptron based on alpha level sets and describes a recurrent fuzzy neural network model with a learning algorithm based on the improved particle swarm optimization method.