Issues in the Use of Neural Networks in Information Retrieval (Hardcover)

Iuliana F. Iatan

ISBN 10: 3319438700 / ISBN 13: 9783319438702

Editore: Springer International Publishing AG, Cham, 2016

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Hardcover. 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. Shipping may be from multiple locations in the US or from the UK, depending on stock availability.

Codice articolo 9783319438702

Dati bibliografici

• Titolo: Issues in the Use of Neural Networks in Information Retrieval (Hardcover)
• Editore: Springer International Publishing AG, Cham
• Data di pubblicazione: 2016
• Lingua: Inglese
• ISBN 10: 3319438700
• ISBN 13: 9783319438702
• Rilegatura: Hardcover
• Edizione: prima edizione
• Condizione: new

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.