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Issues in the Use of Neural Networks in Information Retrieval de Iuliana F. Iatan

Issues in the Use of Neural Networks in Information Retrieval: Studies in Computational Intelligence, cartea 661

Autor Iuliana F. Iatan
en Limba Engleză Paperback – 15 iun 2018
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.
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Specificații

ISBN-13: 9783319829302
ISBN-10: 3319829300
Ilustrații: XIX, 199 p. 88 illus., 44 illus. in color.
Dimensiuni: 155 x 235 mm
Greutate: 0.31 kg
Ediția:Softcover reprint of the original 1st ed. 2017
Editura: Springer International Publishing
Colecția Springer
Seria Studies in Computational Intelligence

Locul publicării:Cham, Switzerland

Cuprins

Mathematical Aspects of Using Neural Approaches for Information
Retrieval.- A Fuzzy Kwan- Cai Neural Network for Determining Image Similarity and for the Face Recognition.- Predicting Human Personality from Social Media using a Fuzzy Neural Network.- Modern Neural Methods for Function Approximation.- A Fuzzy Gaussian Clifford Neural Network.- Concurrent Fuzzy Neural Networks.- A New Interval Arithmetic Based Neural Network.- A Recurrent Neural Fuzzy Network

Textul de pe ultima copertă

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.

Caracteristici

Highlights the ability of Neural Networks (NNs) to be excellent pattern matchers and their importance in information retrieval (IR) Defines a new neural-network-based method for learning image similarity and explains how to use fuzzy Gaussian neural networks to predict personality Describes the design of a new model of fuzzy nonlinear perceptron based on alpha level sets Includes supplementary material: sn.pub/extras