Issues in the Use of Neural Networks in Information Retrieval, Softcover reprint of the original 1st ed. 2017 Studies in Computational Intelligence Series, Vol. 661
Langue : Anglais
Auteur : Iatan Iuliana F.
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.
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
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
Date de parution : 10-2016
Ouvrage de 199 p.
15.5x23.5 cm
Date de parution : 06-2018
Ouvrage de 199 p.
15.5x23.5 cm
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