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Issues in the use of neural networks in information retrieval

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 ne...

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Detalles Bibliográficos
Autor principal: Iatan, Iuliana F
Lenguaje:eng
Publicado: Springer 2017
Materias:
Acceso en línea:https://dx.doi.org/10.1007/978-3-319-43871-9
http://cds.cern.ch/record/2240626
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author Iatan, Iuliana F
author_facet Iatan, Iuliana F
author_sort Iatan, Iuliana F
collection CERN
description 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.
id cern-2240626
institution Organización Europea para la Investigación Nuclear
language eng
publishDate 2017
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spelling cern-22406262021-04-21T19:23:26Zdoi:10.1007/978-3-319-43871-9http://cds.cern.ch/record/2240626engIatan, Iuliana FIssues in the use of neural networks in information retrievalEngineeringThis 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.Springeroai:cds.cern.ch:22406262017
spellingShingle Engineering
Iatan, Iuliana F
Issues in the use of neural networks in information retrieval
title Issues in the use of neural networks in information retrieval
title_full Issues in the use of neural networks in information retrieval
title_fullStr Issues in the use of neural networks in information retrieval
title_full_unstemmed Issues in the use of neural networks in information retrieval
title_short Issues in the use of neural networks in information retrieval
title_sort issues in the use of neural networks in information retrieval
topic Engineering
url https://dx.doi.org/10.1007/978-3-319-43871-9
http://cds.cern.ch/record/2240626
work_keys_str_mv AT iataniulianaf issuesintheuseofneuralnetworksininformationretrieval