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Issues in the Use of Neural Networks in Information Retrieval [electronic resource] / by Iuliana F. Iatan.

By: Iatan, Iuliana F [author.].
Contributor(s): SpringerLink (Online service).
Material type: materialTypeLabelBookSeries: Studies in Computational Intelligence: 661Publisher: Cham : Springer International Publishing : Imprint: Springer, 2017Edition: 1st ed. 2017.Description: XIX, 199 p. 88 illus., 44 illus. in color. online resource.Content type: text Media type: computer Carrier type: online resourceISBN: 9783319438719.Subject(s): Computational intelligence | Artificial intelligence | Neural networks (Computer science)  | Pattern recognition systems | Computational Intelligence | Artificial Intelligence | Mathematical Models of Cognitive Processes and Neural Networks | Automated Pattern RecognitionAdditional physical formats: Printed edition:: No title; Printed edition:: No title; Printed edition:: No titleDDC classification: 006.3 Online resources: Click here to access online
Contents:
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.
In: Springer Nature eBookSummary: 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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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.

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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