Issues in the Use of Neural Networks in Information Retrieval
Authors: Iatan, Iuliana F.
Free Preview- 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
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- About this book
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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.
- Table of contents (8 chapters)
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Mathematical Aspects of Using Neural Approaches for Information Retrieval
Pages 1-35
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A Fuzzy Kwan–Cai Neural Network for Determining Image Similarity and for the Face Recognition
Pages 37-79
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Predicting Human Personality from Social Media Using a Fuzzy Neural Network
Pages 81-105
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Modern Neural Methods for Function Approximation
Pages 107-121
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A Fuzzy Gaussian Clifford Neural Network
Pages 123-142
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Table of contents (8 chapters)
- Download Sample pages 2 PDF (2.2 MB)
- Download Table of contents PDF (163.2 KB)
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Bibliographic Information
- Bibliographic Information
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- Book Title
- Issues in the Use of Neural Networks in Information Retrieval
- Authors
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- Iuliana F. Iatan
- Series Title
- Studies in Computational Intelligence
- Series Volume
- 661
- Copyright
- 2017
- Publisher
- Springer International Publishing
- Copyright Holder
- Springer International Publishing Switzerland
- eBook ISBN
- 978-3-319-43871-9
- DOI
- 10.1007/978-3-319-43871-9
- Hardcover ISBN
- 978-3-319-43870-2
- Softcover ISBN
- 978-3-319-82930-2
- Series ISSN
- 1860-949X
- Edition Number
- 1
- Number of Pages
- XIX, 199
- Number of Illustrations
- 44 b/w illustrations, 44 illustrations in colour
- Topics
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