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

By:

Iatan, Iuliana F [aut]

Resource type: Ressourcentyp: Buch (Online)Book (Online)Language: English Series: Studies in Computational Intelligence ; 661 | SpringerLink Bücher | Springer eBook Collection EngineeringPublisher: Cham : Springer, 2017Description: Online-Ressource (XIX, 199 p. 88 illus., 44 illus. in color, online resource)ISBN:

9783319438719

Subject(s):

Additional physical formats: 9783319438702 | Erscheint auch als: 978-3-319-43870-2 Druck-Ausgabe | Printed edition: 9783319438702 DDC classification:

006.3

MSC: MSC: *68-02 | 68P20 | 68T05LOC classification:

Q342

DOI: DOI: 10.1007/978-3-319-43871-9Online resources:

Summary: 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 methodSummary: 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 NetworkPPN: PPN: 1658928377Package identifier: Produktsigel: ZDB-2-ENG

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