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Issues in the use of neural networks in information retrieval

紀錄類型:	書目-語言資料,印刷品 : Monograph/item
正題名/作者:	Issues in the use of neural networks in information retrieval/ by Iuliana F. Iatan.
作者:	Iatan, Iuliana F.
出版者:	Cham :Springer International Publishing : : 2017.,
面頁冊數:	xix, 199 p. :ill. (some col.), digital ; : 24 cm.;
Contained By:	Springer eBooks
標題:	Neural networks (Computer science) -
電子資源:	http://dx.doi.org/10.1007/978-3-319-43871-9
ISBN:	9783319438719

Issues in the use of neural networks in information retrieval
Iatan, Iuliana F.

Issues in the use of neural networks in information retrieval[electronic resource] /by Iuliana F. Iatan. - Cham :Springer International Publishing :2017. - xix, 199 p. :ill. (some col.), digital ;24 cm. - Studies in computational intelligence,v.6611860-949X ;. - Studies in computational intelligence ;v. 50. .

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.

ISBN: 9783319438719

Standard No.: 10.1007/978-3-319-43871-9doiSubjects--Topical Terms:

528588
Neural networks (Computer science)

LC Class. No.: QA76.87

Dewey Class. No.: 006.32

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520 $a 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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