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Issues in the Use of Neural Networks in Information Retrieval 1st ed. 2017 [Kõva köide]

  • Formaat: Hardback, 199 pages, kõrgus x laius: 235x155 mm, kaal: 4557 g, 44 Illustrations, color; 44 Illustrations, black and white; XIX, 199 p. 88 illus., 44 illus. in color., 1 Hardback
  • Sari: Studies in Computational Intelligence 661
  • Ilmumisaeg: 07-Oct-2016
  • Kirjastus: Springer International Publishing AG
  • ISBN-10: 3319438700
  • ISBN-13: 9783319438702
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Issues in the Use of Neural Networks in Information Retrieval 1st ed. 2017Suurem pilt
  • Formaat: Hardback, 199 pages, kõrgus x laius: 235x155 mm, kaal: 4557 g, 44 Illustrations, color; 44 Illustrations, black and white; XIX, 199 p. 88 illus., 44 illus. in color., 1 Hardback
  • Sari: Studies in Computational Intelligence 661
  • Ilmumisaeg: 07-Oct-2016
  • Kirjastus: Springer International Publishing AG
  • ISBN-10: 3319438700
  • ISBN-13: 9783319438702
Teised raamatud teemal:
Püsilink: https://www.kriso.ee/db/9783319438702.html
Märksõnad:
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.

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
1 Mathematical Aspects of Using Neural Approaches for Information Retrieval
1(36)
1.1 Information Retrieval Models
3(4)
1.2 Mathematical Background
7(10)
1.2.1 Discrete Cosine Transformation
7(1)
1.2.2 Algorithm for Image Compression Using Discrete Cosine Transformation
8(4)
1.2.3 Multilayer Nonlinear Perceptron
12(3)
1.2.4 Fuzzy Neural Perceptron
15(2)
1.3 A New Approach of a Possibility Function Based Neural Network
17(1)
1.4 Architecture of the PFBNN
18(2)
1.5 Training Algorithm of the PBFNN
20(6)
1.6 Neural Networks-Based IR
26(11)
1.6.1 Keyword Recognition Approach Based on the Fuzzy Multilayer Perceptron
28(3)
1.6.2 Text Document Retrieval Approach on the Base of a Spreading Activation Neural Network
31(3)
References
34(3)
2 A Fuzzy Kwan-Cai Neural Network for Determining Image Similarity and for the Face Recognition
37(44)
2.1 Introduction
37(3)
2.2 Related Work
40(1)
2.3 Background
41(12)
2.3.1 Measure of the Class Similarities
41(1)
2.3.2 Similarity-Based Classification
42(4)
2.3.3 Using Kohonen Algorithm in Vector Quantization
46(1)
2.3.4 Fourier Descriptors
47(4)
2.3.5 Fuzzy Neurons
51(2)
2.4 Fuzzy Kwan-Cai Neural Network
53(6)
2.4.1 Architecture of FKCNN
54(3)
2.4.2 Training Algorithm of FKCNN
57(1)
2.4.3 Analysis of FKCNN
58(1)
2.5 Experimental Evaluation
59(7)
2.5.1 Data Sets
59(1)
2.5.2 Evaluation Criteria
60(2)
2.5.3 Experimental Results
62(4)
2.6 Face Recognition
66(15)
2.6.1 Applying the Fuzzy Kwan-Cai Neural Network for Face Recognition
69(6)
2.6.2 Applying Kohonen Maps for Feature Selection
75(2)
References
77(4)
3 Predicting Human Personality from Social Media Using a Fuzzy Neural Network
81(26)
3.1 Classifying Personality Traits
81(3)
3.2 Related Work
84(1)
3.2.1 Personality and Word Use
84(1)
3.2.2 Neural Methods
84(1)
3.3 A Neural Network for Predicting Personality
85(13)
3.3.1 Regression Using Neural Networks
86(2)
3.3.2 Fuzzy Gaussian Neural Network
88(1)
3.3.3 Architecture
89(2)
3.3.4 Basic Equations
91(2)
3.3.5 On-Line Weight Initialization
93(1)
3.3.6 Training Algorithm
94(4)
3.4 Experimental Evaluation
98(9)
3.4.1 Task, Data Set, Data Processing and Evaluation Details
98(2)
3.4.2 Baselines
100(1)
3.4.3 Experimental Setup
101(1)
3.4.4 Experimental Results and Analysis
102(2)
References
104(3)
4 Modern Neural Methods for Function Approximation
107(16)
4.1 Mathematical Background
107(4)
4.1.1 Discrete Fourier Transform
108(2)
4.1.2 Numerical Methods for Function Approximation
110(1)
4.2 Fourier Series Neural Network (FSNN)
111(3)
4.3 A New Neural Network for Function Approximation
114(3)
4.4 Experimental Evaluation
117(6)
References
121(2)
5 A Fuzzy Gaussian Clifford Neural Network
123(20)
5.1 Introduction
123(5)
5.1.1 Basics of Clifford Algebras
124(1)
5.1.2 Generation of Clifford Algebras
125(3)
5.2 Background
128(2)
5.2.1 Fuzzy Gaussian Neural Network (FGNN)
128(1)
5.2.2 Using the Clifford Algebras in Neural Computing
128(2)
5.3 Fuzzy Clifford Gaussian Neural Network (FCGNN)
130(6)
5.3.1 Basic Equations
130(1)
5.3.2 On-Line Weight Initialization
131(3)
5.3.3 Training Algorithm
134(2)
5.4 Experimental Evaluation
136(7)
5.4.1 2D Rotation with Euler's Equation
136(1)
5.4.2 3D Rotation with Quaternion
137(1)
5.4.3 Data Sets
138(3)
5.4.4 Experimental Results
141(1)
References
142(1)
6 Concurrent Fuzzy Neural Networks
143(28)
6.1 Baselines
143(3)
6.1.1 Principal Component Analysis
143(3)
6.2 Face Recognition Using the Stage of the Feature Selection with PCA/DCT
146(4)
6.3 ECG Classification in the Case of the Feature Selection with PCA/DCT
150(12)
6.4 Concurrent Fuzzy Nonlinear Perceptron Modules
162(3)
6.5 Concurrent Fuzzy Gaussian Neural Network Modules
165(2)
6.6 Experimental Results
167(4)
References
169(2)
7 A New Interval Arithmetic-Based Neural Network
171(16)
7.1 The Representation of the Fuzzy Numbers
171(8)
7.1.1 Representing the Fuzzy Numbers by a Finite Number of Membership Values
174(2)
7.1.2 Representing the Fuzzy Numbers by a Finite Number of Alpha level Sets
176(3)
7.2 A New Fuzzy Nonlinear Perceptron Based on Alpha Level Sets
179(8)
7.2.1 Network Architecture
179(4)
7.2.2 The Training Algorithm of FNPALS
183(3)
References
186(1)
8 A Recurrent Neural Fuzzy Network
187
8.1 Introduction
187(5)
8.1.1 Wavelet Neural Networks
189(1)
8.1.2 Z-Transform
190(1)
8.1.3 Application of Genetic Algorithms
191(1)
8.2 RNFN Architecture
192(2)
8.3 Learning Algorithm of RNFN
194
References
198