Research on E-Commerce Applications Based on Neural Network

Pang, Jiangang

doi:10.1166/jctn.2016.5406

Cited by 5 publications

(3 citation statements)

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“…Based on this, this paper proposes to use the customer social behavior data on the we-media platform to build a customer identification model. Pang et al proposed a method for calculating semantic similarity of Chinese words based on WordNet, which has become the main basis for calculating emotional polarity strength of Chinese words [5]. Peng et al studied the problem of feature recognition of comment objects.…”

Section: Introductionmentioning

confidence: 99%

Research on E-Commerce Customer Feature Extraction Question Answering System Based on Artificial Intelligence Semantic Analysis

Niu

2022

Advances in Multimedia

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In order to analyze e-commerce customer behavior and preference, a migration identification method of consumer behavior tendency is proposed. Data mining technology is adopted to mine social data in individual online we-media platforms and to mine individual personal attributes and preferences from their unconscious social language. Its methods are through the customer identification model construction related research, consumer preference identification and analysis related research, based on data mining technology of consumer preference identification and analysis, and the introduction of feature extraction method: semantic analysis. According to the data, there are 2,990 customer interest consumption forecasts, 1,836 customer social network data consumption forecasts, and 3,652 customer preference consumption forecasts. In order to screen out the main factors that have the greatest impact on consumer behavior from all kinds of consumer behavior propensity factors, the multiple step-based regression method is adopted for factor selection. Because of the large difference in the multidimensional dynamic vector, the corresponding consumer behavior tendency changes greatly, so the migration identification method of consumer behavior tendency is feasible.

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Section: Introductionmentioning

confidence: 99%

Research on E-Commerce Customer Feature Extraction Question Answering System Based on Artificial Intelligence Semantic Analysis

Niu

2022

Advances in Multimedia

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“…The back propagation (BP) nervous system is a multilayer network trained according to the error-backpropagation algorithm and is one of the most widely used models in the study of current nervous systems 2 . The principle of the BP neuropsychological study is to use a feedforward network with backscattering, without adjusting the level and weight of the network, thus reducing the sum of the square network errors 3 . There is no feedback link between individual neurons in the BP neurological model.…”

Section: Introductionmentioning

confidence: 99%

“…2 The principle of the BP neuropsychological study is to use a feedforward network with backscattering, without adjusting the level and weight of the network, thus reducing the sum of the square network errors. 3 There is no feedback link between individual neurons in the BP neurological model. The three-layered local structure consists of an obvious forward neural network with supporting layers.…”

Section: Introductionmentioning

confidence: 99%

(Retracted) Research on computer network security evaluation based on image recognition and neural network

Wang

Shi

Chen³

et al. 2022

J. Electron. Imag.

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.In today’s social development, the level of informatization has been greatly improved. Computer networks are now used in all aspects of society, especially with the popularity of mobile phones and computers. Basically, a mobile phone is a computer that stores all the information of a person, so it is indispensable for carrying out research on computer network security evaluation. The purpose of this article is to examine the growing state of information security threats in computer networks. Neural network technology, which is considered secure, has high flexibility, fast access to information, strong logic, and low failure. Toward creating a low-cost network topology, we used a low-cost network risk assessment method to assess the security of computer networks based on neural networks, and we evaluated existing risks that are appropriate for future computer security research. The results of the study show that neural networks using the Bayesian network method have a significant impact on network security. Considering the problems that can occur with information security risks, computer security systems based on neural networks have a 30% reduction in information error rate compared with traditional methods, and computer network systems based on neural networks have better learning performance to safeguard network security. Improving the security of information requires further research and evaluation of computer network security based on neural networks.

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Investment risk model based on intelligent fuzzy neural network and VaR

Zhang

2020

Journal of Computational and Applied Mathematics

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Research on E-Commerce Applications Based on Neural Network

Cited by 5 publications

References 0 publications

Research on E-Commerce Customer Feature Extraction Question Answering System Based on Artificial Intelligence Semantic Analysis

Research on E-Commerce Customer Feature Extraction Question Answering System Based on Artificial Intelligence Semantic Analysis

(Retracted) Research on computer network security evaluation based on image recognition and neural network

Investment risk model based on intelligent fuzzy neural network and VaR

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