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A Deep Ranking Weighted Multihashing Recommender System for Item Recommendation.

Computational intelligence and neuroscience
Collaborative filtering (CF) techniques are used in recommender systems to provide users with specialised recommendations on social websites and in e-commerce. But they suffer from sparsity and cold start problems (CSP) and fail to interpret why they...

Artificial Intelligence Based Customer Churn Prediction Model for Business Markets.

Computational intelligence and neuroscience
The introduction of artificial intelligence (AI) and machine learning (ML) technologies in recent years has resulted in improved company performance. Customer churn forecast is a difficult problem in many corporate sectors, particularly the telecommu...

Application of Price Competition Model Based on Computational Neural Network in Risk Prediction of Transnational Investment.

Computational intelligence and neuroscience
Aiming at the scenario where edge devices rely on cloud servers for collaborative computing, this paper proposes an efficient edge-cloud collaborative reasoning method. In order to meet the application's specific requirements for delay or accuracy, a...

A Deep Spiking Neural Network Anomaly Detection Method.

Computational intelligence and neuroscience
Cyber-attacks on specialized industrial control systems are increasing in frequency and sophistication, which means stronger countermeasures need to be implemented, requiring the designers of the equipment in question to re-evaluate and redefine thei...

Digital Transformation and Financial Risk Prediction of Listed Companies.

Computational intelligence and neuroscience
Digitalization is a revolution, a frontal battleground in the new global competitive landscape, and a long-distance race for which all employees must be prepared, and organizations must actively embrace the resulting changes. The article begins by an...

Continuous biomanufacturing with microbes - upstream progresses and challenges.

Current opinion in biotechnology
Current biomanufacturing facilities are mainly built for batch or fed-batch operations, which are subject to low productivities and do not achieve the great bioconversion potential of the rewired cells generated via modern biotechnology. Continuous b...

Item Relationship Graph Neural Networks for E-Commerce.

IEEE transactions on neural networks and learning systems
In a modern e-commerce recommender system, it is important to understand the relationships among products. Recognizing product relationships-such as complements or substitutes-accurately is an essential task for generating better recommendation resul...

Human Resource Demand Prediction and Configuration Model Based on Grey Wolf Optimization and Recurrent Neural Network.

Computational intelligence and neuroscience
Business development is dependent on a well-structured human resources (HR) system that maximizes the efficiency of an organization's human resources input and output. It is tough to provide adequate instructions for HR's unique task. In a time when ...

Lightweight Deep Learning Model for Marketing Strategy Optimization and Characteristic Analysis.

Computational intelligence and neuroscience
The business model of traditional market is declining day by day, and people's consumption cognition has risen to a new level with the leap in science and technology. Enterprises need to adjust and optimize their marketing strategies in time accordin...

Neural Network Model of Dynamic Prediction of Cross-Border E-Commerce Sales for Virtual Community Knowledge Sharing.

Computational intelligence and neuroscience
The current popular one with forecasting method simply studies for prediction, and insufficient consideration is given to the prediction of the evolution of product sales applied to Internet platforms. To improve the forecast effect and to realize th...