Call for Papers
Topics of Interest
Papers describing original work, as shown in any topic below, are invited. Acceptance will be based on quality, relevance, originality, and clarity. Topics of interest for submission include, but are not limited to:
Chapter One:
Intelligent Computing and Algorithmic Models
Machine Learning and Deep Learning: Reinforcement learning, transfer learning, federated learning, graph neural networks, and fine-tuning of pre-trained models.
Data Mining and Knowledge Discovery: Feature extraction from heterogeneous data, association rule mining, anomaly detection, and explainable AI (XAI).
Computer Vision and Pattern Recognition: Retail space analytics, behavioral trajectory tracking, product recognition, and biometric authentication.
Natural Language Processing: Sentiment analysis, semantic understanding for intelligent customer service, commercial text generation via large language models, and public opinion monitoring.
Distributed Computing and Edge Intelligence: Cloud–edge–device collaboration, real-time streaming data processing, and high-performance financial computing.
Chapter Two:
Big Data Analytics and Economic–Financial Modeling
Macroeconomics and Industrial Digitalization: Non-traditional big data for economic forecasting, industry chain mapping, and digital economy accounting.
Quantitative Finance and Algorithmic Trading: High-frequency data mining, investment optimization via deep reinforcement learning, value-at-risk models, and stress testing.
Blockchain and Digital Currencies: On-chain data analytics, volatility forecasting for crypto markets, DeFi risk assessment, and smart contract auditing.
Predictive Modeling and Operations Optimization: Supply chain risk forecasting, dynamic pricing, intelligent replenishment, and logistics route planning.
Chapter Three:
Digital Marketing, Consumer Behavior, and Intelligent Decision-Making
Precision Marketing: User profiling and recommendation systems, look-alike audience expansion, and real-time CTR/CVR estimation.
Multimodal Consumer Insights: Affective computing from voice, text, and vision; eye-tracking for experience analysis.
Social Networks and Opinion Analytics: Sentiment contagion on social media, KOL effectiveness evaluation, and misinformation detection.
Intelligent Decision Support Systems: Digital twin–based business simulation, data-driven visual dashboards, and human–machine collaborative decision-making.
Chapter Four:
Data Governance, Privacy Security, and Business Ethics
Privacy-Preserving Computing: Federated learning, secure multi-party computation, and trusted execution environments.
Data Compliance and Circulation: Anonymization algorithms, data pricing, and trading market design.
Algorithmic Fairness and Ethics: Bias mitigation, AI accountability, and auditability.