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Big Data and Social Computing: 9th China National Conference, BDSC 2024, Harbin, China, August 8–10, 2024, Proceedings de Xiaofeng Meng

Big Data and Social Computing: 9th China National Conference, BDSC 2024, Harbin, China, August 8–10, 2024, Proceedings: Communications in Computer and Information Science, cartea 2161

Editat de Xiaofeng Meng, Zhidong Cao, Suran Wu, Yang Chen, Xiu-Xiu Zhan
en Limba Engleză Paperback – 16 sep 2024
This book constitutes the refereed proceedings of the 9th China National Conference on Big Data and Social Computing, BDSC 2024, held in Harbin, China, during August 8–10, 2024.
The 28 full papers presented in this volume were carefully reviewed and selected from a total of 141 submissions. The papers in the volume are organized according to the following topics: digital society and public security; modelling and simulation of social systems; internet intelligent algorithm governance; social network and group behavior; innovation, risks, and network security of large language models; and artificial intelligence and cognitive science.
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Specificații

ISBN-13: 9789819758029
ISBN-10: 9819758025
Pagini: 478
Ilustrații: XII, 465 p.
Dimensiuni: 155 x 235 mm
Ediția:2024
Editura: Springer Nature Singapore
Colecția Springer
Seria Communications in Computer and Information Science

Locul publicării:Singapore, Singapore

Cuprins

Digital Society and Public Security.- Early Warning Methods Based on a Real Time Series Dataset: a Comparative Study.- EG-ConMix: An Intrusion Detection Method based on Graph Contrastive Learning.- Network Analysis Reveals Regional Disparity in COVID-19 Policymaking.- Exploring Urban Spatio-temporal Patterns via Large-scale Vehicle Travel Data : The Role of Geographical Attributes and Traveler Characteristics.- Mapping Gridded Wealth Index Using Open Geospatial Data in Zambia.- Bidirectional Multi-grain Graph Convolution Network for Origin-Destination Demand Prediction.- Modelling and Simulation of Social Systems.- The Prospects of Multi-modal Pre-training Models in Epidemic Forecasting.- Deep Reinforcement Learning Based Dynamic Bus Timetable Scheduling with Bidirectional Constraints.- Modeling Knowledge Spillover Effects in High Speed Rail Development: A Discrete Simulation Approach Using Cellular Automata.- Educators' Networking Interacts with Digital Competence Heterogeneity to Enhance the Implementation of AIEd: A Mixed‐Methods Study.- Intelligent Fatigue Driving Detection Method Based on Fusion of Smartphone and Smartwatch Data.- SCPM-R+ER: A R+ER-based Algorithm for Mining Spatial Co-location Patterns.- Internet Intelligent Algorithm Governance.- Extracting Spatial High Utility Co-location Patterns Based on Fuzzy Feature Clusters.- Incremental Network Traffic Category Models Based on Hybrid Learning Strategies.- Modeling the BGP Prefix Hijack via Pollution and Recovery Processes.- A Weakly Supervised Method for Encrypted Traffic Classification in the Dark Web.- Rumor Detection Based on Conflict and Bot Features.- Social Network and Group Behavior.- A Study of Digital Nomad Culture and Local Social Practices -- Based on Fieldwork Research in a Certain Area of Southwest China.- Analysis of the Relationship Between Temperature and Insomnia Based on Social Media Text.- Do Gender Role Attitudes Affect Fertility Intentions ? — Evidence from International Data.- Dynamic Shifts: The Rise of Unicorns in the AI Ecosystem.- Measurement and Analysis of China's Fashion Events on Social Media: A Study of Shanghai Fashion Week.- Innovation, Risks, and Network Security of Large Language Models.- Enhanced Product Embedding with Sememe for Product Search.- FOKE: A Personalized and Explainable Education Framework Integrating Foundation Models, Knowledge Graphs, and Prompt Engineering.- Improving the Adversarial Transferability of Radio Signal with Denoising, Data Diversity, and Gradient Average.-Artificial Intelligence and Cognitive Science.- Temporal Knowledge Graph Reasoning: A Review.- The Impact of AI Trust Violation on Trustworthiness: An Empirical Study Based on AI Chatbots.- An Epileptic EEG Classification Approach with Spike Train Encoding Using Spiking Neural Networks.