Meng / Cao / Wu | Big Data and Social Computing | E-Book | sack.de
E-Book

E-Book, Englisch, Band 2161, 478 Seiten, eBook

Reihe: Communications in Computer and Information Science

Meng / Cao / Wu Big Data and Social Computing

9th China National Conference, BDSC 2024, Harbin, China, August 8–10, 2024, Proceedings

E-Book, Englisch, Band 2161, 478 Seiten, eBook

Reihe: Communications in Computer and Information Science

ISBN: 978-981-97-5803-6
Verlag: Springer Singapore
Format: PDF
Kopierschutz: 1 - PDF Watermark



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.

Meng / Cao / Wu Big Data and Social Computing jetzt bestellen!

Zielgruppe


Research

Weitere Infos & Material


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.


Ihre Fragen, Wünsche oder Anmerkungen
Vorname*
Nachname*
Ihre E-Mail-Adresse*
Kundennr.
Ihre Nachricht*
Lediglich mit * gekennzeichnete Felder sind Pflichtfelder.
Wenn Sie die im Kontaktformular eingegebenen Daten durch Klick auf den nachfolgenden Button übersenden, erklären Sie sich damit einverstanden, dass wir Ihr Angaben für die Beantwortung Ihrer Anfrage verwenden. Selbstverständlich werden Ihre Daten vertraulich behandelt und nicht an Dritte weitergegeben. Sie können der Verwendung Ihrer Daten jederzeit widersprechen. Das Datenhandling bei Sack Fachmedien erklären wir Ihnen in unserer Datenschutzerklärung.