Hao / Velásquez / Li | Behavioural and Social Computing | Buch | 978-981-957140-6 | www.sack.de

Buch, Englisch, Band 16432, 512 Seiten, Format (B × H): 155 mm x 235 mm, Gewicht: 791 g

Reihe: Behavioural and Social Computing

Hao / Velásquez / Li

Behavioural and Social Computing

12th International Conference, BESC 2025, Hong Kong SAR, China, October 16-18, 2025, Proceedings, Part II
Erscheinungsjahr 2026
ISBN: 978-981-957140-6
Verlag: Springer Nature B.V.

12th International Conference, BESC 2025, Hong Kong SAR, China, October 16-18, 2025, Proceedings, Part II

Buch, Englisch, Band 16432, 512 Seiten, Format (B × H): 155 mm x 235 mm, Gewicht: 791 g

Reihe: Behavioural and Social Computing

ISBN: 978-981-957140-6
Verlag: Springer Nature B.V.


This three-volume set LNCS 16431-16433 constitutes the refereed proceedings of the 12th International Conference on Behavioural and Social Computing, BESC 2025 held in Hong Kong SAR, China, during October 16–18, 2025.

The 18 full papers and 5 short papers presented in this volumes were carefully reviewed and selected from 149 submissions.

These papers focus on various aspects of social computing, applied psychology, behaviour pattern learning, text and sentiment
analysis, graph learning, AI in education, and AI for social good.

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Research

Weitere Infos & Material


.- MyEcoPal: Bridging the Gap between Sustainability Understanding and Sustainable Actions.

.- Uncovering the Nexus Between Attitudes Toward LLMs and Problematic Dependency on Them: A Latent Profile Analysis.

.- The Effectiveness of Balanced Product Explanations for Decision Support in Online Shopping.

.- How Warnings of Product Drawbacks Affect Online Shopping Decisions.

.- Temporal Inference of Psychosocial States from Digital Biomarkers for Just-In-Time Adaptive Interventions.

.- Exploring Global Patterns of Social Media Disorder: The Role of Sociodemographic Factors.

.- Research and Application of AI Decision System for Perioperative Period Based on Smart IoT and WIRE Database.

.- Real-Time Multimodal Hazard Detection for Assistive Wheelchair Navigation.

.- Density Harmonized Gradient Descent Online Active Learning for Imbalanced Data Streams.

.- Early Detection of Multimodal Hot-Topic Misinformation in User-Generated Content.

.- Prompt-based Zero-shot Learning in Large Language Models for Recommender Systems: A Reproducibility Study.

.- MacCDR: a Memory-Augmented Cluster-Level Preference Mapping Framework for Cross-Domain Cold-Start Recommendation.

.- PFRCRP: Parameter-Factorized Personalized Federated Recommendation for Cross-Domain Rating Predictions.

.- Enhancing the Training Process with Multi Metrics for Session-based Recommendations.

.- Interpretable Recommendation via Semantic and Syntactic Knowledge Enhanced Aspect-based Sentiment Analysis.

.- Large-scale Weakly Supervised Person Re-ID: Towards Generalizable and Scalable Solutions.

.- ExamEaseVR: An Immersive Virtual Reality Exposure System for Alleviating Test Anxiety.

.- An Exploration of ChatGPT in Personalized Learning: Behavioral Flow Analysis of Graduate Student Interactions.

.- Design and Implementation of an AI Agent-Based Collaborative Platform for Software Engineering Education.

.- Designing an Interactive Al-Supported Learning System for Mathematics Education in Primary Schools.

.- Theory-Informed vs. Example-Driven Prompting for LLM-Based Qualitative Data Coding in Educational Research.

.- DFST-Net:Dual-Frequency Spatiotemporal Graph Neural Network for Traffic Forecasting.

.- Analysis of Tongue Image Data Augmentation and Classification Methods Based on Multi-Attribute Features.

.- Discovering Brain Functional Connectivity in Parkinson's Disease from Graph Mining  Perspectives.

.- Machine Learning-Ready Genomic Biomarkers: ATF3 Polymorphisms Predict Postoperative Analgesic Demand Through AI-Compatible Phenotyping.

.- Dual-Level Contrastive Learning for Patient Condition Representation with Multimodal Electronic Health Records.

.- Text-Enhanced Panoptic Symbol Spotting in CAD Drawings.

.- Ensemble Transformer-Based Multiple Instance Learning for Predicting Neoadjuvant Chemotherapy Response from Breast Cancer Biopsy Whole-Slide Images.

.- DCKG: A Dual-view Collaborative Knowledge Graph for Pull Request Recommendation.

.- Optimized Feature Extraction and Alignment for Cross-Modal Molecule Retrieval.

.- MolJury: A Role-Driven Multi-Agent Architecture for Factual Molecular Understanding.

.- EquiMapLE: High-Fidelity and High-Throughput Molecular Analogue Screening with Equivariant Fingerprints and Learned Fusion.

.- KGsteeredDTI: Drug-Target Interaction Prediction via Knowledge Graphs-Steering.



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