Big Data Analytics and Knowledge Discovery

28th International Conference, DaWaK 2026, Graz, Austria, August 11–13, 2026, Proceedings
Erscheinungsjahr 2026
ISBN: 978-3-032-34895-1
Verlag: Springer

Buch, Englisch, 363 Seiten, Format (B × H): 155 mm x 235 mm

Reihe: Lecture Notes in Computer Science

This book constitutes the proceedings of the 28th International Conference on Big Data Analytics and Knowledge Discovery, DaWaK 2026, held in Graz, Austria, during August 11–13, 2026.

The 17 full papers and 11 Short papers included in this book were carefully reviewed and selected from 65 submissions. They focus on Mature, Well-Developed Research, Novel, Early-Stage Research, Emerging Concepts, and Preliminary Findings.

Zielgruppe

Research

Autoren/Hrsg.

Ordonez, Carlos

Kotsis, Gabriele

Tjoa, A Min

Khalil, Ismail

Fachgebiete

• Mathematik | Informatik EDV | Informatik Informatik Künstliche Intelligenz Wissensbasierte Systeme, Expertensysteme
• Mathematik | Informatik EDV | Informatik Angewandte Informatik
• Mathematik | Informatik EDV | Informatik Daten / Datenbanken Data Mining

Inhaltsverzeichnis

.- Invited Paper.
 
.- Finding Prominent Clusters in VAT Family of Algorithms. 

.- Responsible AI & Learning 

.- BALM: Bias-Aware Generation for Large Language Models. 
.- FAIRTOPIA: A Multi-Agent Guardianship Framework for Disrupting Unfair AI Pipelines.
.- ACAT: A Collaborative Platform for Efficient Aspect-Based Sentiment Dataset Annotation.
.- Calibration improves detection of mislabeled examples. 
.- Q-Matrix Learning Based on Graph Attention Neural Network for Knowledge Tracing. 
.- Q-dEclat: A Vertical Quantitative Frequent Pattern Mining Algorithm.

.- Data Lakes & Lakehouses.
 
.- Hybrid Table Annotation in Data Lakes. 
.- Context-aware Data Quality Management in Data Lakes.
.- Discovering Relationships in Data Lakes Using Large Language Models: An Industrial Case.
.- LLM-Assisted Metadata Query Answering on Data Warehouses.
.- SmartIngest: A Unified Framework for Adaptive Data Ingestion and Management in Lakehouse Architectures.

.- Time Series & Machine Learning.

.- MoE-TFT: Mixture-of-Experts Enhanced Temporal Fusion Transformer for Time Series Forecasting.
.- CODA: A Coordinate-Driven Autoencoder for Robust Multivariate Time Series Anomaly Detection.
.- Topologically-Constrained Any-Variate Time-Series Foundation Models for Twinning of Continuous Industrial Processes.
.- ConvTransAKD: Multi-Level Wasserstein Alignment for Efficient Knowledge Distillation in Sensor-Based Activity Recognition.
.- ANNOYing HDBSCAN for clustering.
.- Evaluating Time-Dependent Risk Trajectories through Class–Cluster Alignment.

.- Data Integration & Quality.

.- KAN-ER: Kolmogorov-Arnold Networks-based Entity Resolution in Data Lakes.
.- Leveraging Tattoo Description Classification in Historical Record Linkage.
.- ASOS-CRM: Automated Semantic Scoping for CIDOC CRM Population.
.- Relational Database Data Lineage Ontology.
.- Data Profiling for Change Rules.
.- Causally-constrained Power Indices: Predicate Attribution for Aggregate Query Explanations.

.- Database & Graph Systems.

.- Database Tuning via Distributional Reinforcement Learning for Hybrid Transactional/Analytical Processing Workload.
.- How Good are Learned and Hybrid Join Order Strategies from Energy Perspective.
.- GPU-Accelerated Dependency Graph Construction and Conflict Analysis for Preventing Read-Only Anomalies.
.- Evaluating Sustainability in Graph Intelligence.
.- A Verifiable Query Processing for Distributed Property Graphs.