Big Data Analytics and Knowledge Discovery
Description
This book constitutes the proceedings of the 27th International Conference on Big Data Analytics and Knowledge Discovery, DaWaK 2025, held in Bangkok, Thailand, during August 25-27, 2025.
The 12 full and 14 short papers included in the proceedings were carefully reviewed and selected from 62 submissions. The proceedings also contain one keynote talk, one invited talk and one tutorial. The papers were organized in topical sections as follows: Data mining and knowledge discovery; sequential data analytics and recommendation systems; graph data processing and analytics; data management and indices; Large language Models (LLMs); and Neural Networks.
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Content
.- Keynote Talk.
.- Sparse Matrix Algorithms for Evolving Neural Networks.
.- Invited Talk.
.- Data integration in the AI era: research trends and still open issues.
.- Tutorial.
.- Leveraging machine learning techniques for customer data deduplication-hard-won lessons from a real-world project in the financial industry,
.- Data mining and knowledge discovery.
.- FairFES - Fast Exact Sampling for Fair Classification.
.- Autism Detection by Analyzing Handwriting Characteristics of Chinese Characters via Deep Learning Models.
.- FNoDe: Faulty Node Detection in Microservices Architecture.
.- An Enhanced FP-Growth Algorithm with Hybrid Adaptive Support Threshold for Association Rule Mining.
.- Sequential data analytics and recommendation systems.
.- Entity Resolution for Streaming Data with Embeddings.
.- Cross-Modal Sequential Point-of-Interest Recommendation with Lightweight Hybrid Fusion Strategy.
.- Alternatives to Shallow Autoencoders for Collaborative Filtering.
.- Accurate Concept Drift Detection without Updating Autoencoders.
.- Graph data processing and analytics.
.- Parallel and Distributed SQL/PGQ Query Processing for Property Graphs.
.- Graph Constraint Language for Industrial Knowledge Graphs and Machine Learning.
.- SemViSG : Semantic Enrichment and Visualization of Software Graphs.
.- Data management and Indices.
.- Certainty Attacks Using Explainability Preprocessing.
.- Integrating Bitcoin Transactions into Relational Databases for IoT: Challenges and Solutions.
.- Effects of Response Length on User Search Experience in Spoken Conversational Search.
.- Fair Proportional Top-k Ranking.
.- PAID: Power-efficient AI-optimized Databases.
.- On the Costs and Benefits of Learned Indexing for Dynamic High-Dimensional Data.
.- A Bayesian Reinforcement Learning Framework for Online Index Tuning.
.- Large language models (LLMs).
.- Explaining Recovery Trajectories of Older Adults Post Lower-Limb Fracture Using Modality-wise Multiview Clustering and Large Language Models.
.- Parameter Drift as a Signal for Membership Inference in Overfit-Tuned LLMs.
.- MicroSuggest: Kernel-Aware Microservice Decomposition.
.- TraceTune: Targeted Fine-Tuning of Attention Heads for Text-to-SQL.
.- Neural networks.
.- ONNYX : Optimized Neural Networks Yielding eXplainable insights from ECG signals-based data streams.
.- SpaPool: Soft Partition Assignment Pooling for Graph Neural Networks.
.- Prediction of iterative solvers' convergence using pretraining by natural images.
.- Local-aware Convolutional Modulation for Short-Term Sequential Recommendation.