Advances in Intelligent Data Analysis XXIII : 23rd International Symposium on Intelligent Data Analysis, IDA 2025, Konstanz, Germany, May 7–9, 2025, Proceedings / edited by Georg Krempl, Kai Puolamäki, Ioanna Miliou.

Format:

Book

Contributor:

Krempl, Georg, Editor.

Puolamäki, Kai., Editor.

Miliou, Ioanna., Editor.

Series:

Lecture Notes in Computer Science, 1611-3349 ; 15669

Language:

English

Subjects (All):

Database management.

Education--Data processing.

Education.

Image processing--Digital techniques.

Image processing.

Computer vision.

Artificial intelligence.

Machine learning.

Natural language processing (Computer science).

Database Management System.

Computers and Education.

Computer Imaging, Vision, Pattern Recognition and Graphics.

Artificial Intelligence.

Machine Learning.

Natural Language Processing (NLP).

Local Subjects:

Database Management System.

Computers and Education.

Computer Imaging, Vision, Pattern Recognition and Graphics.

Artificial Intelligence.

Machine Learning.

Natural Language Processing (NLP).

Physical Description:

1 online resource (XVI, 486 p. 117 illus., 111 illus. in color.)

Edition:

1st ed. 2025.

Place of Publication:

Cham : Springer Nature Switzerland : Imprint: Springer, 2025.

Summary:

This volume constitutes the proceedings of the 23rd International Symposium on Intelligent Data Analysis, IDA 2025, which was held in Konstanz, Germany, during May 7–9, 2025. The 35 full papers included in the proceedings were carefully reviewed and selected from 91 submissions. They were organized in topical sections as follows: Applications of data science, foundations of data science; natural language processing; temporal and streaming data; and explainable and interpretable data science. .

Contents:

Applications of Data Science

Credal Knowledge Tracing for Imprecise and Uncertain MCQ

Development of Models to Quantify Training Load in Outdoor Running using Inertial Sensors

Estimating the Learning Capacity of Bacterial Metabolic Networks

Semi-supervised learning with pairwise instance comparisons for medical instance classification

Local-global Data Augmentation for Contrastive Learning in Static Sign Language Recognition

SiamCircle: Trajectory Representation Learning in Free Settings

Synthetic Tabular Data Detection In the Wild

Assessing the Impact of Graph Structure Learning in Graph Deviation Networks

Foundations of Data Science

The When and How of Target Variable Transformations

Balancing performance and scalability of demand forecasting ML models

Balancing global importance and source proximity for personalized recommendations using random walk length

Counterintuitive Behavior of Clustering Quality: Findings for K-Means on Synthetic and Real Data

BOWSA: a contribution of sensitivity analysis to improve Bayesian optimization for parameter tuning

Overfitting in Combined Algorithm Selection and Hyperparameter Optimization

Local Subgroup Discovery on Attributed Network Graphs

Imposing Constraints in Probabilistic Circuits via Gradient Optimization

Natural Language Processing

Improving Next Tokens via Second-Last Predictions with ’Generate and Refine’

Detection of Large Language Model Contamination with Tabular Data

Imbalanced Data Clustering via Targeted Data Augmentation Using GMM and LLM

Make Literature-Based Discovery Great Again through Reproducible Pipelines

Extracting information in a low-resource setting: case study on bioinformatics workflows

Vocabulary Quality in NLP Datasets: An Autoencoder-Based Framework Across Domains and Languages

Temporal and Streaming Data Expertise Prediction of Tetris Players Using Eye Tracking Information

Integrating Inverse and Forward Modeling for Sparse Temporal Data from Sensor Networks

Bridging Spatial and Temporal Contexts: Sparse Transfer Learning

Meta-learning and Data Augmentation for Stress Testing Forecasting Models

Pragmatic Paradigm for Multi-stream Regression

Two-in-one Models for Event Prediction and Time Series Forecasting. Comparison of Four Deep Learning Approaches to Simulate a Digital Patient under Anesthesia

An Analysis of Temporal Dropout in Earth Observation Time Series for Regression Tasks

Performative Drift Resistant Classification using Generative Domain Adversarial Networks

Explainable and Interpretable Data Science

Extracting Moore Machines from Transformers using Queries and Counterexamples

Obtaining Example-Based Explanations from Deep Neural Networks

Relevance-aware Algorithmic Recourse

Expanding Polynomial Kernels for Global and Local Explanations of Support Vector Machines

A Constrained Declarative Based Approach for Explainable Clustering.

Notes:

Description based on publisher supplied metadata and other sources.

ISBN:

3-031-91398-1

OCLC:

1524420579