Advances in Intelligent Data Analysis XXI : 21st International Symposium on Intelligent Data Analysis, IDA 2023, Louvain-la-Neuve, Belgium, April 12–14, 2023, Proceedings / edited by Bruno Crémilleux, Sibylle Hess, Siegfried Nijssen.

Format:

Book

Contributor:

Crémilleux, Bruno, editor.

Hess, Sibylle, editor.

Nijssen, Siegfried, editor.

Series:

Lecture Notes in Computer Science, 1611-3349 ; 13876

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.

Computers and Education.

Computer Imaging, Vision, Pattern Recognition and Graphics.

Artificial Intelligence.

Machine Learning.

Natural Language Processing (NLP).

Local Subjects:

Database Management.

Computers and Education.

Computer Imaging, Vision, Pattern Recognition and Graphics.

Artificial Intelligence.

Machine Learning.

Natural Language Processing (NLP).

Physical Description:

1 online resource (514 pages)

Edition:

1st ed. 2023.

Place of Publication:

Cham : Springer Nature Switzerland : Imprint: Springer, 2023.

Summary:

This book constitutes the proceedings of the 21st International Symposium on Intelligent Data Analysis, IDA 2022, which was held in Louvain-la-Neuve, Belgium, during April 12-14, 2023. The 38 papers included in this book were carefully reviewed and selected from 91 submissions. IDA is an international symposium presenting advances in the intelligent analysis of data. Distinguishing characteristics of IDA are its focus on novel, inspiring ideas, its focus on research, and its relatively small scale. .

Contents:

Contextual Word Embeddings Clustering through Multiway Analysis: A Comparative Study

Transferable Deep Metric Learning for Clustering

Spatial Graph Convolution Neural Networks for Water Distribution Systems

Data-Centric Perspective on Explainability versus Performance Trade-off

Towards Data Science Design Patterns

Diverse Paraphrasing with Insertion Models for Few-Shot Intent Detection

LEMON: Alternative Sampling for More Faithful Explanation through Local Surrogate Models

GASTeN: Generative Adversarial Stress Test Networks

Learning Permutation-Invariant Embeddings for Description Logic Concepts

Diffusion Transport Alignment

Mind the Gap: Measuring Generalization Performance Across Multiple Objectives

Effects of Locality and Rule Language on Explanations for Knowledge Graph Embeddings

Shapley Values with Uncertain Value Functions. -Revised Conditional t-SNE: Looking Beyond the Nearest Neighbors

On the Change of Decision Boundary and Loss in Learning with Concept Drift

AID4HAI: Automatic Idea Detection for Healthcare-Associated Infections from Twitter, A Framework based on Active Learning and Transfer Learning

Explanations for Itemset Mining by Constraint Programming: A Case Study using ChEMBL data

Translated Texts Under the Lens: From Machine Translation Detection to Source Language Identification

Geolet: An Interpretable Model for Trajectory Classification

An investigation of structures responsible for gender bias in BERT and DistilBERT

Discovering diverse top-k characteristic lists

Online Influence Forest for Streaming Anomaly Detection

APs: a proxemic framework for social media interactions modeling and analysis

User Authentication via Multifaceted Mouse Movementsand Outlier Exposure

Explaining Black Box Reinforcement Learning Agents Through Counterfactual Policies

A GNN-based Architecture for Group Detection from spatio-temporal Trajectory Data

Discovering Rule Lists with Preferred Variables

Don’t Start Your Data Labeling from Scratch: OpSaLa - Optimized Data Sampling Before Labeling

The Other Side of Compression: Measuring Bias in Pruned Transformers

Dropping incomplete records is (not so) straightforward

Meta-Learning for Automated Selection of Anomaly Detectors for Semi-Supervised Datasets

Should We Consider On-Demand Analysis in Scale-Free Networks?

ROCKAD: Transferring ROCKET to whole time series anomaly detection

Out-of-Distribution Generalisation with Symmetry-Based Disentangled Representations

Forecasting Electricity Prices: an Optimize then Predict-based approach

A Similarity-Guided Framework for Error-Driven Discovery of Patient Neighbourhoods in EMA Data

QBERT: Generalist Model for Processing Questions

On Compositionality in Data Embedding.

Notes:

Includes bibliographical references and index.

Other Format:

Print version: Crémilleux, Bruno Advances in Intelligent Data Analysis XXI

ISBN:

9783031300479

OCLC:

1374878156