Overview

This book constitutes short papers, Doctoral Consortium and Workshops papers which were held in conjunction with the 28th European Conference on New Trends in Databases and Information Systems, ADBIS 2024, which took place in Bayonne, France, during August 28–31, 2024. The total of 28 full papers and 7 short papers presented in this book were carefully reviewed and selected from 103 submissions. They were organized in the following topical sections:  Doctoral Consortium; 5th Workshop on Intelligent Data - From Data to Knowledge (DOING 2024); 3rd Workshop on Knowledge Graphs Analysis on a Large Scale (K-GALS 2024); 6th Workshop on Modern Approaches in Data Engineering and Information System Design (MADEISD 2024); 3rd Workshop on Personalization and Recommender Systems (PERS 2024); Access methods and query processing; discovery and data analysis; Machine Learning; large language models; and tutorials. 

Full Product Details

Author:   Joe Tekli ,  Johann Gamper ,  Richard Chbeir ,  Yannis Manolopoulos
Publisher:   Springer International Publishing AG
Imprint:   Springer International Publishing AG
Edition:   2024 ed.
Volume:   2186
ISBN:  

9783031704208

ISBN 10:   3031704207
Pages:   402
Publication Date:   17 November 2024
Audience:   Professional and scholarly ,  Professional & Vocational
Format:   Paperback
Publisher's Status:   Active
Availability:   Manufactured on demand  
We will order this item for you from a manufactured on demand supplier.

Table of Contents

.- Doctoral Consortium. .- Using Graph Theory for Clinical Data Management. .- Advancing Legal NLP: Application of Pre-trained Language Models in the Legal Domain. .- An application for scoliosis screening and follow-up: a first proposal. .- Negation Detection in Italian: A Key Challenge in Sentiment Analysis. .- Optimizing Federated Learning and Increasing Efficiency. .- Integrating Pseudo-Time Series Analysis into Telemedicine: Enhancing Real-Time Disease Monitoring and Intervention. .- Classifying Chest X-Ray Images with Deep Learning Techniques: Challenges and Explainable Analysis. .- Scalable Deep Learning: Applications in Medicine. .- Towards More Efficient and Improved Federated Learning. .- Development of Explainable AI Methods for the Interpretation of Machine Learning Models in Bioinformatics and Medicine. .- Deep Learning Techniques for Predicting Wildires in Calabria Italy Using Environmental Parameters. .- 5th Workshop on Intelligent Data - From Data to Knowledge (DOING 2024). .- Capturing Analytical Intents from Text. .- The Effect of Text Normalization on Mining Portuguese Man-of-War Instagram Posts. .- A Preliminary Investigation: Strategies for Incorporating Logical Rules into Knowledge Graph Embeddings. .- Construction of Open Data Sources for Data Interoperability in Brazilian Health Information Systems. .- Brazilian Political Study with Topics Analysis and Complex Networks. .- 3rd Workshop on Knowledge Graphs Analysis on a Large Scale (K-GALS 2024). .- Transforming Text into Knowledge with Graphs: Report of the GDR MADICS DOING Action. .- Building Model-Driven Knowledge Graphs via Large Language Models. .- 6th Workshop on Modern Approaches in Data Engineering and Information System Design (MADEISD 2024). .- Process Mining in Croatia’s Judicial Auctions. .- Towards the Utilization of AI-powered Assistance for Systematic Literature Review. .- Estimating Information Efficiency of Bitcoin Inscriptions. .- Deep Learning-Based Cellular Nuclei Segmentation Using Transformer Mode. .- Towards a Model-Driven Approach to Enable Uniform Access to Vector Databases. .- Employing Multiple Online Translation Services in a Multilingual Database Design Tool. .- 3rd Workshop on Personalization and Recommender Systems (PERS 2024). .- Development of Collaborative Business Intelligence Framework for Tourism Analysis. .- Session-based Recommendation with Graph Neural Networks with an Examination of the Impact of Local and Global Vectors. .- Senselife: Service Recommendation and Frailty Prevention through Knowledge Models. .- Evaluating Diversity in Sequential Group Recommendations. .- Access methods and Query Processing. .- A Reproducibility Study of Subgroup Discovery Algorithms (short). .- Discovery and Data Analysis. .- A Compact and Efficient Data Structure for Line-based Processing of Series of Raster Data (short). .- Machine Learning. .- FedeM: Federated Learning-Based Privacy-Preserving Record Matching (short). .- Estimating MPdist with SAX and Machine Learning (short). .- Large Language Models. .- Entity Matching with Large Language Models as Weak and Strong labellers (short). .- LLMClean: Context-Aware Tabular Data Cleaning via LLM-Generated OFDs (short). .- Tutorials. .- Data-driven Analysis for Monitoring Software Evolution. .- On Customer Data Deduplication - Research vs. Industrial Perspective: Lessons Learned from a R&D Project in the Financial Sector.

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