ISBN13: | 9783031706288 |
ISBN10: | 3031706285 |
Kötéstípus: | Puhakötés |
Terjedelem: | 231 oldal |
Méret: | 235x155 mm |
Nyelv: | angol |
Illusztrációk: | 23 Illustrations, black & white; 69 Illustrations, color |
700 |
Advances in Databases and Information Systems
EUR 160.49
Kattintson ide a feliratkozáshoz
This volume LNCS 14918 constitutes the refereed proceedings of 28th European Conference, ADBIS 2024, held in Bayonne, France, during August 28-31, 2024.
The 15 full papers presented were carefully reviewed and selected from 43 submissions. The conference focuses on Algebra, Models, Schemata, Discovery and Data Analysis, Algorithms and Optimization, Access Methods and Query Processing, Advanced Architectures, Machine Learning, Large Language Models.
Algebra, Models, Schemata.- JSON Model a Lightweight Featureful DSL for JSON.- A Data Model and Predicate Logic for Trajectory Data.- Evaluating a Temporal Relational Algebra supporting Preferences in Temporal Relational Databases.- PG FD Mapping Functional Dependencies to the Future Property Graph Schema Standard.- Discovery and Data Analysis.- Generating SPARQL Queries for Data Discovery.- Algorithms and Optimization.- A Recursive Approach for Maximal (?,?) Clique Enumeration in Temporal Networks.- Influential Billboard Slot Selection under Zonal Influence Constraint.- Amethyst A Generalized on the fly De Recompression Framework to Accelerate Data intensive Integer Operations on GPUs.- Access Methods and Query Processing.- GXJoin Generalized Cell Transformations for Explainable Joinability.- Density Based Learned Spatial Index for Clustered Data.- Advanced Architectures.- Coordination Free Parallel and Replicated Datalog Streams.- On the fly Data Distribution to Accelerate Query Processing in Heterogeneous.- Enhancing Machine Learning Capabilities in Data Lakes with AutoML and LLMs.- Machine Learning.- BBQ Tree A Decision Tree with Boolean and Quantum Logic Decisions.- Large Language Models.- Using LLMs for the Extraction and Normalization of Product Attribute Values.