Titlebook: Advances in Databases and Information Systems; 28th European Confer Joe Tekli,Johann Gamper,Yannis Manolopoulos Conference proceedings 2024

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书目名称Advances in Databases and Information Systems影响因子(影响力)




书目名称Advances in Databases and Information Systems影响因子(影响力)学科排名




书目名称Advances in Databases and Information Systems网络公开度




书目名称Advances in Databases and Information Systems网络公开度学科排名




书目名称Advances in Databases and Information Systems被引频次




书目名称Advances in Databases and Information Systems被引频次学科排名




书目名称Advances in Databases and Information Systems年度引用




书目名称Advances in Databases and Information Systems年度引用学科排名




书目名称Advances in Databases and Information Systems读者反馈




书目名称Advances in Databases and Information Systems读者反馈学科排名

DEFER

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Evaluating a Temporal Relational Algebra Supporting Preferences in Temporal Relational Databases faced yet. In several tasks and applications (e.g., planning, scheduling, workflows, guidelines), the exact time of occurrence of facts is not known (i.e., time is .), and preferences can be assigned to the different temporal possibilities. In a recent paper, we have laid the theoretical basis of t

精密

PG-FD: Mapping Functional Dependencies to the Future Property Graph Schema Standard to the role SQL plays in relational data querying. Although this goal is still a work in progress, the graph database community has been advancing by not only defining the GQL specification but also introducing additional specifications such as Property Graph Key, PG-Key, and later Property Graph S

follicle

Generating SPARQL Queries for Data Discovery the data for a specific need is time-consuming. This paper presents an approach that identifies and extracts the relevant portion of RDF data sources for some application requirements described by a target schema. The identification process is based on a semi-supervised learning algorithm that iter

BROOK

A Recursive Approach for Maximal (,)-Clique Enumeration in Temporal Networks, social networks, human contact networks, financial transaction networks, etc.) are time-varying in nature, i.e., the relationship changes over time. Such networks are often modeled as Temporal Networks. In this paper, we study the problem of enumerating cohesive substructures present in a given te

Ordeal

ALLEY

Amethyst - A Generalized on-the-Fly De/Re-compression Framework to Accelerate Data-Intensive Integernal function on every (un)compressed input format and to output the result in an arbitrary (un)compressed format. Thus, our on-the-fly de/re-compression framework approach automatically conducts a decompression on the input side and compression on the output side. To show the feasibility and applica

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武器