Publications associées à NoSQL

Interactive-time Exploration, Querying, and Analysis of Large High-dimensional Datasets

In the current era of big data, aggregation queries on high-dimensional datasets are frequently utilized to uncover hidden patterns, trends, and correlations critical for effective business decision-making. Data cubes facilitate such queries by employing p ...

EPFL2023

Graph integration of structured, semistructured and unstructured data for data journalism

Angelos Christos Anadiotis, Jingmao You

Digital data is a gold mine for modern journalism. However, datasets which interest journalists are extremely heterogeneous, ranging from highly structured (relational databases), semi-structured (JSON, XML, HTML), graphs (e.g., RDF), and text. Journalists ...

PERGAMON-ELSEVIER SCIENCE LTD2022

Differentiated consistency for worldwide gossips

Davide Frey, Pierre-Louis Blaise Roman

Eventual consistency is a consistency model that favors liveness over safety. It is often used in large-scale distributed systems where models ensuring a stronger safety incur performance that are too low to be deemed practical. Eventual consistency tends ...

2022

High-dimensional Data Cubes

Christoph Koch, Sachin Basil John

This paper introduces an approach to supporting high-dimensional data cubes at interactive query speeds and moderate storage cost. The approach is based on binary(-domain) data cubes that are judiciously partially materialized; the missing information can ...

ASSOC COMPUTING MACHINERY2022

High-dimensional Data Cubes

Christoph Koch, Sachin Basil John

This paper introduces an approach to supporting high-dimensional data cubes at interactive query speeds and moderate storage cost. The approach is based on binary(-domain) data cubes that are judiciously partially materialized; the missing information can ...

2022

Propagation on Multi-relational Graphs for Node Regression

Eda Bayram

Recent years have witnessed a rise in real-world data captured with rich structural information that can be conveniently depicted by multi-relational graphs. While inference of continuous node features across a simple graph is rather under-studied by the c ...

Springer, Cham2022

Representation Learning for Multi-relational Data

Eda Bayram

Recent years have witnessed a rise in real-world data captured with rich structural information that can be better depicted by multi-relational or heterogeneous graphs. However, research on relational representation learning has so far mostly focused on th ...

EPFL2021

Scalable Multi-Query Execution using Reinforcement Learning

Anastasia Ailamaki, Panagiotis Sioulas

The growing demand for data-intensive decision support and the migration to multi-tenant infrastructures put databases under the stress of high analytical query load. The requirement for high throughput contradicts the traditional design of query-at-a-time ...

Association for Computing Machinery2021

AiiDA 1.0, a scalable computational infrastructure for automated reproducible workflows and data provenance

Nicola Marzari, Giovanni Pizzi, Nicolas Frank Mounet, Martin Uhrin, Andrea Cepellotti, Boris Kozinsky, Fernando Gargiulo, Christoph Leopold Talirz, Leonid Kahle, Aliaksandr Yakutovich

The ever-growing availability of computing power and the sustained development of advanced computational methods have contributed much to recent scientific progress. These developments present new challenges driven by the sheer amount of calculations and d ...

2020

Node Attribute Completion in Knowledge Graphs with Multi-Relational Propagation

Robert West, Eda Bayram, Alberto Garcia Duran

The existing literature on knowledge graph completion mostly focuses on the link prediction task. However, knowledge graphs have an additional incompleteness problem: their nodes possess numerical attributes, whose values are often missing. Our approach, d ...

2021