JointConf: Jointly autotuning configuration parameters for modularized graph databases
Sign Up to like & getrecommendations! Published in 2022 at "Journal of Software: Evolution and Process"
DOI: 10.1002/smr.2495
Abstract: To support different application scenarios, graph databases (GDBs) usually provide a large number of performance‐related parameters for developers. Since manually configuring is both time‐consuming and cost‐intensive, automatically tuning configurations parameters to achieve a better performance… read more here.
Keywords: jointly autotuning; graph databases; graph; configuration parameters ... See more keywords
Enhancing Investigative Pattern Detection via Inexact Matching and Graph Databases
Sign Up to like & getrecommendations! Published in 2022 at "IEEE Transactions on Services Computing"
DOI: 10.1109/tsc.2021.3073145
Abstract: Tracking individuals or groups based on their hidden and/or emergent behaviors is an indispensable task in homeland security, mental health evaluation, and consumer analytics. On-line and off-line communication patterns, behavior profiles and social relationships form… read more here.
Keywords: investigative pattern; pattern detection; graph databases; enhancing investigative ... See more keywords
Implementation of a Terminology Server with SNOMED CT in Graph Databases
Sign Up to like & getrecommendations! Published in 2019 at "Studies in health technology and informatics"
DOI: 10.3233/shti190546
Abstract: This paper described the implementation of a terminology server performed at a health institution in Uruguay, whose architecture is based on SNOMED CT using graph databases (NoSQL). The aim of this development was to create… read more here.
Keywords: implementation terminology; server snomed; graph databases; terminology server ... See more keywords
Experimental Evaluation of Graph Databases: JanusGraph, Nebula Graph, Neo4j, and TigerGraph
Sign Up to like & getrecommendations! Published in 2023 at "Applied Sciences"
DOI: 10.3390/app13095770
Abstract: NoSQL databases were created with the primary goal of addressing the shortcomings in the efficiency of relational databases, and can be of four types: document, column, key-value, and graph databases. Graph databases can store data… read more here.
Keywords: databases janusgraph; graph databases; experimental evaluation; graph ... See more keywords