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https://doi.org/10.1109/iscc.2...
Article . 2018 . Peer-reviewed
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Analysis of a NoSQL Graph DBMS for a Hospital Social Network

Authors: Celesti, Antonio; Buzachis, Alina; Galletta, Antonino; Fiumara, Giacomo; Fazio, Maria; Villari, Massimo;

Analysis of a NoSQL Graph DBMS for a Hospital Social Network

Abstract

Nowadays, the possibility of using social media in the healthcare domain is attracting the attention of many clinical professionals all around the world. In this panorama, many Healthcare Social Network (HSN) platforms are emerging with the purpose to enhance patient care and education. However, many clinical operators are reluctant to use them because they do not fulfil their requirements and are looking at the possibility to develop their own HSN platforms in order to perform social science studies. In this context, one of the major issue is the management of generated big data presenting a huge amount of relations and for this reason, traditional Relational Database management Systems (RDBMSs) are not adequate. The objective of this preliminary scientific work is to prove that a NoSQL graph DBMS can address such an issue, paving the way toward future social science studies. Experiments results show that Neo4j, i.e., one of the major NoSQL graph DBMS, simplifies the management of HSN data also guaranteeing acceptable performances in the perspective of future social science studies.

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Keywords

Healthcare, social network, Cloud computing,NoSQL, graph database

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selected citations
These citations are derived from selected sources.
This is an alternative to the "Influence" indicator, which also reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
BIP!Citations provided by BIP!
popularity
This indicator reflects the "current" impact/attention (the "hype") of an article in the research community at large, based on the underlying citation network.
BIP!Popularity provided by BIP!
influence
This indicator reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
BIP!Influence provided by BIP!
impulse
This indicator reflects the initial momentum of an article directly after its publication, based on the underlying citation network.
BIP!Impulse provided by BIP!
2
Average
Average
Average
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