| Autor: |
Kaur, Puneet, Chaudhary, Deepika, Molla, K. Z., Singh, Jaiteg |
| Předmět: |
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| Zdroj: |
AIP Conference Proceedings; 2022, Vol. 2357 Issue 1, p1-7, 7p |
| Abstrakt: |
Data science is emerging as a novel domain in the area of not only computers but also medical, agriculture, machine learning, social networking, and health care. As the data increases every second, the success of any real-world data analytical application majorly depends on the type and efficiency of its storage and management system. In these applications where there is difficulty in organizing the data in structured form materializes the role of Graph databases. Graph databases are well-organized to manage and store the data in the real world. Often, the graph databases have the capability of representing trillions of relationships which exist in any of the web or social networking dataset. The world is suffering from COVID-19 pandemic. Many researchers are working on post lockdown strategies that will control the spread of the coronavirus as well as unlock some of our freedoms. This situation is quite tricky, but data science as technology can probably provide a solution. One of the major objectives of this paper is that how graph database like Neo4j can help us information of policies which leads to achieve social isolation and to provide a solution for contact tracing problems which is a hurdle to social isolation [18]. [ABSTRACT FROM AUTHOR] |
| Databáze: |
Complementary Index |
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