Federated Aggregated Micro Pipelines (FAMP) for Efficient Data Processing in MongoDB: A Case Study on Universities and Movie Dataset
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Publisher
Springer Nature Singapore
Link
https://link.springer.com/content/pdf/10.1007/978-981-99-8628-6_22
Reference6 articles.
1. Dataset available at: https://github.com/Bharani1802/datasets
2. Liang L, Zhu L, Shang W, Feng D, Xiao Z (2017) Express supervision system based on NodeJS and MongoDB. In: 2017 IEEE/ACIS 16th international conference on computer and information science (ICIS), Wuhan, China, pp 607–612. https://doi.org/10.1109/ICIS.2017.7960064
3. Zhao G, Huang W, Liang S, Tang Y (2013) Modeling MongoDB with relational model. In: 2013 fourth international conference on emerging intelligent data and web technologies. Xi’an, China, pp 115–121. https://doi.org/10.1109/EIDWT.2013.25
4. Gu Y, Wang X, Shen S, Wang J, Kim J-U (2015) Analysis of data storage mechanism in NoSQL database MongoDB. In: 2015 IEEE international conference on consumer electronics—Taiwan, Taipei, Taiwan, pp 70–71. https://doi.org/10.1109/ICCE-TW.2015.7217036
5. Anand V, Rao CM (2016) MongoDB and oracle NoSQL: a technical critique for design decisions. In: 2016 international conference on emerging trends in engineering, technology and science (ICETETS), Pudukkottai, India, pp 1–4. https://doi.org/10.1109/ICETETS.2016.7602984
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