Akan Verinin Makine Öğrenme Algoritmaları Kullanılarak Ölçeklenmesi
Öz
Anahtar Kelimeler
Kaynakça
- Nittel S., 2015, Real-time Sensor Data Streams, Sigspatial Special, 7(2).
- Kolajo T., Daramola O. and Adebiyi A., 2019, Big Data Stream Analysis: A Systematic Literature Review, Journal of Big Data, 6(1), pp. 47.
- Krishnaswamy S., Gaber M. M. and Zaslavsky A., 2005, Mining Dat Streams: A Review, ACM Sigmod Record, 34(2), pp. 18-26.
- Jing G., Clay W., Jiawei K., Nikunj C., Mohamad M., Latifur K. and Kevin W, 2011, Facing the Reality of Data Stream Classification: Coping with Scarcity of Labeled Data, Knowledge and Information Systems, 33, pp. 213-214.
- Bifet A., Holmes G., Kirkby R. and Pfahringer B., 2011, Data Stream Mining a Practical Approach, https://moa.cms.waikato.ac.nz/downloads/, [Ziyaret tarihi: 15 Kasım 2020].
- Lindburg K., Stern R., Buddhika T., Pallicara S. and Ericson K., 2017, Online Scheduling and Interface Alleviation for Low-Latency, High-Troughput Processing of Data Streams, IEEE Transactions on Parallel and Distributed Systems, 28(12), pp. 3553-3569.
- Meng X., Wang C., Guo Q., Weng Z. and Yang C., 2017, Automating Characterization Deployment in Distributed Data Stream Management Systems, IEEE Transactions on Knowledge and Data Engineering, 29(12), pp. 2669 - 2681.
- Liu X. and Buyya R., 2019, Performance-oriented deployment of streaming applications on cloud, IEEE Tr. on Big Data, 5(1), pp. 46-59.
Ayrıntılar
Birincil Dil
Türkçe
Konular
Mühendislik
Bölüm
Araştırma Makalesi
Yayımlanma Tarihi
27 Haziran 2022
Gönderilme Tarihi
30 Aralık 2021
Kabul Tarihi
25 Mart 2022
Yayımlandığı Sayı
Yıl 2022 Cilt: 15 Sayı: 1
