A Mini-Review of Machine Learning in Big Data Analytics: Applications, Challenges, and Prospects
The availability of digital technology in the hands of every citizenry worldwide makes an available unprecedented massive amount of data. The capability to process these gigantic amounts of data in real-time with Big Data Analytics (BDA) tools and Machine Learning (ML) algorithms carries many paybac...
| Main Authors: | , , , |
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| Format: | Article |
| Language: | English |
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Tsinghua University Press
2022-06-01
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| Series: | Big Data Mining and Analytics |
| Subjects: | |
| Online Access: | https://www.sciopen.com/article/10.26599/BDMA.2021.9020028 |
| _version_ | 1798029360148512768 |
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| author | Isaac Kofi Nti Juanita Ahia Quarcoo Justice Aning Godfred Kusi Fosu |
| author_facet | Isaac Kofi Nti Juanita Ahia Quarcoo Justice Aning Godfred Kusi Fosu |
| author_sort | Isaac Kofi Nti |
| collection | DOAJ |
| description | The availability of digital technology in the hands of every citizenry worldwide makes an available unprecedented massive amount of data. The capability to process these gigantic amounts of data in real-time with Big Data Analytics (BDA) tools and Machine Learning (ML) algorithms carries many paybacks. However, the high number of free BDA tools, platforms, and data mining tools makes it challenging to select the appropriate one for the right task. This paper presents a comprehensive mini-literature review of ML in BDA, using a keyword search; a total of 1512 published articles was identified. The articles were screened to 140 based on the study proposed novel taxonomy. The study outcome shows that deep neural networks (15%), support vector machines (15%), artificial neural networks (14%), decision trees (12%), and ensemble learning techniques (11%) are widely applied in BDA. The related applications fields, challenges, and most importantly the openings for future research, are detailed. |
| first_indexed | 2024-04-11T19:23:04Z |
| format | Article |
| id | doaj.art-4b9fe8fde590471f94185d9cf563c0b2 |
| institution | Directory Open Access Journal |
| issn | 2096-0654 |
| language | English |
| last_indexed | 2024-04-11T19:23:04Z |
| publishDate | 2022-06-01 |
| publisher | Tsinghua University Press |
| record_format | Article |
| series | Big Data Mining and Analytics |
| spelling | doaj.art-4b9fe8fde590471f94185d9cf563c0b22022-12-22T04:07:14ZengTsinghua University PressBig Data Mining and Analytics2096-06542022-06-0152819710.26599/BDMA.2021.9020028A Mini-Review of Machine Learning in Big Data Analytics: Applications, Challenges, and ProspectsIsaac Kofi Nti0Juanita Ahia Quarcoo1Justice Aning2Godfred Kusi Fosu3Department of Computer Science and Informatics, University of Energy and Natural Resources, Sunyani BS2103, GhanaDepartment of Electrical & Electronic Engineering, Sunyani Technical University, Sunyani BS2103, GhanaDepartment of Computer Science, Sunyani Technical University, Sunyani BS2103, GhanaDepartment of Computer Science, Sunyani Technical University, Sunyani BS2103, GhanaThe availability of digital technology in the hands of every citizenry worldwide makes an available unprecedented massive amount of data. The capability to process these gigantic amounts of data in real-time with Big Data Analytics (BDA) tools and Machine Learning (ML) algorithms carries many paybacks. However, the high number of free BDA tools, platforms, and data mining tools makes it challenging to select the appropriate one for the right task. This paper presents a comprehensive mini-literature review of ML in BDA, using a keyword search; a total of 1512 published articles was identified. The articles were screened to 140 based on the study proposed novel taxonomy. The study outcome shows that deep neural networks (15%), support vector machines (15%), artificial neural networks (14%), decision trees (12%), and ensemble learning techniques (11%) are widely applied in BDA. The related applications fields, challenges, and most importantly the openings for future research, are detailed.https://www.sciopen.com/article/10.26599/BDMA.2021.9020028big data analytics (bda)machine learning (ml)big data (bd)hadoopmapreduce |
| spellingShingle | Isaac Kofi Nti Juanita Ahia Quarcoo Justice Aning Godfred Kusi Fosu A Mini-Review of Machine Learning in Big Data Analytics: Applications, Challenges, and Prospects Big Data Mining and Analytics big data analytics (bda) machine learning (ml) big data (bd) hadoop mapreduce |
| title | A Mini-Review of Machine Learning in Big Data Analytics: Applications, Challenges, and Prospects |
| title_full | A Mini-Review of Machine Learning in Big Data Analytics: Applications, Challenges, and Prospects |
| title_fullStr | A Mini-Review of Machine Learning in Big Data Analytics: Applications, Challenges, and Prospects |
| title_full_unstemmed | A Mini-Review of Machine Learning in Big Data Analytics: Applications, Challenges, and Prospects |
| title_short | A Mini-Review of Machine Learning in Big Data Analytics: Applications, Challenges, and Prospects |
| title_sort | mini review of machine learning in big data analytics applications challenges and prospects |
| topic | big data analytics (bda) machine learning (ml) big data (bd) hadoop mapreduce |
| url | https://www.sciopen.com/article/10.26599/BDMA.2021.9020028 |
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