Big data stream analysis: a systematic literature review
Recently, big data streams have become ubiquitous due to the fact that a number of
applications generate a huge amount of data at a great velocity. This made it difficult for …
applications generate a huge amount of data at a great velocity. This made it difficult for …
Data stream analysis: Foundations, major tasks and tools
The significant growth of interconnected Internet‐of‐Things (IoT) devices, the use of social
networks, along with the evolution of technology in different domains, lead to a rise in the …
networks, along with the evolution of technology in different domains, lead to a rise in the …
Time series big data: a survey on data stream frameworks, analysis and algorithms
Big data has a substantial role nowadays, and its importance has significantly increased
over the last decade. Big data's biggest advantages are providing knowledge, supporting …
over the last decade. Big data's biggest advantages are providing knowledge, supporting …
Anomalies detection using isolation in concept-drifting data streams
MU Togbe, Y Chabchoub, A Boly, M Barry, R Chiky… - Computers, 2021 - mdpi.com
Detecting anomalies in streaming data is an important issue for many application domains,
such as cybersecurity, natural disasters, or bank frauds. Different approaches have been …
such as cybersecurity, natural disasters, or bank frauds. Different approaches have been …
A comparative analysis of big data frameworks: An adoption perspective
The emergence of social media, the worldwide web, electronic transactions, and next-
generation sequencing not only opens new horizons of opportunities but also leads to the …
generation sequencing not only opens new horizons of opportunities but also leads to the …
Review of big data and processing frameworks for disaster response applications
Natural hazards result in devastating losses in human life, environmental assets and
personal, and regional and national economies. The availability of different big data such as …
personal, and regional and national economies. The availability of different big data such as …
A hybrid support vector machine algorithm for big data heterogeneity using machine learning
Big data technology has gained attention in all fields, particularly with regard to research
and financial institutions. This technology has changed the world tremendously …
and financial institutions. This technology has changed the world tremendously …
[PDF][PDF] Big data streaming platforms: A review
H Kumar, MA Ismail - Iraqi Journal for Computer Science and Mathematics, 2022 - iasj.net
Yesterday's “Big Data” is today's “data.” As technology advances, new difficulties and new
solutions emerge. In recent years, as a result of the development of Internet of Things (IoT) …
solutions emerge. In recent years, as a result of the development of Internet of Things (IoT) …
A comprehensive study and review of tuning the performance on database scalability in big data analytics
MR Sundarakumar, G Mahadevan… - Journal of Intelligent …, 2023 - content.iospress.com
In the modern era, digital data processing with a huge volume of data from the repository is
challenging due to various data formats and the extraction techniques available. The …
challenging due to various data formats and the extraction techniques available. The …
A distributed stream processing middleware framework for real-time analysis of heterogeneous data on big data platform: Case of environmental monitoring
In recent years, the application and wide adoption of Internet of Things (IoT)-based
technologies have increased the proliferation of monitoring systems, which has …
technologies have increased the proliferation of monitoring systems, which has …