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it - Information Technology, 2016 The age of big data is now coming. But the traditional data analytics may not be able to handle such large quantities of data. The question that arises now is, how to develop a high performance platform to efficiently analyze big data and how to design ...
Tsai, Chun-Wei, +7 more
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Big Data and Big Data Analytics
2021Big data is emerging, and the latest developments in technology have spawned enormous amounts of data. The traditional databases lack the capabilities to handle this diverse data and thus has led to the employment of new technologies, methods, and tools. This research discusses big data, the available big data analytical tools, the need to use big data
Sam Goundar +4 more
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BIG DATA AND BIG DATA ANALYTICS
2023Big Data and Big Data Analytics are terms used to describe the enormous amount of information that is produced daily in our contemporary digital environment. The term "big data" refers to massive, complex data volumes that are very challenging to handle and manage successfully when using traditional data processing methods.
Jaishree Agrawal, Kapish Nautiyal
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Proceedings of the 21th ACM SIGKDD International Conference on Knowledge Discovery and Data Mining, 2015
As the scale and dimensionality of data continue to grow in many applications of data analytics (e.g., bioinformatics, finance, computer vision, medical informatics), it becomes critical to develop efficient and effective algorithms to solve numerous machine learning and data mining problems. This tutorial will focus on simple yet practically effective
Tianbao Yang, Qihang Lin, Rong Jin 0001
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As the scale and dimensionality of data continue to grow in many applications of data analytics (e.g., bioinformatics, finance, computer vision, medical informatics), it becomes critical to develop efficient and effective algorithms to solve numerous machine learning and data mining problems. This tutorial will focus on simple yet practically effective
Tianbao Yang, Qihang Lin, Rong Jin 0001
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2015 IEEE International Conference on Computer and Information Technology; Ubiquitous Computing and Communications; Dependable, Autonomic and Secure Computing; Pervasive Intelligence and Computing, 2015
Large amounts of heterogeneous education data have emerged in MOOC, which are provided by various educational organizations and universities. In this paper, we present an overview of state-of-art research framework and techniques used in the field of analytics over education big data. Finally, the conclusion is given.
Yanyan Zheng, Beibei Yin
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Large amounts of heterogeneous education data have emerged in MOOC, which are provided by various educational organizations and universities. In this paper, we present an overview of state-of-art research framework and techniques used in the field of analytics over education big data. Finally, the conclusion is given.
Yanyan Zheng, Beibei Yin
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Journal of Parallel and Distributed Computing, 2014
Abstract One of the major applications of future generation parallel and distributed systems is in big-data analytics. Data repositories for such applications currently exceed exabytes and are rapidly increasing in size. Beyond their sheer magnitude, these datasets and associated applications’ considerations pose significant challenges for method and
Karthik Kambatla +3 more
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Abstract One of the major applications of future generation parallel and distributed systems is in big-data analytics. Data repositories for such applications currently exceed exabytes and are rapidly increasing in size. Beyond their sheer magnitude, these datasets and associated applications’ considerations pose significant challenges for method and
Karthik Kambatla +3 more
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Big data analytics and investment
Technological Forecasting and Social Change, 2023Big data has found extensive applications in various industries, including finance. It is an essential tool for investors to make high-stakes investment decisions. Using China's A-shares Market, this paper employs 76 firm characteristics to conduct descriptive analytics (factor model) and predictive analytics (long\textendashshort portfolio) through an
Boubaker, S., Liu, Z., Mu, Y.
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Big data analytics for healthcare
Proceedings of the 19th ACM SIGKDD international conference on Knowledge discovery and data mining, 2013Large amounts of heterogeneous medical data have become available in various healthcare organizations (payers, providers, pharmaceuticals). Those data could be an enabling resource for deriving insights for improving care delivery and reducing waste.
Jimeng Sun 0001, Chandan K. Reddy
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Big data analytics for sustainability
Future Generation Computer Systems, 2018Abstract Sustainability is a paradigm for thinking about the future in which environmental, societal and economic considerations are equitable in the pursuit of an improved lifestyle. Most of the economies are developing with breakneck velocities and are becoming epicenters of unsustainable global growth.
Zhihan Lv +2 more
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International Journal of Cognitive Informatics and Natural Intelligence, 2017
Big data are pervasively generated by human cognitive processes, formal inferences, and system quantifications. This paper presents the cognitive foundations of big data systems towards big data science. The key perceptual model of big data systems is the recursively typed hyperstructure (RTHS).
Yingxu Wang 0001, Jun Peng 0008
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Big data are pervasively generated by human cognitive processes, formal inferences, and system quantifications. This paper presents the cognitive foundations of big data systems towards big data science. The key perceptual model of big data systems is the recursively typed hyperstructure (RTHS).
Yingxu Wang 0001, Jun Peng 0008
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