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Big Data and Different Subspace Clustering Approaches: From social media promotion to genome mapping

By
Vijaya Kishore Veparala ,
Vijaya Kishore Veparala

Department of ECE, Mohan Babu University, Tirupati, A.P, India

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Vattikunta Kalpana ,
Vattikunta Kalpana

Department of ECE, Mohan Babu University, Tirupati, A.P, India

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Abstract

In the present age of information technology, information is the most important factor in determining how different paradigms will progress. This information needs to be mined out of a massive computer treasure trove. The rise in the amount of data been analyzed and interpreted is a direct result of the proliferation of more powerful processing platforms, the increase in the amount of storage space available, and the transition toward the use of electronic platforms. A thorough study of Big Data, its characteristics, and the role that Subspace clustering algorithm plays is described in this work. The most important contribution that this paper makes is that it reads a lot of previous research and then makes a thorough presentation about the different ways that other authors have classified subspace clustering methods. In addition, significant algorithms that are capable of acting as a benchmark for any future development have been provided with a short explanation.

How to Cite

1.
Kishore Veparala V, Kalpana V. Big Data and Different Subspace Clustering Approaches: From social media promotion to genome mapping. Salud, Ciencia y Tecnología [Internet]. 2023 Jun. 20 [cited 2024 Jun. 20];3:413. Available from: https://revista.saludcyt.ar/ojs/index.php/sct/article/view/413

The article is distributed under the Creative Commons Attribution 4.0 License. Unless otherwise stated, associated published material is distributed under the same licence.

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