Analysis of Refined Big Data Clustering Algorithm using Power Method on Block Chain Network
DOI:
https://doi.org/10.54228/mjaret08220003Keywords:
Power Method, Clustering, Big Data, Block Chain, Inflation.Abstract
The need to redesign and convert the traditional clustering technique has paved a way to analyze and refine a new clustering algorithm that address the challenges like efficiency and scalability when dealing with Big Data. Clustering deanonmizes block chain data. It links various blocks that belongs to the same entity. It ensures secure transaction and reduces the cost. Also, it speeds up data processing. This paper aims in refining the clustering technique for block chain data that can process huge volumes of data using the Power Method. In addition, the block chain system helps to secure and interpret the information.
Downloads
Downloads
Published
Issue
Section
License
License Terms for MJARET
Creative Commons Attributio 4.0 International (CC BY) License:
This license allows for the following:
-
Sharing — Copy and redistribute the material in any medium or format.
-
Adaptation — Remix, transform, and build upon the material.
The license is subject to the following terms:
-
Attribution:
- You must give appropriate credit, provide a link to the license, and indicate if changes were made.
- Attribution should include the citation of the article, the author's name, and a link to the original work published in MJARET.
- This must be done in any reasonable manner, but not in any way that suggests the licensor endorses you or your use.
-
NonCommercial:
- The material cannot be used for commercial purposes.
- Any use of the work intended to provide a commercial advantage or monetary compensation is considered outside the scope of this license.
-
No Additional Restrictions:
- You may not apply legal terms or technological measures that legally restrict others from doing anything the license permits.
General Provisions:
- Understandability: This license can be revoked if you do not comply with its terms and conditions.
- Public Domain: Where the work or any of its elements is in the public domain under applicable law, that status is in no way affected by the license.
- Other Rights:
- The license does not cover rights such as publicity, privacy, or moral rights that may affect your ability to use the material as contemplated by the license.
- Such rights might need to be considered and respected separately.
Disclaimer:
- MJARET does not provide any warranties with the work. The work is provided "as is" without any representations or warranties, express or implied. MJARET will not be liable for any damages resulting from the use of the work.
How to Cite:
- Proper attribution for use of the licensed work should follow the standard citation format provided by MJARET, which should include the author(s), the title of the work, MJARET, and the DOI link.
