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https://gnanaganga.inflibnet.ac.in:8443/jspui/handle/123456789/1361
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DC Field | Value | Language |
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dc.contributor.author | M, Senbagavalli | - |
dc.contributor.author | K, Vinodha | - |
dc.date.accessioned | 2023-09-27T07:20:37Z | - |
dc.date.available | 2023-09-27T07:20:37Z | - |
dc.date.issued | 2020-01-10 | - |
dc.identifier.uri | 10.35291/2454-9150.2020.0036 | - |
dc.identifier.uri | http://gnanaganga.inflibnet.ac.in:8080/jspui/handle/123456789/1361 | - |
dc.description.abstract | Research and assessment by other companies and researchers is insufficient or ineffective in selecting the best provider of cloud to implement. We were therefore determined to expand our studies to include a solid, costeffective implementation solution for all significant cloud platform providers. The manual process of collecting raw data from various social media platforms and SEO tools is a very tedious process and requires many skilled forces to complete it successfully. Yet it might contain lots of human errors which are common. Thus, to save time and money, we proposed an Architecture which required to work on data mining and validation tools to perform web scraping and reviewing of data, which yielded results within a short period of time. | en_US |
dc.language.iso | en | en_US |
dc.publisher | IJREAM | en_US |
dc.subject | Cloud Computing | en_US |
dc.subject | Visualization | en_US |
dc.subject | Mining | en_US |
dc.subject | Amazon Web Services | en_US |
dc.title | Visualization of Enterprise Grade Cloud Architecture for the Most Cost-Effective Application Deployment using Mining Tool | en_US |
dc.type | Article | en_US |
Appears in Collections: | Journal Articles |
Files in This Item:
File | Description | Size | Format | |
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IJREAMV05I1058063.pdf Restricted Access | 772.24 kB | Adobe PDF | View/Open Request a copy |
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