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  Published Paper Details:

  Paper Title

Developing a Framework for Utilizing AI for Data Access Optimization

  Authors

  Venkatakrishna Valleru

  Keywords

Data, Artificial Intelligence, Optimization, Accuracy, Mining

  Abstract


The use of artificial intelligence for data access optimization is becoming increasingly important in the field of data science. AI algorithms can be used to create complex data structures that can be used to facilitate faster and more efficient access to data. Additionally, AI can be used to create frameworks capable of handling large amounts of data and optimizing the speed and accuracy of query results. This paper presents a framework for utilizing AI for data access optimization. In this framework, AI algorithms are used to create a structure for data storage and user interfaces that allow users to interact with the data more efficiently. Data mining techniques are used to identify patterns in the data that can be used to generate optimized queries. Additionally, the framework includes tools and libraries to automate processes and enable easy implementation of the developed framework. The proposed framework has been evaluated using a case study, and results show that the AI-based query optimization proposed in this framework can significantly reduce the query result time compared to traditional methods

  IJCRT's Publication Details

  Unique Identification Number - IJCRT24A4907

  Paper ID - 258627

  Page Number(s) - q563-q571

  Pubished in - Volume 12 | Issue 4 | April 2024

  DOI (Digital Object Identifier) -   

  Publisher Name - IJCRT | www.ijcrt.org | ISSN : 2320-2882

  E-ISSN Number - 2320-2882

  Cite this article

  Venkatakrishna Valleru,   "Developing a Framework for Utilizing AI for Data Access Optimization", International Journal of Creative Research Thoughts (IJCRT), ISSN:2320-2882, Volume.12, Issue 4, pp.q563-q571, April 2024, Available at :http://www.ijcrt.org/papers/IJCRT24A4907.pdf

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ISSN: 2320-2882
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Journal Starting Year (ESTD) : 2013
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ISSN and 7.97 Impact Factor Details


ISSN
ISSN
ISSN: 2320-2882
Impact Factor: 7.97 and ISSN APPROVED
Journal Starting Year (ESTD) : 2013
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