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Statistics report
Apr. 2024
Submitted Papers : 80
Accepted Papers : 10
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Acc. Perc : 12%
Issue Published : 133
Paper Published : 1552
No. of Authors : 4025
  Journal Paper


Paper Title :
Swarming Network Geno-Generative Model for Enhanced Top-K Query Processing In a Distributed Database

Author :Okorie Darlington Nnamdi, Amadi Uchechukwu

Article Citation :Okorie Darlington Nnamdi ,Amadi Uchechukwu , (2022 ) " Swarming Network Geno-Generative Model for Enhanced Top-K Query Processing In a Distributed Database " , International Journal of Advance Computational Engineering and Networking (IJACEN) , pp. 51-54, Volume-10,Issue-12

Abstract : The aim of this study was to develop an Intelligent Swarming Network (ISWAN) Geno-Generative Model for an enhanced Top-k query processing in a distributed database system. The study adopted the object-oriented analysis and design. This includes strategies and techniques employed in the synthesis of a software arte fact. The study presented an improved approach to query processing through the application of an ISWAN Generative model and Mongo Db. The improved approach depicts evolutionary learning techniques for query processing which is also a type of machine learning algorithm used to draw inferences from datasets consisting of input data without labeled responses. It was recommended that database administrators and analysts in real industrial environments, software developers and researchers should show keen interest in the study area. Keywords - Optimized Generative Model, Intelligent Networks, Database Management Systems, Query, Object-Oriented System

Type : Research paper

Published : Volume-10,Issue-12


DOIONLINE NO - IJACEN-IRAJ-DOIONLINE-19452   View Here

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