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  • 标题:Performance Analysis of Recurrent Neural Network and Fuzzy Logic Algorithms in Cloud Information Retrieval System
  • 本地全文:下载
  • 作者:Manimegalai.M ; K.Sebasthirani ; Padmavathi.H
  • 期刊名称:International Journal of Early Childhood Special Education
  • 电子版ISSN:1308-5581
  • 出版年度:2022
  • 卷号:14
  • 期号:4
  • 页码:764-771
  • DOI:10.9756/INT-JECSE/V14I4.97
  • 语种:English
  • 出版社:International Journal of Early Childhood Special Education
  • 摘要:The rapid progress of cloud technology has brought a innovative bent to information services. Information retrieval is an essential part of cloud computing, as it allows to store and retrieve information from the cloud to your environment. Technology and resource availability are compelling a dramatic variation in the information management organization in the next few years. With its web-based information management system, technology has commenced to do with conventionally-based information management methods. Information management doesn't merely mean storing data, however collectively handling unstructured and structured info on an oversized scale. These systems involve not only large-scale storage, but also management of both unstructured and structured data. Search-engines and web-services could benefit from data retrieval systems. Therefore, information retrieval systems should be established as sophisticated applications. The proposed work will apply a Recurrent Neural Network to train the machine to retrieve information from a cloud server. A recurrent neural network was then used in order to achieve an accuracy of over 95%.
  • 关键词:Recurrent Neural Network (RNN);Cloud Computing;Firebase Cloud Storage;Information Retrieval;Fuzzy Logic;Deep Learning
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