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RETRACTED: Intelligent personal assistant for personal computers using long short-term memory-based verbalizer

Iwin Thanakumar Joseph Swamidason (Department of Computer Science and Engineering, Koneru Lakshmaiah Education Foundation, Guntur, India)
Sravanthy Tatiparthi (Vaagdevi Engineering College, Warangal, India)
Karunakaran Velswamy (Department of Computer Science and Engineering (AI and ML and Cybersecurity), Jain University, Bangalore, India)
S. Velliangiri (Department of Computational Intelligence, SRM Institute of Science and Technology, Kattankulathur Campus, Chennai, India)

International Journal of Intelligent Unmanned Systems

ISSN: 2049-6427

Article publication date: 5 July 2022

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This article was retracted on 26 Oct 2023.

Retraction notice

The publishers of the International Journal of Intelligent Unmanned Systems wish to retract the Swamidason, I.T.J., Tatiparthi, S., Velswamy, K. and Velliangiri, S. (2022), “Intelligent personal assistant for personal computers using long short-term memory-based verbalizer”, International Journal of Intelligent Unmanned Systems, Vol. ahead-of-print No. ahead-of-print. https://doi.org/10.1108/IJIUS-02-2022-0012

An internal investigation into a series of submissions has uncovered evidence that the peer review process was compromised. As a result of these concerns, the findings of the article cannot be relied upon. This decision has been taken in accordance with Emerald’s publishing ethics and the COPE guidelines on retractions. Despite numerous attempts to contact the authors, the journal has received no response; the response of the authors would be gratefully received.

The publishers of the journal sincerely apologize to the readers.

Abstract

Purpose

An intelligent personal assistant for personal computers (PCs) is a vital application for the current generation. The current computer personal assistant services checking frameworks are not proficient at removing significant data from PCs and long-range informal communication information.

Design/methodology/approach

The proposed verbalizers use long short-term memory to classify the user task and give proper guidelines to the users. The outcomes show that the proposed method determinedly handles heterogeneous information and improves precision. The main advantage of long short-term memory is that handle the long-term dependencies in the input data.

Findings

The proposed model gives the 22% mean absolute error. The proposed method reduces mean square error than support vector machine (SVM), convolutional neural network (CNN), multilayer perceptron (MLP) and K-nearest neighbors (KNN).

Originality/value

This paper fulfills the necessity of intelligent personal assistant for PCs using verbalizer.

Keywords

Citation

Swamidason, I.T.J., Tatiparthi, S., Velswamy, K. and Velliangiri, S. (2022), "RETRACTED: Intelligent personal assistant for personal computers using long short-term memory-based verbalizer", International Journal of Intelligent Unmanned Systems, Vol. ahead-of-print No. ahead-of-print. https://doi.org/10.1108/IJIUS-02-2022-0012

Publisher

:

Emerald Publishing Limited

Copyright © 2022, Emerald Publishing Limited

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