Advancing Disability Management in Information Systems: A Novel Approach through Bidirectional Federated Learning-Based Gradient Optimization
Surbhi Bhatia Khan (),
Mohammed Alojail and
Moteeb Al Moteri
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Surbhi Bhatia Khan: Department of Data Science, School of Science, Engineering and Environment, University of Salford, Manchester M5 4WT, UK
Mohammed Alojail: Department of Management Information Systems, College of Business Administration, King Saud University, P.O. Box 28095, Riyadh 11437, Saudi Arabia
Moteeb Al Moteri: Department of Management Information Systems, College of Business Administration, King Saud University, P.O. Box 28095, Riyadh 11437, Saudi Arabia
Mathematics, 2023, vol. 12, issue 1, 1-20
Abstract:
Disability management in information systems refers to the process of ensuring that digital technologies and applications are designed to be accessible and usable by individuals with disabilities. Traditional methods face several challenges such as privacy concerns, high cost, and accessibility issues. To overcome these issues, this paper proposed a novel method named bidirectional federated learning-based Gradient Optimization (BFL-GO) for disability management in information systems. In this study, bidirectional long short-term memory (Bi-LSTM) was utilized to capture sequential disability data, and federated learning was employed to enable training in the BFL-GO method. Also, gradient-based optimization was used to adjust the proposed BFL-GO method’s parameters during the process of hyperparameter tuning. In this work, the experiments were conducted on the Disability Statistics United States 2018 dataset. The performance evaluation of the BFL-GO method involves analyzing its effectiveness based on evaluation metrics, namely, specificity, F1-score, recall, precision, AUC-ROC, computational time, and accuracy and comparing its performance against existing methods to assess its effectiveness. The experimental results illustrate the effectiveness of the BFL-GO method for disability management in information systems.
Keywords: disability management; information systems; federated learning; bidirectional long short-term memory; gradient-based optimization (search for similar items in EconPapers)
JEL-codes: C (search for similar items in EconPapers)
Date: 2023
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Persistent link: https://EconPapers.repec.org/RePEc:gam:jmathe:v:12:y:2023:i:1:p:119-:d:1310127
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