Innovative Technique for Classification of Web Service Quality through Machine Learning

Nagesh C., Bhavana Y., Ayesha K., Govardhini Gowd G., Jaswanth Reddy M.

2025

Abstract

Web services have become a cornerstone of modern distributed systems, enabling seamless communication and interoperability. Traditional methods for classifying web services using Quality-of-Service (QoS) attributes often face challenges in effectively managing dynamic and unlabeled data. To address this challenge, this research introduces a machine learning-based framework for web service analysis and classification, incorporating clustering techniques alongside supervised models such as Logistic Regression, SVM, KNN, and GNB. The system processes QoS metrics like response time, availability, and reliability to classify services into predefined quality classes. By integrating pseudo-labeled data through clustering, the framework significantly improves classification accuracy and scalability. This approach offers a robust and adaptive solution for efficient web service quality assessment, addressing the evolving needs of real-world applications.

Paper Citation

in Harvard Style

C. N., Y. B., K. A., G. G. and M. J. (2025). Innovative Technique for Classification of Web Service Quality through Machine Learning. In Proceedings of the 1st International Conference on Research and Development in Information, Communication, and Computing Technologies - ICRDICCT`25; ISBN 978-989-758-777-1, SciTePress, pages 830-835. DOI: 10.5220/0013906500004919

in Bibtex Style

@conference{icrdicct`2525,
author={Nagesh C. and Bhavana Y. and Ayesha K. and Govardhini G. and Jaswanth M.},
title={Innovative Technique for Classification of Web Service Quality through Machine Learning},
booktitle={Proceedings of the 1st International Conference on Research and Development in Information, Communication, and Computing Technologies - ICRDICCT`25},
year={2025},
pages={830-835},
publisher={SciTePress},
organization={INSTICC},
doi={10.5220/0013906500004919},
isbn={978-989-758-777-1},
}

in EndNote Style

TY - CONF

JO - Proceedings of the 1st International Conference on Research and Development in Information, Communication, and Computing Technologies - ICRDICCT`25
TI - Innovative Technique for Classification of Web Service Quality through Machine Learning
SN - 978-989-758-777-1
AU - C. N.
AU - Y. B.
AU - K. A.
AU - G. G.
AU - M. J.
PY - 2025
SP - 830
EP - 835
DO - 10.5220/0013906500004919
PB - SciTePress