Optimizing Dynamic Multi-Agent Performance in E-Learning Environment

D. K. Aarthi, E. J. Fredrik

2023

Abstract

The instructor-centric paradigm has been displaced as the most cutting-edge method of learning with the introduction of web-based learning and content management systems.For e-learning systems, web mining is extremely essential. The user can alter the learning setting in a personalized E-Learning system according to their preferences. A link that receives the most hits will be displayed first in a general search procedure. To construct a customizable system, user logs must be used to store each user’s historical information. The proposed approach provides a novel viewpoint by combining web usage mining, the HIT algorithm, and web content mining. It combines user logs and web page hit statistics and contains data that has been clustered using the Lingo clustering method. We will discuss a method in this article that makes use of content mining and web usage to personalized e-Learning services. The usefulness and advantages of web mining for e-learning are examined in this essay.

Paper Citation

in Harvard Style

Aarthi D. and Fredrik E. (2023). Optimizing Dynamic Multi-Agent Performance in E-Learning Environment. In Proceedings of the 1st International Conference on Artificial Intelligence for Internet of Things: Accelerating Innovation in Industry and Consumer Electronics - Volume 1: AI4IoT; ISBN 978-989-758-661-3, SciTePress, pages 259-264. DOI: 10.5220/0012613000003739

in Bibtex Style

@conference{ai4iot23,
author={D. K. Aarthi and E. J. Fredrik},
title={Optimizing Dynamic Multi-Agent Performance in E-Learning Environment},
booktitle={Proceedings of the 1st International Conference on Artificial Intelligence for Internet of Things: Accelerating Innovation in Industry and Consumer Electronics - Volume 1: AI4IoT},
year={2023},
pages={259-264},
publisher={SciTePress},
organization={INSTICC},
doi={10.5220/0012613000003739},
isbn={978-989-758-661-3},
}

in EndNote Style

TY - CONF

JO - Proceedings of the 1st International Conference on Artificial Intelligence for Internet of Things: Accelerating Innovation in Industry and Consumer Electronics - Volume 1: AI4IoT
TI - Optimizing Dynamic Multi-Agent Performance in E-Learning Environment
SN - 978-989-758-661-3
AU - Aarthi D.
AU - Fredrik E.
PY - 2023
SP - 259
EP - 264
DO - 10.5220/0012613000003739
PB - SciTePress