Data mining in AI: Evolution, applications, and future directions

Zongjian Wu

doi:10.54254/2755-2721/104/20240904

Research Article

Open access

Published on 8 November 2024

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Wu,Z. (2024). Data mining in AI: Evolution, applications, and future directions. Applied and Computational Engineering,104,1-6.

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Data mining in AI: Evolution, applications, and future directions

Zongjian Wu *^,1,

¹ The University of Queensland

* Author to whom correspondence should be addressed.

https://doi.org/10.54254/2755-2721/104/20240904

Abstract

This paper provides a comprehensive analysis of the evolution and impact of data mining in the field of artificial intelligence (AI), with a particular focus on its application within social and information networks. It traces the origins of AI back to the 1956 Dartmouth Conference, highlighting the subsequent advancements in technologies such as machine learning and data mining that have fueled AI's growth. The paper explores the multifaceted applications of data mining in various sectors including healthcare, transportation, and industrial manufacturing, and delves into the challenges and innovations in recommendation systems, matrix factorization, and intelligent control of autonomous vehicles in intelligent transportation systems. The study emphasizes the significance of distributed algorithms and big data processing frameworks in enhancing the efficiency and applicability of data mining techniques.

Keywords

Artificial Intelligence, Data Mining, Machine Learning, Distributed Algorithms, MapReduce Framework.

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References

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Cite this article

Wu,Z. (2024). Data mining in AI: Evolution, applications, and future directions. Applied and Computational Engineering,104,1-6.

Data availability

The datasets used and/or analyzed during the current study will be available from the authors upon reasonable request.

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About volume

Volume title: Proceedings of the 2nd International Conference on Machine Learning and Automation

Conference website: https://2024.confmla.org/

ISBN：978-1-83558-697-6(Print) / 978-1-83558-698-3(Online)

Conference date: 12 January 2025

Editor：Mustafa ISTANBULLU

Series: Applied and Computational Engineering

Volume number: Vol.104

ISSN：2755-2721(Print) / 2755-273X(Online)

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