Discovering temporal frequent patterns: An optimized approach

Sheel Shalini; Sweta Kumari

doi:10.30574/ijsra.2024.12.2.1366

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Discovering temporal frequent patterns: An optimized approach

Sheel Shalini ^* and Sweta Kumari

Department of Computer Science and Engineering, Birla Institute of Technology Mesra, Patna, India.

Review Article

International Journal of Science and Research Archive, 2024, 12(02), 1273–1278

Article DOI: 10.30574/ijsra.2024.12.2.1366

DOI url: https://doi.org/10.30574/ijsra.2024.12.2.1366

Publication history

Received on 30 March 2024; revised on 23 July 2024; accepted on 26 July 2024

Abstract

Temporal frequent pattern mining is a critical area of data mining that focuses on identifying recurring set of events over time. Traditional methods often face challenges related to scalability, data complexity, and noise, necessitating the development of optimized approaches. This survey reviews the existing literature on temporal frequent pattern mining, highlights the limitations of traditional techniques, and presents recent advancements in optimized methods. The paper also discusses future directions and applications across various domains.

Keywords

Temporal Frequent pattern Mining; Optimized Approaches; Parallel and Distributed Computing; Dynamic Time Window; Pattern Pruning Technique; Recent Advancements

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How to cite this article

Sheel Shalini and Sweta Kumari. Discovering temporal frequent patterns: An optimized approach. International Journal of Science and Research Archive, 2024, 12(02), 1273–1278. Article DOI: https://doi.org/10.30574/ijsra.2024.12.2.1366

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