流数据频繁模式挖掘算法的比较分析

2017 International Conference on Computing, Communication and Automation (ICCCA) Pub Date : 2017-05-01 DOI:10.1109/CCAA.2017.8229809

Shalini, Sanjay Kumar Jain

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引用次数: 1

摘要

跨流数据进行频繁的模式挖掘是一项具有挑战性的任务。它要求实时响应，计算复杂度高。在本文中，我们讨论了开发流数据频繁模式挖掘算法的挑战，比较了文献中提出的三种算法，并探讨了算法的改进范围。根据实际应用讨论了这些算法的适用性。

本文章由计算机程序翻译，如有差异，请以英文原文为准。

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A comparative analysis of frequent pattern mining algorithms used for streaming data

Frequent pattern mining across streaming data i s a challenging task. It require real time response and incurs great computational complexity. In this paper, we discuss challenges of developing frequent pattern mining algorithms for streaming data, compare three algorithms proposed in literature and explore scope of improvement in the algorithms. We discuss the suitability of these algorithms according to applications.

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2017 International Conference on Computing, Communication and Automation (ICCCA)

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