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A Projected Upper Bound for Mining High Utility Patterns from Interval-Based Event Sequences

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Recent Challenges in Intelligent Information and Database Systems (ACIIDS 2023)

Part of the book series: Communications in Computer and Information Science ((CCIS,volume 1863))

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Abstract

High utility pattern mining is an interesting yet challenging problem. The intrinsic computational cost of the problem will impose further challenges if efficiency in addition to the efficacy of a solution is sought. Recently, this problem was studied on interval-based event sequences with a constraint on the length and size of the patterns. However, the proposed solution lacks adequate efficiency. To address this issue, we propose a projected upper bound on the utility of the patterns discovered from sequences of interval-based events. To show its effectiveness, the upper bound is utilized by a pruning strategy employed by the HUIPMiner algorithm. Experimental results show that the new upper bound improves HUIPMiner performance in terms of both execution time and memory usage.

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Correspondence to S. Mohammad Mirbagheri .

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Mirbagheri, S.M. (2023). A Projected Upper Bound for Mining High Utility Patterns from Interval-Based Event Sequences. In: Nguyen, N.T., et al. Recent Challenges in Intelligent Information and Database Systems. ACIIDS 2023. Communications in Computer and Information Science, vol 1863. Springer, Cham. https://doi.org/10.1007/978-3-031-42430-4_30

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  • DOI: https://doi.org/10.1007/978-3-031-42430-4_30

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  • Print ISBN: 978-3-031-42429-8

  • Online ISBN: 978-3-031-42430-4

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