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Rule-based Matching and Hidden Markov Model-based Warning for Brushing Behavior

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DOI: 10.23977/jaip.2024.070119 | Downloads: 5 | Views: 145

Author(s)

Jian Wang 1, Yang Liu 1

Affiliation(s)

1 Shandong Yantai Tobacco Co., Ltd., Yantai, 264000, China

Corresponding Author

Jian Wang

ABSTRACT

This paper proposes a warning system for brushing behavior based on the tobacco industry's reward activities by combining rule-based matching and Hidden Markov Models. Targeting behaviors where customers make large-scale purchases during promotional events that deviate from their individual historical consumption patterns, the system employs rule-based matching for initial assessment, followed by a more in-depth behavioral analysis using Hidden Markov Models. Experimental results demonstrate the significant effectiveness of the system in warning against brushing behavior, providing an effective monitoring tool for the tobacco industry and similar sectors.

KEYWORDS

Rule-based matching, Hidden Markov Model, Brushing behavior, Warning system, Tobacco industry, Consumer behavior, Point redemption

CITE THIS PAPER

Jian Wang, Yang Liu, Rule-based Matching and Hidden Markov Model-based Warning for Brushing Behavior. Journal of Artificial Intelligence Practice (2024) Vol. 7: 124-131. DOI: http://dx.doi.org/10.23977/jaip.2024.070119.

REFERENCES

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