A Note on Mathematical Modelling of Practical Multicampaign Assignment and Its Computational Complexity

Yong-Hyuk Kim; Yourim Yoon

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arXiv · 0906.5475

A Note on Mathematical Modelling of Practical Multicampaign Assignment and Its Computational Complexity

Yong-Hyuk Kim·Yourim Yoon

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Abstract

Within personalized marketing, a recommendation issue known as multicampaign assignment is to overcome a critical problem, known as the multiple recommendation problem which occurs when running several personalized campaigns simultaneously. This paper mainly deals with the hardness of multicampaign assignment, which is treated as a very challenging problem in marketing. The objective in this problem is to find a customer-campaign matrix which maximizes the effectiveness of multiple campaigns under some constraints. We present a realistic response suppression function, which is designed to be more practical, and explain how this can be learned from historical data. Moreover, we provide a proof that this more realistic version of the problem is NP-hard, thus justifying to use of heuristics presented in previous work.

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Yong-Hyuk Kim, Yourim Yoon. 2009-06-30. A Note on Mathematical Modelling of Practical Multicampaign Assignment and Its Computational Complexity. https://arxiv.org/abs/0906.5475

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