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Multicampaign Assignment Problem
March 2006 (vol. 18 no. 3)
pp. 405-414
It is crucial to maximize targeting efficiency and customer satisfaction in personalized marketing. State-of-the-art techniques for targeting focus on the optimization of individual campaigns. Our motivation is the belief that the effectiveness of a campaign with respect to a customer is affected by how many precedent campaigns have been recently delivered to the customer. We raise the multiple recommendation problem, which occurs when performing several personalized campaigns simultaneously. We formulate the multicampaign assignment problem to solve this issue and propose algorithms for the problem. The algorithms include dynamic programming and efficient heuristic methods. We verify by experiments the effectiveness of the problem formulation and the proposed algorithms.

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Index Terms:
Personalized marketing, multicampaign assignment, dynamic programming, heuristic algorithms.
Citation:
Yong-Hyuk Kim, Byung-Ro Moon, "Multicampaign Assignment Problem," IEEE Transactions on Knowledge and Data Engineering, vol. 18, no. 3, pp. 405-414, March 2006, doi:10.1109/TKDE.2006.49
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