Threshold Influence Model for Allocating Advertising Budgets
Threshold Influence Model for Allocating Advertising Budgets
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发表时间：
2015-07
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通讯作者：
Atsushi Miyauchi;Yuni Iwamasa;Takuro Fukunaga;Naonori Kakimura
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作者：
Atsushi Miyauchi;Yuni Iwamasa;Takuro Fukunaga;Naonori Kakimura
我们提出了一个新的影响力模型分配预算的广告渠道。我们的模型捕捉到客户的敏感性广告作为一个阈值行为，客户预计将受到影响，如果他收到的影响超过了他的阈值。在阈值模型上，我们讨论了两个优化问题。第一个是受约束的影响最大化。提出了两种基于不同策略的贪婪算法，并分析了影响为次模时的性能。然后，我们引入了一个新的特征来衡量营销活动的成本效益，即所产生的影响力与所花费的成本的比例。我们设计了一个近似线性时间的算法，以最大限度地提高成本效益。在此基础上，针对一种特殊情况，设计了一种基于线性规划的近似算法。我们进行彻底的实验，以确认我们的算法优于基线算法。
We propose a new influence model for allocating budgets to advertising channels. Our model captures customer's sensitivity to advertisements as a threshold behavior; a customer is expected to be influenced if the influence he receives exceeds his threshold. Over the threshold model, we discuss two optimization problems. The first one is the budget-constrained influence maximization. We propose two greedy algorithms based on different strategies, and analyze the performance when the influence is submodular. We then introduce a new characteristic to measure the cost-effectiveness of a marketing campaign, that is, the proportion of the resulting influence to the cost spent. We design an almost linear-time approximation algorithm to maximize the cost-effectiveness. Furthermore, we design a better-approximation algorithm based on linear programming for a special case. We conduct thorough experiments to confirm that our algorithms outperform baseline algorithms.