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Predicting the influence of group buying on the restaurant's popularity by online reviews

机译:通过在线评论预测团购对餐厅人气的影响

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摘要

Group buying, which provides considerable discounts for various services and products, is a novel marketing strategy that has been very popular all over the world in recent years. Customers, merchants and websites all can gain benefits from successful group buying campaigns. However, group buying is not always effective, merchants have to seriously consider that whether they are under appropriate business conditions and adopt proper group buying strategies. Different from the perspective of customers and websites held in most existing work, we focus on the impact of group buying on the operation performance from the aspect of merchants, especially restaurants. Based on online user reviews, we try to predict a restaurant's popularity, which is an important measurement of its operation performance, during and after a group buying campaign. We consider this problem as a time series prediction problem. Under the framework of a typical intervention analysis model, we propose a new approach to handle this problem. A comprehensive experimental study on the real-world dataset has been conducted to demonstrate that our proposed methods are effective and outperform existing methods in predicting a restaurant's popularity.
机译:团购是一种新颖的营销策略,为各种服务和产品提供了可观的折扣,近年来,这种策略已在全球范围内广受欢迎。客户,商人和网站都可以从成功的团购活动中受益。但是,团购并不总是有效的,商家必须认真考虑自己是否处于适当的商业条件下,并采取适当的团购策略。从大多数现有工作中所拥有的客户和网站的角度来看,我们从商人(尤其是餐馆)的角度着眼于团购对运营绩效的影响。根据在线用户评论,我们尝试预测在团购活动期间和之后,餐厅的受欢迎程度,这是衡量餐厅运营绩效的重要指标。我们将此问题视为时间序列预测问题。在典型的干预分析模型的框架下,我们提出了一种解决该问题的新方法。已对现实世界数据集进行了全面的实验研究,以证明我们提出的方法在预测餐厅受欢迎程度方面有效且优于现有方法。

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