Changing perspectives: Using graph metrics to predict purchase probabilities
作者：
Highlights：
• We assess the applicability of graph metrics to predict purchase probabilities.
• Real-world clickstream data of two online retailers is used.
• Graphs are derived out of sessions of website visitors.
• Distance- and centrality-based graph metrics are useful for prediction.
• Closeness vitality, radius, number of circles and self-loops are most important.
摘要
•We assess the applicability of graph metrics to predict purchase probabilities.•Real-world clickstream data of two online retailers is used.•Graphs are derived out of sessions of website visitors.•Distance- and centrality-based graph metrics are useful for prediction.•Closeness vitality, radius, number of circles and self-loops are most important.
论文关键词：Predictive analytics,Clickstream data,User graph,Graph metrics
论文评审过程：Received 20 June 2017, Revised 20 October 2017, Accepted 21 October 2017, Available online 23 October 2017, Version of Record 5 November 2017.
论文官网地址：https://doi.org/10.1016/j.eswa.2017.10.046
