A dynamic understanding of customer behavior processes based on clustering and sequence mining

作者：

Highlights：

• The dynamics of data points is studied based on clustering and sequence mining.

• A general methodology based on different algorithms is proposed.

• Visual and statistical approaches are used in order to obtain comprehensible results.

• Prior knowledge is introduced in order to guide the clustering algorithms.

• The framework is applied to a real-life case of an event organizer.

摘要

•The dynamics of data points is studied based on clustering and sequence mining.•A general methodology based on different algorithms is proposed.•Visual and statistical approaches are used in order to obtain comprehensible results.•Prior knowledge is introduced in order to guide the clustering algorithms.•The framework is applied to a real-life case of an event organizer.

论文关键词：Clustering,Sequence mining,Business knowledge,Behavior process,Trajectories,Direct marketing

论文评审过程：Available online 5 February 2014.

论文官网地址：https://doi.org/10.1016/j.eswa.2014.01.022