User Churn Migration Analysis with DEDICOM

Time plays an important role regarding user preferences for products. It introduces asymmetries into the adoption of products which should be considered in the context of recommender systems and business intelligence. We therefore investigate how temporally asymmetric user preferences can be analyzed using a latent factor model called Decomposition Into Directional Components (DEDICOM). We introduce a new scalable hybrid algorithm that combines projected gradient descent and alternating least squares updates to compute DEDICOM and imposes semi-nonnegativity constraints to better interpret the resulting factors. We apply our model to analyze user churn and migration between different computer games in a social gaming environment.

[1]  Henk A. L. Kiers.  Desicom: Decomposition of Asymmetric Relationships Data into Simple Components , 1997 .

[2]  C. Lawson,et al.  Solving least squares problems , 1976, Classics in applied mathematics.

[3]  Yehuda Koren,et al.  Towards scalable and accurate item-oriented recommendations , 2013, RecSys.

[4]  Alla Rozovskaya,et al.  Using DEDICOM for Completely Unsupervised Part-of-Speech Tagging , 2009 .

[5]  Charles L. Lawson,et al.  Solving least squares problems , 1976, Classics in applied mathematics.

[6]  Peng Gao,et al.  Churn prediction for high-value players in casual social games , 2014, 2014 IEEE Conference on Computational Intelligence and Games.

[7]  Yehuda Koren,et al.  Matrix Factorization Techniques for Recommender Systems , 2009, Computer.

[8]  Tamara G. Kolda,et al.  Temporal Analysis of Semantic Graphs Using ASALSAN , 2007, Seventh IEEE International Conference on Data Mining (ICDM 2007).

[9]  Christian Bauckhage,et al.  Predicting player churn in the wild , 2014, 2014 IEEE Conference on Computational Intelligence and Games.

[10]  R. Bro,et al.  A fast non‐negativity‐constrained least squares algorithm , 1997 .

[11]  Christian Bauckhage,et al.  Beyond heatmaps: Spatio-temporal clustering using behavior-based partitioning of game levels , 2014, 2014 IEEE Conference on Computational Intelligence and Games.