Contextual Sequential Pattern Mining in Games: Rock, Paper, Scissors, Lizard, Spock

Traditional sequential pattern algorithms do not usually take consideration of contextual information commonly associated with sequential data. Our project is based on the non-cooperative game Rock Paper Scissors Lizard Spock by associating the age and sex of the player in order to bring to light the hidden correlations in the data or general gaming trends. Considering the hypothesis that a sequential pattern is specific to a particular sex and age, we propose to extract patterns of the form: after playing figure A followed by figure B, men aged between 18 and 22 years tend to play figure C.

[1]  Pascal Poncelet,et al.  Contextual Sequential Pattern Mining , 2010, 2010 IEEE International Conference on Data Mining Workshops.

[2]  Tomasz Imielinski,et al.  Mining association rules between sets of items in large databases , 1993, SIGMOD Conference.

[3]  Zhijian Wang,et al.  Social cycling and conditional responses in the Rock-Paper-Scissors game , 2014, Scientific Reports.

[4]  Anne Laurent,et al.  M2SP: Mining Sequential Patterns Among Several Dimensions , 2005, PKDD.

[5]  Radoslaw Ziembinski Algorithms for Context Based Sequential Pattern Mining , 2007, Fundam. Informaticae.

[6]  Ramakrishnan Srikant,et al.  Mining sequential patterns , 1995, Proceedings of the Eleventh International Conference on Data Engineering.

[7]  Umeshwar Dayal,et al.  Multi-dimensional sequential pattern mining , 2001, CIKM '01.