HybridRank: A Hybrid Content-Based Approach To Mobile Game Recommendations

نویسندگان

  • Anthony Chow
  • Min-Hui Nicole Foo
  • Giuseppe Manai
چکیده

The massive number of mobile games available necessitates a technique to help the consumer find the right game at the right time. This paper introduces HybridRank, a novel hybrid algorithm to deliver recommendations for mobile games. This technique is based on a personalised random walk approach, with the incorporation of both content-based and user-based information in the formulation of the recommendations. This technique is evaluated against traditional neighbourhood based collaborative filtering and content-based recommendation algorithms. This paper also explores the fact that this algorithm can also be used to help alleviate the cold start problem that is associated with little user data.[1] Online evaluations were conducted and results yield that the approach presented performed the best in both a controlled testing environment as well as in live production. This algorithm is currently implemented in a live mobile game platform developed by Singapore Telecommunications Ltd called WePlay.

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تاریخ انتشار 2014