Effectiveness of Different Recommender Algorithms in the Mobile Internet: A Case Study

Kolja Hegelich, Dietmar Jannach
2009 International Joint Conference on Artificial Intelligence  
Despite the broad use of Recommender Systems (RS) technology in various domains, the number of publicly available reports on the actual business value of such systems is limited. This paper presents first results of an empirical evaluation of how different recommendation algorithms affect the navigation and buying behavior of a sample of over 155.000 different customers on a commercial Mobile Internet portal for cell phone games. The evaluated RS algorithms include itembased collaborative
more » ... ing, SlopeOne, a content-based as well as a hybrid technique, which were compared with naive approaches based on top-selling and top-rated items. The analysis shows that RS measurably affected the navigation and buying behavior of the portal visitors. The personalized recommendation lists not only attracted more clicks on detailed item descriptions but also lead to an overall sales increase when compared with control groups that received nonpersonalized recommendations or no recommendations during the evaluation period. The comparison of different algorithms brought no clear winner that consistently outperformed the others. However, the results indicate that the choice of the recommendation technique should depend on the specific navigational situation in which recommendation lists are presented.
dblp:conf/ijcai/HegelichJ09 fatcat:lyimcx6itvc5bjxp4os3zwt3dy