Research on O2O take-away restaurant recommendation system: taking ele.me APP as an example

Online to Offline (O2O) take-away has the great potentialT for development in China, but with a large number of merchants taking part in O2O take-away APP, resulting in the problem of information overload. And the recommended system can effectively relieve the information overload of APP. In this paper, the O2O take-away restaurant recommendation system is studied in detail. By analyzing the current situation of the O2O takeaway restaurant recommendation system, we put forward a recommendation algorithm based on rank-centroid/analytic hierarchy process. Through transforming the recent booking preferences of user into the take-away service standard weight, we establish the model, combined with the case of ele.me APP, compute actual scores of the restaurants by the comprehensive score, and choose the high score of the restaurants to recommend. Compared with the mainstream collaborative filtering recommendation method, the proposed method is simple and computationally smaller.