A recommendation solution for multi person dinner location
Shu-Cheng Yang, Yichuan Yang, Xinyu Miao · 2017
Restaurant recommended software has been a lot, but for many people have not yet dinner, more than dinner to consider not only everyone's preferences, but also need to consider the location of dining personnel and other information. This article will introduce a solution to the multi-person dining recommendation. First of all, through the association rules mining relationship between the cuisines. Next, based on the influence of the time on the user's selection, the possible dining information is supplemented based on the result of the association rule. And then through the statistical order to be recommended for dining cuisine type. The next step is to determine the restaurant's range using the location information of the diner and the restaurant density data. The season is then used to exclude seasonally unsuitable restaurants. Finally, restaurant recommendations are based on restaurant ratings, restaurant per capita consumption, cuisine and location.