A Chinese dishes recommendation algorithm based on personal taste

There are few Chinese dish recommendation algorithms due to the variety of Chinese dishes. It could be impossible to find one´s most liked dishes in a restaurant through the name or the ingredients of a dish. The algorithm in this paper uses the user´s ordering history to quantify one´s taste by k-means clustering method and determines the number of user´s favorite tastes by the BWP index. With the knowledge of user´s tastes, screen matrix are used to rank the dishes according to the user´s taste in any restaurant.