Wine Recommendation System Using the Optimum Degree of Similarity

초록

Recently, South Korea's drinking culture is changing. Not to take drinking, drink to enjoy the atmosphere. There is an increasing consumption of wine to enjoy wine. The taste of the wine is determined by breed, vintage, etc. Wine of the latest trends is a good assessment of the quality, grade, and in particular the lower price. In this paper, to find similar users, based on the evaluation of wine. And we are using a collaborative filtering to recommend the wine that users prefer. To distributed storage of wine data and shorten to analysis time. By adding a weighting element to the system, it is possible to obtain a more accurate recommendation.