Implementation of a Recommendation System Using Association Rules and Collaborative Filtering

In this study, a recommendation system was designed and implemented which analyzes using patterns and personal propensities of customers by using association rule analysis and collaborative filtering for collected customer data on visiting customer companies with NFC (Near Field Communication). The recommendation algorithm used in the proposed system used the data analysis results and the distance data from GPS (Global Positioning System) to recommend local businesses that people are highly likely to visit.