針對亞洲消費者設計的美妝保養品推薦與經驗收集系統

Abstract

每種美妝保養品的設計都是針對不同的消費族群與症狀所設計，市面上的美妝保養品玲瑯滿目，消費者又缺乏美妝保養品的專業知識。所以，消費者很難在數萬種的產品中辨識出真正適合自己的美妝保養品。本研究提出一套演算法，讓消費者輸入自己的個人屬性資料，透過這些資料從資料庫塞選適合消費者的產品。更多的是，本研究演算法設計產品經驗回饋表，收集消費者的產品使用經驗，優化推薦給消費者產品的結果。

Each individual beauty product is designed for specific customer group and conditions. Since there are hundreds of thousands of beauty products in market and most customers lack of knowledge about beauty product, thus it is hard for the customers to find real suitable product that really fits their need. In this thesis, we implement an application program that allows consumers to input personal conditions, then our program further accesses the personalized data from the database for classification, then it produces recommendations of beauty products to that customer. Furthermore, in this research work, we designed a customized table that allows consumers to record their product experiences, which then used by our recommender system to further optimized the results.