基于k近邻算法的个性口红颜色推荐系统

Ryan Adiputra, N. Iswari, Wella Wella
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引用次数: 2

摘要

口红是一种唇色,有很多颜色可供选择。一项研究表明,对女性性格的即时评价可以通过她们对口红颜色的选择来衡量。因此,有必要使用合适的口红颜色,以获得个性和外表之间的和谐。本实验采用k近邻算法和MBTI人格测试工具对口红颜色进行推荐。该系统基于Android应用程序构建。欧几里得距离值受年龄、内向、感觉、思维和判断5个因素的影响。通过提取7个欧几里得距离最近的训练数据,与性格测试结果进行对比,得出口红颜色推荐。在这个实验中使用的颜色是裸色、粉色、红色、橙色和紫色。经过评估,该应用程序的分类准确率为87.38%,为良好分类,准确率和召回率均为75.68%,为公平分类。软件质量得分为79.13%,被认为是良好的质量。关键词:k近邻,数据挖掘,Myers-Briggs类型指标,推荐系统,口红。
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Personality Based Lipstick Color Recommender System using K-Nearest Neighbors Algorithm
Lipstick is a lip color which available in many colors. A research said instant valuation of woman personality can be figured by their lipstick color choice. Therefore there is a necessity to use the right lipstick color to obtain a harmony between personality and appearance. This experiment was conducted to give lipstick color recommendation by using K-Nearest Neighbors algorithm, and Myers-Briggs Type Indicator (MBTI) personality test instrument. The system was built on Android application. Euclidean distance value is affected by 5 factors which are age, introvert, sensing, thinking, and judging. Lipstick color recommendation is obtained by fetching 7 training data with nearest Euclidean distance when compared to personality test result. The colors used in this experiment are nude, pink, red, orange, and purple. After evaluation, it is obtained the application’s accuracy of 87.38% which considered as good classification, both precision and recall with 75.68% which considered as fair classification. The score for software quality is 79.13% which considered as good quality. Keywords—K-Nearest Neighbors, Data Mining, Myers-Briggs Type Indicator,Recommender System, Lipstick.  
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