用户对美食类视频喜好等级分层数据

在日常生活工作之余，越来越多的人喜欢刷视频来缓解压力，有部分人群对美食类视频感兴趣。统计分析用户观看美食类视频的数据，通过对历史观看用户建立表格，对用户进行标签制定，定位用户喜好级别，通过大数据推广，为用户推送符合喜好的视频提供数据支持。1. 数据采集:采集用户对美食类视频的点击数量等信息; 2. 用户点击数量占总点击数量的比例=用户点击数量/总点击数量*100%； 3. 用户点击数量占总点击数量的比例按从大到小进行排名；分类运用ABCDEF分类法，对占比0.26%以上的，给予“A类用户”分层；占比0.21%到0.25%区间的，则给予“B类用户”分层；占比在0.16%到0.20%区间，则给予“C类用户”分层；占比在0.11%到0.15%区间，则给予“D类用户”分层；占比在0.06%到0.1%区间，则给予“E类用户”分层；占比在0.05%以下，则给予“F类用户”分层； 4. 数据应用: 美食类视频的点击次数结果可以作为用户喜好等级评价的依据，为监管部门向监管提供技术支撑。

In addition to daily life and work, an increasing number of people prefer watching videos to relieve stress, with a subset of users showing interest in food-related videos. This dataset conducts statistical analysis on user viewing data of food-related videos: it establishes tables for users with historical viewing records, formulates user tags to locate their preference levels, and provides data support for delivering videos matching user preferences via big data-driven promotion.
1. Data Collection: Collect information including the number of clicks users make on food-related videos;
2. Proportion of a user's clicks to total clicks = (user clicks / total clicks) * 100%;
3. Rank the calculated proportions in descending order. Adopt the ABCDEF classification method to stratify users: users with a proportion above 0.26% are classified as "Category A users"; those with a proportion ranging from 0.21% to 0.25% are "Category B users"; users with a proportion between 0.16% and 0.20% fall into "Category C users"; those with a proportion of 0.11% to 0.15% are "Category D users"; users with a proportion of 0.06% to 0.10% are "Category E users"; and those with a proportion below 0.05% are "Category F users";
4. Data Application: The click count results of food-related videos can be used as a basis for evaluating users' preference levels, providing technical support for regulatory authorities to carry out their supervision work.