用户对古装类视频偏好等级数据

通过对用户点击历史数据的分析，可以精准把握其对视频题材、类型和风格的偏好，并据此为用户推荐他们感兴趣的内容。当有新的古装类视频需要推广时，可以优先推送给对该类视频兴趣浓厚的A级用户。此外，基于用户的点击偏好数据，能够实现广告的精准投放，将广告精准地推送给目标受众，从而有效提高广告的点击率和转化率。例如，对于A级用户，广告商可以投放与古装类视频相关的产品广告，如该类视频的周边产品等。由于这些用户对古装类视频兴趣浓厚，他们对相关产品广告的接受度往往会更高。1.数据收集：通过小网影视展示系统收集用户对古装类视频的点击数据。2.数据处理：该类视频点击占比=该用户该类视频点击量/当月该用户总点击量*100%（保留小数点后两位）。点击量的计量单位为【次】。用户偏好等级分类运用ABC分类法，该类视频点击占比大于40%，用户偏好等级为A;该类视频点击占比大于20%小于等于40%，用户偏好等级为B;该类视频点击占比小于等于20%则用户偏好等级为C。

By analyzing users' click history data, their preferences for video themes, genres and styles can be accurately grasped, and targeted content recommendations can be delivered based on these preferences. When promoting new costume-themed videos, they can be prioritized to Class A users who have a strong interest in such content. Additionally, based on users' click preference data, precise advertisement delivery can be achieved, with ads accurately targeted to the intended audience, effectively enhancing the advertisement click-through rate (CTR) and conversion rate. For example, advertisers can launch product advertisements related to costume-themed videos, such as peripheral products of such videos, targeting Class A users. Since these users have a strong interest in costume-themed videos, their acceptance of relevant product advertisements is usually higher.
1. Data Collection: Collect users' click data on costume-themed videos via the Xiaowang Video Display System.
2. Data Processing: The click proportion of such videos = (the number of clicks of a user on such videos / the total number of clicks of the user in the current month) × 100% (rounded to two decimal places). The unit of measurement for click volume is [times]. The user preference level is classified using the ABC classification method: Class A if the click proportion of such videos exceeds 40%; Class B if the click proportion is greater than 20% and less than or equal to 40%; Class C if the click proportion is less than or equal to 20%.

搜集汇总

背景与挑战

背景概述

该数据集包含539条用户对古装类视频的偏好数据，每月更新，通过点击量占比计算用户偏好等级（A、B、C），用于精准内容推荐和广告投放，提升用户体验和商业转化率。