MovieLens/analysis_results/analysis_report.html

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<!DOCTYPE html>
<html>
<head>
<meta charset="utf-8">
<title>MovieLens数据集分析报告</title>
<style>
body { font-family: Arial, sans-serif; margin: 0; padding: 20px; color: #333; }
.container { max-width: 1200px; margin: 0 auto; }
h1 { color: #2c3e50; text-align: center; margin-bottom: 30px; }
h2 { color: #3498db; margin-top: 30px; border-bottom: 1px solid #eee; padding-bottom: 10px; }
.summary { background-color: #f9f9f9; padding: 15px; border-radius: 5px; margin-bottom: 20px; }
.gallery { display: flex; flex-wrap: wrap; gap: 20px; justify-content: center; margin-top: 20px; }
.gallery img { max-width: 100%; height: auto; border-radius: 5px; box-shadow: 0 2px 5px rgba(0,0,0,0.1); }
.figure { margin-bottom: 30px; text-align: center; }
.figure img { max-width: 100%; height: auto; border-radius: 5px; box-shadow: 0 2px 5px rgba(0,0,0,0.1); }
.figure .caption { margin-top: 10px; font-style: italic; color: #666; }
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tr:hover { background-color: #f5f5f5; }
</style>
</head>
<body>
<div class="container">
<h1>MovieLens数据集用户-电影偏好分析报告</h1>
<div class="summary">
<h2>数据概览</h2>
<p>本分析基于MovieLens数据集包含 6040 位用户、3883 部电影 和 1000209 条原始评分记录。</p>
</div>
<h2>用户基本情况分析</h2>
<div class="figure">
<img src="user_analysis/gender_distribution.png" alt="User Gender Distribution">
<p class="caption">用户性别分布</p>
</div>
<div class="figure">
<img src="user_analysis/age_distribution.png" alt="User Age Distribution">
<p class="caption">用户年龄分布</p>
</div>
<div class="figure">
<img src="user_analysis/occupation_distribution.png" alt="User Occupation Distribution">
<p class="caption">用户职业分布</p>
</div>
<h2>电影分布情况分析</h2>
<div class="figure">
<img src="movie_analysis/genre_distribution.png" alt="Movie Genre Distribution">
<p class="caption">电影类型分布</p>
</div>
<div class="figure">
<img src="movie_analysis/year_distribution.png" alt="Movie Release Year Distribution">
<p class="caption">电影发行年份分布</p>
</div>
<div class="figure">
<img src="movie_analysis/most_rated_movies.png" alt="Top 20 Most Rated Movies">
<p class="caption">评分数量最多的20部电影</p>
</div>
<h2>评分分布情况分析</h2>
<div class="figure">
<img src="rating_analysis/rating_distribution.png" alt="Rating Distribution">
<p class="caption">评分分布情况</p>
</div>
<div class="figure">
<img src="rating_analysis/genre_avg_ratings.png" alt="Average Rating by Movie Genre">
<p class="caption">各类型电影的平均评分</p>
</div>
<div class="figure">
<img src="rating_analysis/top_rated_movies.png" alt="Top 20 Highest Rated Movies">
<p class="caption">评分最高的20部电影至少有100个评分</p>
</div>
<h2>用户特征与电影偏好分析</h2>
<div class="figure">
<img src="preference_analysis/gender_genre_heatmap.png" alt="Movie Genre Preferences by Gender">
<p class="caption">不同性别的电影类型偏好对比</p>
</div>
<div class="figure">
<img src="preference_analysis/age_genre_heatmap.png" alt="Movie Genre Preferences by Age Group">
<p class="caption">不同年龄段的电影类型偏好对比</p>
</div>
<div class="figure">
<img src="preference_analysis/age_year_heatmap.png" alt="Preferences for Movies by Decade Across Age Groups">
<p class="caption">不同年龄段对不同年代电影的偏好</p>
</div>
<div class="figure">
<img src="preference_analysis/gender_avg_rating.png" alt="Average Rating by Gender">
<p class="caption">性别与平均评分的关系</p>
</div>
<h2>结论与洞察</h2>
<p>通过对MovieLens数据集的深入分析我们发现了用户特征如性别、年龄、职业与电影偏好之间存在显著关联。主要结论包括</p>
<ul>
<li>不同性别用户在电影类型偏好上存在明显差异</li>
<li>年龄因素会影响用户对不同年代电影的评价</li>
<li>职业背景与电影类型偏好具有相关性</li>
</ul>
<p>这些发现对于电影推荐系统的设计和电影营销策略制定具有重要参考价值。</p>
</div>
</body>
</html>