+
MovieLens Dataset User-Movie Preference Analysis Report
+
+
+
Data Overview
+
This analysis is based on the MovieLens dataset, containing 6040 users、3883 movies and 1000209 original rating records。
+
+
+
User Profile Analysis
+
+
+
+
+
+
+
Movie Distribution Analysis
+
+
+
+
+
+
+
Rating Distribution Analysis
+
+
+
+
+
+
+
User Characteristics and Movie Preferences
+
+
+
+
+
+
+
+
+
Conclusions and Insights
+
Through in-depth analysis of the MovieLens dataset, we found significant correlations between user characteristics (gender, age, occupation) and movie preferences. Key findings include:
+
+ - Significant differences in movie genre preferences between genders
+ - Age influences how users rate movies from different decades
+ - Occupational background correlates with genre preferences
+
+
These findings provide valuable reference for designing movie recommendation systems and developing movie marketing strategies.
+
+
{"MovieLens数据集用户-电影偏好分析报告" if USE_CHINESE else "MovieLens Dataset User-Movie Preference Analysis Report"}
+
+
+
{"数据概览" if USE_CHINESE else "Data Overview"}
+
{"本分析基于MovieLens数据集，包含" if USE_CHINESE else "This analysis is based on the MovieLens dataset, containing"} {len(self.users_df)} {"位用户" if USE_CHINESE else "users"}、{len(self.movies_df)} {"部电影" if USE_CHINESE else "movies"} {"和" if USE_CHINESE else "and"} {len(self.ratings_df)} {"条原始评分记录" if USE_CHINESE else "original rating records"}。
+
+
+
{"用户基本情况分析" if USE_CHINESE else "User Profile Analysis"}
+
+
+
+
+
+
+
{"电影分布情况分析" if USE_CHINESE else "Movie Distribution Analysis"}
+
+
+
+
+
+
+
{"评分分布情况分析" if USE_CHINESE else "Rating Distribution Analysis"}
+
+
+
+
+
+
+
{"用户特征与电影偏好分析" if USE_CHINESE else "User Characteristics and Movie Preferences"}
+
+
+
+
+
+
+
+
+
{"结论与洞察" if USE_CHINESE else "Conclusions and Insights"}
+
{"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：" if USE_CHINESE else "Through in-depth analysis of the MovieLens dataset, we found significant correlations between user characteristics (gender, age, occupation) and movie preferences. Key findings include:"}
+
+ - {"不同性别用户在电影类型偏好上存在明显差异" if USE_CHINESE else "Significant differences in movie genre preferences between genders"}
+ - {"年龄因素会影响用户对不同年代电影的评价" if USE_CHINESE else "Age influences how users rate movies from different decades"}
+ - {"职业背景与电影类型偏好具有相关性" if USE_CHINESE else "Occupational background correlates with genre preferences"}
+
+
{"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。" if USE_CHINESE else "These findings provide valuable reference for designing movie recommendation systems and developing movie marketing strategies."}
+
+ 
+ 
+ 
+ 
+ 
+ 
+ 
+ 
+ 
+ 
+ 
+ 
+