arXiv:2511.08363cs.AI2025-11

AI自动分析数据并生成交互式可视化,省去手动操作

AI-Powered Data Visualization Platform: An Intelligent Web Application for Automated Dataset Analysis

  • 用AI自动清洗数据、补全缺失值、检测异常点
  • 支持百万级数据实时分析,多用户并发处理
  • 适合非技术用户快速获取高质量数据洞察

一个基于AI的数据可视化平台,可自动完成从上传数据到生成交互式可视化的全流程。采用先进机器学习算法对数据进行清洗与预处理,分析特征并自动选择合适的可视化方式。系统通过Python Flask后端与React前端结合,对接Firebase云存储,实现多源数据处理与实时分析。关键贡献包括:自动智能清洗(含缺失值插补与异常点检测)、四种算法智能选特征、根据数据属性自动生成标题与可视化。在两个独立数据集上评估性能,支持最大10万行数据的实时分析,云平台可同时服务多用户请求。结果表明,该平台显著减少人工干预,保持高质、有影响力的可视化输出与用户体验。

原文摘要 · Abstract (English)

An AI-powered data visualization platform that automates the entire data analysis process, from uploading a dataset to generating an interactive visualization. Advanced machine learning algorithms are employed to clean and preprocess the data, analyse its features, and automatically select appropriate visualizations. The system establishes the process of automating AI-based analysis and visualization from the context of data-driven environments, and eliminates the challenge of time-consuming manual data analysis. The combination of a Python Flask backend to access the dataset, paired with a React frontend, provides a robust platform that automatically interacts with Firebase Cloud Storage for numerous data processing and data analysis solutions and real-time sources. Key contributions include automatic and intelligent data cleaning, with imputation for missing values, and detection of outliers, via analysis of the data set. AI solutions to intelligently select features, using four different algorithms, and intelligent title generation and visualization are determined by the attributes of the dataset. These contributions were evaluated using two separate datasets to assess the platform's performance. In the process evaluation, the initial analysis was performed in real-time on datasets as large as 100000 rows, while the cloud-based demand platform scales to meet requests from multiple users and processes them simultaneously. In conclusion, the cloud-based data visualization application allowed for a significant reduction of manual inputs to the data analysis process while maintaining a high quality, impactful visual outputs, and user experiences

数据可视化AI自动化云平台智能清洗

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