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本项目是一个基于 Flask 后端和 Jinja2 模板引擎的网页应用,同时包含了 TF-IDF 算法用于文章推荐

Shell 0.55% Python 54.99% HTML 41.06% Dockerfile 3.40%

first_flask_project's Introduction

First_Flask_Project

项目描述:本项目是一个基于 Flask 后端和 Jinja2 模板引擎的网页应用,同时包含了 TF-IDF 算法用于文章推荐。

功能

文章推荐:基于 TF-IDF 算法,具有刑事案件的相似度的文章推荐功能。算法会根据用户输入的相关内容进行匹配,以推荐相似度最高的5篇文章。

文章推荐算法 本项目使用 TF-IDF 算法进行文章推荐。算法包含以下步骤:

  1. 文本预处理:对文章进行分词、去除停用词等预处理操作。
  2. 构建词频矩阵:统计每篇文章中每个词的出现频率,构建词频矩阵。
  3. 计算 TF-IDF 值:根据词频矩阵计算每个词的 TF-IDF 值。
  4. 案件推荐:根据输入的关键词或者文章的 TF-IDF 值,计算数据的匹配度,进行推荐。

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