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顶会热词及其可视化

一、
（1） 项目名称：信息化领域热词分类分析及解释
（2） 功能设计：
数据采集：要求从定期自动从网络中爬取信息领域的相关热
词；
 数据清洗：对热词信息进行数据清洗，并采用自动分类技术
生成信息领域热词目录，；
热词解释：针对每个热词名词自动添加中文解释（参照百度
百科或维基百科）
热词引用：并对近期引用热词的文章或新闻进行标记，生成
超链接目录，用户可以点击访问；
 数据可视化展示：
① 用字符云或热词图进行可视化展示；
② 用关系图标识热词之间的紧密程度。
 
首先我爬取热词的地址是博客园：https://news.cnblogs.com/n/recommend
python代码：
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import requests
import re
import xlwt
url = 'https://news.cnblogs.com/n/recommend'
headers = {
    "user-agent": "Mozilla/5.0 (Windows NT 10.0; WOW64) AppleWebKit/537.36 (KHTML, like Gecko) Chrome/77.0.3865.90 Safari/537.36"
}
def get_page(url):
    try:
        response = requests.get(url, headers=headers)
        if response.status_code == 200:
            print('获取网页成功')
            print(response.encoding)
            return response.text
        else:
            print('获取网页失败')
    except Exception as e:
        print(e)
f = xlwt.Workbook(encoding='utf-8')
sheet01 = f.add_sheet(u'sheet1', cell_overwrite_ok=True)
sheet01.write(0, 0, '博客最热新闻')  # 第一行第一列
urls = ['https://news.cnblogs.com/n/recommend?page={}'.format(i * 1) for i in range(100)]
temp=0
num=0
for url in urls:
    print(url)
    page = get_page(url)
    items = re.findall('<h2 class="news_entry">.*?<a href=".*?" target="_blank">(.*?)</a>',page,re.S)
    print(len(items))
    print(items)
    for i in range(len(items)):
        sheet01.write(temp + i + 1, 0, items[i])
    temp += len(items)
    num+=1
    print("已打印完第"+str(num)+"页")
print("打印完！！！")
f.save('Hotword.xls')

　　爬取结果截图：

 

 然后继续在爬取结果里面进行筛选，选出100个出现频率最高的信息热词。

Python代码：

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import jieba
import pandas as pd
import re
from collections import Counter
 
if __name__ == '__main__':
    filehandle = open("Hotword.txt", "r", encoding='utf-8');
    mystr = filehandle.read()
    seg_list = jieba.cut(mystr)  # 默认是精确模式
    print(seg_list)
    # all_words = cut_words.split()
    # print(all_words)
    stopwords = {}.fromkeys([line.rstrip() for line in open(r'final.txt',encoding='UTF-8')])
    c = Counter()
    for x in seg_list:
        if x not in stopwords:
            if len(x) > 1 and x != '\r\n':
                c[x] += 1
 
    print('\n词频统计结果：')
    for (k, v) in c.most_common(100):  # 输出词频最高的前两个词
        print("%s:%d" % (k, v))
 
    # print(mystr)
    filehandle.close();
    # seg2 = jieba.cut("好好学学python，有用。", cut_all=False)
    # print("精确模式（也是默认模式）：", ' '.join(seg2))

　　里面的那个final.txt是将那些单词比如“我们”，“什么”，“中国”，“没有”，这些句子常出现的词语频率高但是跟信息没有关系的词语，我们将他们首先排除。

final.txt：

 

 这个txt有需要的，联系Q：893225523

运行结果：

 

 然后将他们存入txt，导入mysql。

之后我们继续进行爬取，爬取百度百科每个热词的解释。

Python源代码:

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import requests
import re
import xlwt
import linecache
url = 'https://baike.baidu.com/'
headers = {
    "user-agent": "Mozilla/5.0 (Windows NT 10.0; WOW64) AppleWebKit/537.36 (KHTML, like Gecko) Chrome/77.0.3865.90 Safari/537.36"
}
def get_page(url):
    try:
        response = requests.get(url, headers=headers)
        response.encoding = 'utf-8'
        if response.status_code == 200:
            print('获取网页成功')
            #print(response.encoding)
            return response.text
        else:
            print('获取网页失败')
    except Exception as e:
        print(e)
f = xlwt.Workbook(encoding='utf-8')
sheet01 = f.add_sheet(u'sheet1', cell_overwrite_ok=True)
sheet01.write(0, 0, '热词')  # 第一行第一列
sheet01.write(0, 1, '热词解释')  # 第一行第二列
sheet01.write(0, 2, '网址')  # 第一行第三列
fopen = open('C:\\Users\\hp\\Desktop\\final_hotword2.txt', 'r',encoding='utf-8')
lines = fopen.readlines()
urls = ['https://baike.baidu.com/item/{}'.format(line) for line in lines]
i=0
for url in urls:
     print(url.replace("\n", ""))
     page = get_page(url.replace("\n", ""))
     items = re.findall('<meta name="description" content="(.*?)">',page,re.S)
     print(items)
     if len(items)>0:
            sheet01.write(i + 1, 0,linecache.getline("C:\\Users\\hp\\Desktop\\final_hotword2.txt", i+1).strip())
            sheet01.write(i + 1, 1,items[0])
            sheet01.write(i + 1, 2,url.replace("\n", ""))
            i+= 1
     print("总爬取完毕数量：" + str(i))
print("打印完！！！")
f.save('hotword_explain.xls')

　　刚开始我爬取的时候，在确定正则表达式正确的情况下，爬取结果一直都是乱码。然后加上 response.encoding = 'utf-8'，就OK了。

爬取结果：

 

 将其存入数据库。

之后打开eclipse，用javaweb实现数据可视化和热词目录。

jsp源代码：

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<%@ include file="left.jsp"%>
<%@ page language="java" contentType="text/html; charset=UTF-8"
    pageEncoding="UTF-8"%>
<!DOCTYPE html PUBLIC "-//W3C//DTD HTML 4.01 Transitional//EN" "http://www.w3.org/TR/html4/loose.dtd">
<html>
<head>
<meta http-equiv="Content-Type" content="text/html; charset=UTF-8">
<title>Insert title here</title>
<script src="https://cdn.staticfile.org/echarts/4.3.0/echarts.min.js"></script>
<script src="js/jquery-1.5.1.js"></script>
<script src="js/echarts-all.js"></script>
</head>
<body>
<div style="position:absolute;left:400px;top:20px;">
<div id="main" style="width: 1000px;height:400px;"></div>
</div>
</body>
<script type="text/javascript">
var myChart = echarts.init(document.getElementById('main'));
var statisticsData =[];
myChart.showLoading();
$.ajax({
   type : "post",
   async : true, //异步请求（同步请求将会锁住浏览器，其他操作须等请求完成才可执行）
   url : "servlet?method=find", //请求发送到Servlet
   data : {},
   dataType : "json", //返回数据形式为json
   //7.请求成功后接收数据name+num两组数据
   success : function(result) {
       //result为服务器返回的json对象
       if (result) {
           //8.取出数据存入数组
           for (var i = 0; i <result.length; i++) {
            var statisticsObj = {name:'',value:''};   //因为ECharts里边需要的的数据格式是这样的
               statisticsObj.name =result[i].hotwords;
               statisticsObj.value =result[i].num;
               //alert( statisticsObj.name);
               //alert(statisticsObj.value);
                statisticsData.push(statisticsObj);
           }
           //alert(statisticsData);
           //把拿到的异步数据push进我自己建的数组里
           myChart.hideLoading();
           //9.覆盖操作-根据数据加载数据图表
           var z1_option = {
                    title : {
                    text:'热词图'
                    },
                    series: [{
                    type: 'wordCloud',
                    gridSize: 20,
                    sizeRange: [12, 50],
                    rotationRange: [-90, 90],
                    shape: 'pentagon',
                    textStyle: {
                    normal: {
                    color: function() {
                    return 'rgb(' + [
                    Math.round(Math.random() * 160),
                    Math.round(Math.random() * 160),
                    Math.round(Math.random() * 160)
                    ].join(',') + ')';
                    }
                    },
                    emphasis: {
                    shadowBlur: 10,
                    shadowColor: '#333'
                    }
                    },
                    data: statisticsData
                    }]
                    };
            myChart.setOption(z1_option, true);
       }
   },
})
</script>
</html>

　　dao层代码：

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package com.hotwords.dao;
 
import java.sql.Connection;
import java.sql.DriverManager;
import java.sql.ResultSet;
import java.sql.Statement;
import java.util.ArrayList;
import java.util.List;
 
import com.hotwords.entity.entity;
 
public class dao {
    public List<entity> list1(){
        List<entity> list =new ArrayList<entity>();
        try {
            // 加载数据库驱动，注册到驱动管理器
            Class.forName("com.mysql.jdbc.Driver");
            // 数据库连接字符串
            String url = "jdbc:mysql://localhost:3306/xinwen?useUnicode=true&characterEncoding=utf-8";
            // 数据库用户名
            String username = "root";
            // 数据库密码
            String password = "893225523";
            // 创建Connection连接
            Connection conn = DriverManager.getConnection(url, username,
                    password);
            // 添加图书信息的SQL语句
            String sql = "select * from final_hotword";
            // 获取Statement
            Statement statement = conn.createStatement();
   
            ResultSet resultSet = statement.executeQuery(sql);
   
            while (resultSet.next()) {
                entity book = new entity();
                book.setHotwords(resultSet.getString("热词"));
                book.setNum(resultSet.getString("次数"));
                list.add(book);
            }
            resultSet.close();
            statement.close();
            conn.close();
}catch (Exception e) {
    e.printStackTrace();
}
        return list;
    }
    //
    public List<entity> list2(){
        List<entity> list =new ArrayList<entity>();
        try {
            // 加载数据库驱动，注册到驱动管理器
            Class.forName("com.mysql.jdbc.Driver");
            // 数据库连接字符串
            String url = "jdbc:mysql://localhost:3306/xinwen?useUnicode=true&characterEncoding=utf-8";
            // 数据库用户名
            String username = "root";
            // 数据库密码
            String password = "893225523";
            // 创建Connection连接
            Connection conn = DriverManager.getConnection(url, username,
                    password);
            // 添加图书信息的SQL语句
            String sql = "select * from website";
            // 获取Statement
            Statement statement = conn.createStatement();
   
            ResultSet resultSet = statement.executeQuery(sql);
   
            while (resultSet.next()) {
                entity book = new entity();
                book.setHotwords(resultSet.getString("热词"));
                book.setExplain(resultSet.getString("解释"));
                book.setWebsite(resultSet.getString("网址"));
                list.add(book);
            }
            resultSet.close();
            statement.close();
            conn.close();
}catch (Exception e) {
    e.printStackTrace();
}
        return list;
    }
}

　　servlet层：

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package com.hotwords.servlet;
 
import java.io.IOException;
import java.util.ArrayList;
import java.util.List;
 
import javax.servlet.ServletException;
import javax.servlet.annotation.WebServlet;
import javax.servlet.http.HttpServlet;
import javax.servlet.http.HttpServletRequest;
import javax.servlet.http.HttpServletResponse;
import javax.servlet.http.HttpSession;
 
import com.hotwords.dao.dao;
import com.hotwords.entity.entity;
import com.google.gson.Gson;
 
/**
 * Servlet implementation class servlet
 */
@WebServlet("/servlet")
public class servlet extends HttpServlet {
    private static final long serialVersionUID = 1L;
    dao dao1=new dao();
 /**
  * @see HttpServlet#HttpServlet()
  */
 public servlet() {
     super();
     // TODO Auto-generated constructor stub
 }
 
 protected void service(HttpServletRequest request, HttpServletResponse response) throws ServletException, IOException {
        request.setCharacterEncoding("utf-8");
        String method=request.getParameter("method");
        if("find".equals(method))
        {
            find(request, response);
        }else if("find2".equals(method))
        {
            find2(request, response);
        }
 }
        private void find(HttpServletRequest request, HttpServletResponse response) throws IOException, ServletException {
            request.setCharacterEncoding("utf-8");
             List<entity> list =new ArrayList<entity>();
                HttpSession session=request.getSession();
                String buy_nbr=(String) session.getAttribute("userInfo");
                 entity book = new entity();
                List<entity> list2=dao1.list1();
                System.out.println(list2.size());
//                String buy_nbr=(String) session.getAttribute("userInfo");
//                System.out.println(buy_nbr);
                Gson gson2 = new Gson();
                String json = gson2.toJson(list2);
                System.out.println(json);
               // System.out.println(json);
               // System.out.println(json.parse);
                response.setContentType("text/html;charset=UTF-8");
                response.getWriter().write(json);
        }
        private void find2(HttpServletRequest request, HttpServletResponse response) throws IOException, ServletException {
            request.setCharacterEncoding("utf-8");
            request.setAttribute("list",dao1.list2());
            request.getRequestDispatcher("NewFile1.jsp").forward(request, response);
        }
}

　　项目结构：

 

 记得一定要加上 echars-all.js要不热词图不能显示。

运行结果：

 

 

 

 那么基本功能就完成了，但是那个导出word还没有实现。

posted on 2021-06-21 12:35  码出个世界  阅读(132)  评论(0)  编辑  收藏  举报