根据CVPR论文生成热点词汇云图
1、用怕python 爬取论文到数据库中；
2、分析、查找关键词，对他排序；
3、生成热词汇云图；
一、python爬取数据
import requests
import pymysql
from bs4 import BeautifulSoup
db = pymysql.connect('127.0.0.1',
port=3306,
user='root',
password='123',
db='mytest',
charset='utf8')
cursor = db.cursor()
headers={
"User-Agent":"Mozilla/5.0 (Windows NT 10.0; WOW64) AppleWebKit/537.36 (KHTML, like Gecko) Chrome/74.0.3729.169 Safari/537.36"
}
url="http://openaccess.thecvf.com/CVPR2019.py"
html=requests.get(url)
soup=BeautifulSoup(html.content,'html.parser')
soup.a.contents=='pdf'
pdfs=soup.findAll(name="a",text="pdf")
lis = []
jianjie=""
for i,pdf in enumerate(pdfs):
pdf_name=pdf["href"].split('/')[-1]
name=pdf_name.split('.')[0].replace("_CVPR_2019_paper","")
link="http://openaccess.thecvf.com/content_CVPR_2019/html/"+name+"_CVPR_2019_paper.html"
url1=link
html1 = requests.get(url1)
soup1 = BeautifulSoup(html1.content, 'html.parser')
weizhi = soup1.find('div', attrs={'id':'abstract'})
if weizhi:
jianjie =weizhi.get_text();
print("这是第"+str(i)+"条数据")
keyword = str(name).split('_')
keywords = ''
for k in range(len(keyword)):
if (k == 0):
keywords += keyword[k]
else:
keywords += ',' + keyword[k]
info = {}
info['title'] = name
info['link'] =link
info['abstract']=jianjie
info['keywords']=keywords
lis.append(info)
cursor = db.cursor()
for i in range(len(lis)):
cols = ", ".join('`{}`'.format(k) for k in lis[i].keys())
print(cols) # '`name`, `age`'
val_cols = ', '.join('%({})s'.format(k) for k in lis[i].keys())
print(val_cols) # '%(name)s, %(age)s'
sql = "insert into lunwen(%s) values(%s)"
res_sql = sql % (cols, val_cols)
print(res_sql)
cursor.execute(res_sql, lis[i]) # 将字典a传入
db.commit()
num=1
print(num)
print("成功")
二、分析、查找关键词
借助Map存储关键词， key为关键词，value为出现的次数。遍历到相同的关键词value值+1，然后根据value值排序。
dao层：
package dao;
import java.sql.Connection;
import java.sql.PreparedStatement;
import java.sql.ResultSet;
import java.sql.SQLException;
import java.sql.Statement;
import java.util.ArrayList;
import java.util.HashMap;
import java.util.LinkedHashMap;
import java.util.Map;
import java.util.stream.Collectors;
import Bean.copy.*;
import jdbc.Util;
import java.sql.Connection;
import java.sql.PreparedStatement;
import java.sql.ResultSet;
import java.sql.SQLException;
import java.sql.Statement;
import java.util.ArrayList;
import java.util.List;
import com.sun.xml.internal.ws.policy.privateutil.PolicyUtils.Collections;
public class Dao {
public static Map<String,Integer> getrc()
{
String sql="select * from lunwen";
Map<String, Integer>map= new HashMap<String, Integer>();
Map<String, Integer>results= new LinkedHashMap<String, Integer>();
Connection con=null;
Statement state=null;
ResultSet rs=null;
con=Util.getConn();
try {
state=con.createStatement();
rs=state.executeQuery(sql);
while(rs.next())
{
String keywords=rs.getString("keywords");
String[] split = keywords.split(",");
for(int i=0;i<split.length;i++)
{
if(map.get(split[i])==null)
{
map.put(split[i],0);
}
else
{
map.replace(split[i], map.get(split[i])+1);
}
}
}
} catch (SQLException e) {
// TODO Auto-generated catch block
e.printStackTrace();
}
Util.close(rs, state, con);
map.entrySet()
.stream()
.sorted((p1, p2) -> p2.getValue().compareTo(p1.getValue()))
.collect(Collectors.toList())
.forEach(ele -> results.put(ele.getKey(), ele.getValue()));
return results;
}
public List<Data> list(String keywords) { // 查询所有信息
List<Data> list = new ArrayList<Data>(); // 创建集合
Connection conn = Util.getConn();
String sql = "select * from lunwen where keywords like "+"'%"+keywords+"%'"; // SQL查询语句
try {
PreparedStatement pst = conn.prepareStatement(sql);
ResultSet rs = pst.executeQuery();
Data data = null;
while (rs.next()) {
String title = rs.getString("title");
String link = rs.getString("link");
String as= rs.getString("abstract");
data = new Data(title,link,as,keywords);
list.add(data);
}
rs.close(); // 关闭
pst.close(); // 关闭
} catch (SQLException e1) {
e1.printStackTrace(); // 抛出异常
}
return list; // 返回一个集合
}
}
servlet层：
package servlet;
import java.io.IOException;
import java.util.Map;
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 dao.Dao;
import net.sf.json.JSONArray;
import net.sf.json.JSONObject;
@WebServlet("/RcServlet")
public class RcServlet extends HttpServlet {
private static final long serialVersionUID = 1L;
/**
* @see HttpServlet#HttpServlet()
*/
public RcServlet() {
super();
// TODO Auto-generated constructor stub
}
/**
* @see HttpServlet#doGet(HttpServletRequest request, HttpServletResponse response)
*/
protected void doGet(HttpServletRequest request, HttpServletResponse response) throws ServletException, IOException {
this.doPost(request, response);
}
/**
* @see HttpServlet#doPost(HttpServletRequest request, HttpServletResponse response)
*/
protected void doPost(HttpServletRequest request, HttpServletResponse response) throws ServletException, IOException {
request.setCharacterEncoding("utf-8");
Map<String, Integer>sortMap=Dao.getrc();
JSONArray json =new JSONArray();
int k=0;
for (Map.Entry<String, Integer> entry : sortMap.entrySet())
{
JSONObject ob=new JSONObject();
ob.put("name", entry.getKey());
ob.put("value", entry.getValue());
if(!(entry.getKey().equals("for")||entry.getKey().equals("and")||entry.getKey().equals("With")||entry.getKey().equals("of")||entry.getKey().equals("in")||entry.getKey().equals("From")||entry.getKey().equals("A")||entry.getKey().equals("to")||entry.getKey().equals("a")||entry.getKey().equals("the")||entry.getKey().equals("by")))
{
json.add(ob);
k++;
}
if(k==10)
break;
}
System.out.println(json.toString());
response.getWriter().write(json.toString());
}
}
三、生成热词汇云图
<%@ page language="java" contentType="text/html; charset=UTF-8"
pageEncoding="UTF-8"%>
<%@taglib uri="http://java.sun.com/jsp/jstl/core" prefix="c"%>
<%request.setCharacterEncoding("utf-8");
response.setCharacterEncoding("utf-8");%>
<!DOCTYPE html>
<html>
<head>
<meta charset="ISO-8859-1">
<title>热词云</title>
</head>
<meta charset="UTF-8">
<link type="text/css" rel="stylesheet" href="css/style.css">
<script src="js/jquery-3.4.1.min.js"></script>
<script src="js/echarts.min.js"></script>
<script src="js/echarts-cloud.js"></script>
<style>
#main{
30%;
height: 500px;
border:1px solid #ddd;
float:right;
}
#table{
overflow-x: auto;
overflow-y: auto;
70%;
height: 500px;
float:left;
margin-top:100dp;
padding-top:100dp;
}
</style>
</head>
<body >
<br>
<h1>热词云</h1>
<br>
<br>
<br>
<div id="table">
<table id='gradient-style' >
<tr>
<th align="center">论文连接</th>
</tr>
<c:forEach var="item" items="${list}">
<tr>
<td><a href="${item.link}">${item.title}</a></td>
</tr>
</c:forEach>
</table>
</div>
<div id="main">
</div>
<script type="text/javascript">
var dt;
$.ajax({
url : "RcServlet",
async : true,
type : "POST",
data : {
},
dataType : "json",
success : function(data) {
dt = data;
var mydata = new Array(0);
for (var i = 0; i < dt.length; i++) {
var d = {};
d["name"] = dt[i].name;
d["value"] = dt[i].value;
mydata.push(d);
}
var myChart = echarts.init(document.getElementById('main'));
//设置点击效果
myChart.setOption({
title: {
text: ''
},
tooltip: {},
series: [{
type : 'wordCloud', //类型为字符云
shape:'smooth', //平滑
gridSize : 8, //网格尺寸
size : ['50%','50%'],
//sizeRange : [ 50, 100 ],
rotationRange : [-45, 0, 45, 90], //旋转范围
textStyle : {
normal : {
fontFamily:'微软雅黑',
color: function() {
return 'rgb(' +
Math.round(Math.random() * 255) +
', ' + Math.round(Math.random() * 255) +
', ' + Math.round(Math.random() * 255) + ')'
}
},
emphasis : {
shadowBlur : 5, //阴影距离
shadowColor : '#333' //阴影颜色
}
},
left: 'center',
top: 'center',
right: null,
bottom: null,
'100%',
height:'100%',
data:mydata
}]
});
myChart.on('click', function (params) {
var url = "ClickServlet?keywords=" + params.name;
window.location.href = url;
});
alert("成功！");
},
error : function() {
alert("请求失败");
},
});
</script>
</body>
</html>
生成图：
