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What is a Webcrawler and where is it used?

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Web Crawler is a bot that downloads the content from the internet and indexes it. The main purpose of this bot is to learn about the different web pages on the internet. This kind of bots is mostly operated by search engines. By applying the search algorithms to the data collected by the web crawlers, search engines can provide the relevant links as a response for the request requested by the user. In this article, let’s discuss how the web crawler is implemented. 

Webcrawler is a very important application of the Breadth-First Search Algorithm. The idea is that the whole internet can be represented by a directed graph: 

  • with vertices -> Domains/ URLs/ Websites.
  • edges -> Connections.

Example:  

Approach: The idea behind the working of this algorithm is to parse the raw HTML of the website and look for other URL in the obtained data. If there is a URL, then add it to the queue and visit them in breadth-first search manner.  

Note: This code will not work on an online IDE due to proxy issues. Try to run on your local computer.

Java




// Java program to illustrate the WebCrawler
 
import java.io.BufferedReader;
import java.io.InputStreamReader;
import java.net.URL;
import java.util.HashSet;
import java.util.LinkedList;
import java.util.List;
import java.util.Queue;
import java.util.regex.Matcher;
import java.util.regex.Pattern;
 
// Class Contains the functions
// required for WebCrowler
class WebCrowler {
 
    // To store the URLs in the
    / /FIFO order required for BFS
    private Queue<String> queue;
 
    // To store visited URls
    private HashSet<String>
        discovered_websites;
 
    // Constructor for initializing the
    // required variables
    public WebCrowler()
    {
        this.queue
            = new LinkedList<>();
 
        this.discovered_websites
            = new HashSet<>();
    }
 
    // Function to start the BFS and
    // discover all URLs
    public void discover(String root)
    {
        // Storing the root URL to
        // initiate BFS.
        this.queue.add(root);
        this.discovered_websites.add(root);
 
        // It will loop until queue is empty
        while (!queue.isEmpty()) {
 
            // To store the URL present in
            // the front of the queue
            String v = queue.remove();
 
            // To store the raw HTML of
            // the website
            String raw = readUrl(v);
 
            // Regular expression for a URL
            String regex
                = "https://(\\w+\\.)*(\\w+)";
 
            // To store the pattern of the
            // URL formed by regex
            Pattern pattern
                = Pattern.compile(regex);
 
            // To extract all the URL that
            // matches the pattern in raw
            Matcher matcher
                = pattern.matcher(raw);
 
            // It will loop until all the URLs
            // in the current website get stored
            // in the queue
            while (matcher.find()) {
 
                // To store the next URL in raw
                String actual = matcher.group();
 
                // It will check whether this URL is
                // visited or not
                if (!discovered_websites
                         .contains(actual)) {
 
                    // If not visited it will add
                    // this URL in queue, print it
                    // and mark it as visited
                    discovered_websites
                        .add(actual);
                    System.out.println(
                        "Website found: "
                        + actual);
 
                    queue.add(actual);
                }
            }
        }
    }
 
    // Function to return the raw HTML
    // of the current website
    public String readUrl(String v)
    {
 
        // Initializing empty string
        String raw = "";
 
        // Use try-catch block to handle
        // any exceptions given by this code
        try {
            // Convert the string in URL
            URL url = new URL(v);
 
            // Read the HTML from website
            BufferedReader be
                = new BufferedReader(
                    new InputStreamReader(
                        url.openStream()));
 
            // To store the input
            // from the website
            String input = "";
 
            // Read the HTML line by line
            // and append it to raw
            while ((input
                    = br.readLine())
                   != null) {
                raw += input;
            }
 
            // Close BufferedReader
            br.close();
        }
 
        catch (Exception ex) {
            ex.printStackTrace();
        }
 
        return raw;
    }
}
 
// Driver code
public class Main {
 
    // Driver Code
    public static void main(String[] args)
    {
        // Creating Object of WebCrawler
        WebCrowler web_crowler
            = new WebCrowler();
 
        // Given URL
        String root
            = "https:// www.google.com";
 
        // Method call
        web_crowler.discover(root);
    }
}


Output: 

Website found: https://www.google.com
Website found: https://www.facebook.com
Website found: https://www.amazon.com
Website found: https://www.microsoft.com
Website found: https://www.apple.com

Problem caused by web crawler: Web crawlers could accidentally flood websites with requests to avoid this inefficiency web crawlers use politeness policies. To implement politeness policy web crawler takes help of two parameters:

  1. Freshness: As the content on webpages is constantly updated and modified web crawler needs to keep revisiting pages. For that freshness uses HTTP protocol to as HTTP has a special request type called HEAD which returns the information about the last updated date of webpage by which crawler can decide the freshness of a webpage. 
  2. Age: An age of a webpage is T days after it has been last crawled. On average webpage updating follow Poisson distribution and the older a page gets the more costs to crawl the web page so Age is more important factor for crawler than freshness.  

Applications: This kind of web crawler is used to acquire the important parameters of the web like: 

  1. What are the frequently visited websites?
  2. What are the websites that are important in the network as a whole?
  3. Useful Information on social networks: Facebook, Twitter… etc.
  4. Who is the most popular person in a group of people?
  5. Who is the most important software engineer in a company?

 



Last Updated : 03 Oct, 2022
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