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The first web crawler was made by Brian Pinkerton from the University of Washington. It was created and launched on 24th April 1994. The crawler was first designed to extract data from different websites and relay that data back into a search engine. It was also designed to visit and learn about new applications and collect data about new webpages from already visited pages.
The Early History:
The early web crawlers were designed to collect statistics about the search engine. In addition to this web crawlers also can perform accessibility checks on the websites that it crawls.
A web crawler program checks a website for keywords, phrases and the type of content that they are looking for, this whole process is called web crawling. After this process is completed the web crawler returns with the information to the search engine which in turn gives the users the data or the specific type of content that they are looking for.
Web crawlers can be called in different names such as Spiderbot, bots, automatic indexers and robots. Each time the user types a query the web crawler scans the relevant pages that are requested by the user.
How does Data Crawling work?
The spiderbot begins to crawl the website or a list of websites that it has visited during the previous crawl. Data Crawl recovers all the information that is required by the user. Google then generates an algorithm that makes the view for the user-friendly easy to see and understand.
What is the Difference between Data Crawling and Data Mining?
Data Crawling or Web Crawling is a process that is done to validate and check for content and extract data from various websites and relay the information back to the search engine. Data Mining is a process that comes after the Web Scrapping process.
How can Data Crawling help in Data Mining?
We have now established a clear understanding of what a web or data crawler is, and be sure that both Crawling as well as Data Mining work in tandem to provide accurate information to the user. Most of the data that is interpreted by the crawler is in an unstructured JSON, CSV or XML format.
So, Data Crawling or Web Crawling is the first step in the larger Data Mining process. The importance of this process comes to our attention during the data extraction process because at this time you will face errors, data in different languages and irregular markups. This is the reason why the encoding format is retained by the developer.
Uses of Data Crawling & Data Mining
1. Insurance Sector:
Companies that sell insurance can use data mining as the main resource to leverage the maximum potential of the same to gauge and monitor the user behavior such as spending power and saving patterns of their customers. This helps them identify the risk factors and deliver results according to their customer level analysis. This analysis will, in turn, help the companies to test and launch new products and can detect fraudulent claims.
2. The Healthcare Sector:
Data Crawling and Data Mining are used by doctors, research institutions and hospitals to help them manage medical data.
Mining reduces the time taken and increases the accuracy levels more than the manual analysis that was being practiced.
Crawling and Mining are used to understand many biological processes by analyzing a flood of biological and clinical data that is produced.
With a state-of-the-art Data Crawling and Data Mining system, it is easier to handle more challenging data and the problems that occur along with it.
3. Data Crawling and Data Mining in the US Presidential Election:
Data Crawling was used to identify 87million records which were scrapped from Facebook which became a huge advertising campaign.
Cambridge Analytica used a crawler that scrapped off records from Facebook and identified those records according to 3 different categories.
1. This consisted of the number of people going to vote for Trump.
2. This was filled with people who hadn’t made their minds up yet.
3. The number of people voting for the opposition.
This was used further to a level during the US Presidential Election.
4. Image Mining:
The process of going through a high volume of data and categorizing them according to the basis of their images.
5. Extraction of Data Through Images:
Companies are slowly starting to extract data through images extracting various data from the shopping comparison websites to understand user behavior and change the prices accordingly.
Conclusion:
Data Crawling and Data Mining are instrumental in defining the success of almost all businesses that rely on the process. From Retail to eCommerce, Healthcare to Entertainment, Data Crawling is used in every field possible and the demand seems to be increasing daily. Data Crawling and Mining are of high demand and companies want insightful data. This data is then used by them for Research and Development. We at PromptCloud provide high demand data at the request of the customer and provides custom web scraping solutions to clientele all over the world and gather data that they will convert into data-backed business solutions.
