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Web scraping

Method of extracting data from websites

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Through Website, World Wide Web and HTTP

Scraping a web page involves fetching it and then extracting data from it. Fetching is the downloading of a page (which a browser does when a user views a page). Therefore, web crawling is a main component of web scraping, to fetch pages for later processing. Having fetched, extraction can take place. The content of a page may be parsed, searched and reformatted, and its data copied into a spreadsheet or loaded into a database. Web scrapers typically take something out of a page, to make use of it for another purpose somewhere else. An example would be finding and copying names and telephone numbers, companies and their URLs, or e-mail addresses to a list (contact scraping). Another example is collecting competitors product prices for marketing purposes, which can involve gathering large-scale pricing datasets from e-commerce websites and analysing them using data science techniques such as trend analysis, predictive modelling, and competitive benchmarking.

Contact scraping is a type of web scraping that is used as a component of applications used for web indexing, web mining and data mining, online price change monitoring and price comparison, product review scraping (to watch the competition), gathering real estate listings, weather data monitoring, website change detection, research, tracking online presence and reputation, web mashup, and web data integration.

Web pages are built using text-based markup languages (HTML and XHTML), and frequently contain a wealth of data in text form. However, most web pages are designed for human end-users and not for ease of automated use. As a result, specialized tools and software have been developed to facilitate the scraping of web pages. Web scraping applications include market research, price comparison, content monitoring and artificial intelligence. Businesses rely on web scraping services to efficiently gather and use this data.

There are methods that some websites use to prevent web scraping, such as detecting and disallowing bots from crawling (viewing) their pages. In response, web scraping systems use techniques involving DOM parsing, computer vision and natural language processing to simulate human-like browsing to enable gathering web page content for offline parsing.

History

After the birth of the World Wide Web in 1989, the first web robot, World Wide Web Wanderer, was created in June 1993, which was intended only to measure the size of the web.

In December 1993, the first crawler-based web search engine, JumpStation, was launched. As there were fewer websites available on the web, search engines at that time used to rely on human administrators to collect and format links. In comparison, Jump Station was the first WWW search engine to rely on a web robot.

In 2000, the first Web API and API crawler were created. In 2000, Salesforce and eBay launched their own API, with which programmers could access and download some of the data available to the public. Since then, many websites offer web APIs for people to access their public database.

In the mid 2020s, the web scrapers of LLM vendors have become a major source of web traffic, using distributed web crawling to avoid detection.

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