What is Web Scraping?

Web scraping, is knowledge scraping used for extracting knowledge from websites. Web scraping computer code could access the globe Wide internet directly mistreatment the machine-readable text Transfer Protocol, or through an online browser. While internet scraping will be done manually by a computer code user, the term usually refers to machine-driven processes enforced employing a larva or internet crawler. It is a variety of repetition, during which specific knowledge is gathered and traced from the online, usually into a central native information or program, for later retrieval or analysis.

How did it start?

After the birth of World Wide internet in 1989, the primary internet golem – World Wide internet Wanderer was created in 1993,June, that was meant solely to live the scale of the web.
In 1993,December, the First crawler-based web search engine – Jump Station.

As there have been not such a lot of websites on the market on the online, search engines at that time used to rely on their human website administrators to collect and edit the links into a particular format.

Jump Station brought a new leap. It is the primary WWW program that depends on an online golem.
In 2000, the primary internet API and API crawler came.

API stands for Application Programming Interface. It is associate degree interface that creates it a lot of easier to develop a program by providing the building blocks.

In 2000, Salesforce and eBay launched their own API, with which programmers were enabled to access and download some of the data available to the public.

Since then, several internet sites provide web Apis for folks to access their public information.
In 2004, Beautiful Soup was released. It is a library designed for Python. As not all websites provide Apis, programmers were still working on developing an approach that could facilitate web scraping.

With straightforward commands, Beautiful Soup could parse content from within the HTML container. It is thought of the foremost refined and advanced library for internet scraping, and additionally one in all the foremost common and widespread approaches these days.

Techniques for Web Scraping?

Human copy-and-paste

Sometimes even the best web-scraping technology cannot replace a human’s manual examination and copy-and-paste, and sometimes this may be the only workable solution when the websites for scraping explicitly set up barriers to prevent machine automation.

Text pattern matching

A simple yet powerful approach to extract information from web pages can be based on the UNIX grep command or regular expressiom matching facilities of programming languages (for instance Perl or Python).

HTTP programming

Static and dynamic web pages can be retrieved by posting HTTP requests to the remote web server using socket programming.

HTML parsing

Many websites have large collections of pages generated dynamically from an underlying structured source like a database.

Data of the same category are typically encoded into similar pages by a common script or template. In data mining, a program that detects such templates in a particular information source, extracts its content and translates it into a relational form, is called a wrapper.

Wrapper generation algorithms assume that input pages of a wrapper induction system conform to a common template and that they can be easily identified in terms of a URL common scheme.

Moreover, some semi-structured data query languages, such as XQuery and the HTQL, can be used to parse HTML pages and to retrieve and transform page content.

DOM parsing

By embedding a full-fledged web browser, such as the Internet Explorer or the Mozilla browser control, programs can retrieve the dynamic content generated by client-side scripts.

These browser controls also parse web pages into a DOM tree, based on which programs can retrieve parts of the pages.

Vertical aggregation

There are several companies that have developed vertical specific harvesting platforms.

These platforms create and monitor a multitude of “bots” for specific verticals with no “man in the loop” (no direct human involvement), and no work related to a specific target site.

The preparation involves establishing the knowledge base for the entire vertical and then the platform creates the bots automatically.

The platform’s robustness is measured by the quality of the information it retrieves (usually number of fields) and its scalability (how quick it can scale up to hundreds or thousands of sites).

This scalability is mostly used to target the Long Tail of sites that common aggregators find complicated or too labor-intensive to harvest content from.

Semantic annotation recognizing

The pages being scraped may embrace metadata or semantic markups and annotations, which can be used to locate specific data snippets.

If the annotations are embedded in the pages, as Micro-format does, this technique can be viewed as a special case of DOM parsing.

In another case, the annotations, organized into a semantic layer, are stored and managed separately from the web pages, so the scrapers can retrieve data schema and instructions from this layer before scraping the pages.

Computer vision web-page analysis

There are efforts using machine learning and computer vision that attempt to identify and extract information from web pages by interpreting pages visually as a human being might.

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