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Web scraping is the process of automatically mining data or collecting information from the World Wide Web. It is a field with active developments sharing a common goal with the semantic web vision, an ambitious initiative that still requires breakthroughs in text processing, semantic understanding, artificial intelligence and human-computer interactions.
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This is a specific form of screen scraping or web scraping dedicated to search engines only. Most commonly larger search engine optimization (SEO) providers depend on regularly scraping keywords from search engines to monitor the competitive position of their customers' websites for relevant keywords or their indexing status.
A screen fragment and a screen-scraping interface (blue box with red arrow) to customize data capture process. Although the use of physical "dumb terminal" IBM 3270s is slowly diminishing, as more and more mainframe applications acquire Web interfaces, some Web applications merely continue to use the technique of screen scraping to capture old screens and transfer the data to modern front-ends.
Scrapy (/ ˈ s k r eɪ p aɪ / [2] SKRAY-peye) is a free and open-source web-crawling framework written in Python. Originally designed for web scraping, it can also be used to extract data using APIs or as a general-purpose web crawler. [3] It is currently maintained by Zyte (formerly Scrapinghub), a web-scraping development and services company.
A Google search result embedding content taken from a Wikipedia article. Search engines such as Google could be considered a type of scraper site. Search engines gather content from other websites, save it in their own databases, index it and present the scraped content to the search engines' own users.
A simple version of this problem in machine learning is known as overfitting, but the same problem can arise at different phases of the process and thus a train/test split—when applicable at all—may not be sufficient to prevent this from happening.
OpenCalais is an automated information extraction web service from Thomson Reuters (Free limited version) Machine Learning for Language Toolkit (Mallet) is a Java-based package for a variety of natural language processing tasks, including information extraction.