question: How can search engines query search results in just a matter of seconds from all over the internet?
comment: Search engines use bots that constantly crawl web pages all over the Internet for content and keywords. This creates an index which is much smaller in size than the web pages themselves. What the search engine is actually searching is the index these crawler bots created this is quick because the engine and the index are closely connected. The engine will then provide you links to web pages it found where the content matches what you searched for.
passages: There are basically three types of search engines: Those that are powered by robots (called crawlers; ants or spiders) and those that are powered by human submissions; and those that are a hybrid of the two.
   Nowadays, mobile devices have been developed to a point that they can perform infinite functions from any place at any time, thanks to the internet and GPS connections. Touch screens, motion sensors and voice recognition are now featured on mobile devices called smartphones. All the features and functions make possible to can execute multimodal searches from any place of the world at any time.
  
  Section::::Introduction.:Search elements.
   A problem created by the rapid pace and huge volume of information created by real-time web technologies and practices is finding relevant information. One approach, known as real-time search, is the concept of searching for and finding information online as it is produced. Advancements in web search technology coupled with growing use of social media enable online activities to be queried as they occur. A traditional web search crawls and indexes web pages periodically, returning results based on relevance to the search query. Google Real-Time Search was available in Google Search until July 2011.
  
  Section::::See also.
  
  BULLET::::- Comet
   The most popular search tools for finding information on the Internet include Web search engines, meta search engines, Web directories, and specialty search services. A Web search engine uses software known as a Web crawler to follow the hyperlinks connecting the pages on the World Wide Web. The information on these Web pages is indexed and stored by the search engine. To access this information, a user enters keywords in a search form and the search engine queries its algorithms, which take into consideration the location and frequency of keywords on a Web page, along with the quality and number of external hyperlinks pointing at the Web page.
   Section::::Search engine categories.
  
  Section::::Search engine categories.:Web search engines.
  
  Search engines that are expressly designed for searching web pages, documents, and images were developed to facilitate searching through a large, nebulous blob of unstructured resources. They are engineered to follow a multi-stage process: crawling the infinite stockpile of pages and documents to skim the figurative foam from their contents, indexing the foam/buzzwords in a sort of semi-structured form (database or something), and at last, resolving user entries/queries to return mostly relevant results and links to those skimmed documents or pages from the inventory.
  
  Section::::Search engine categories.:Web search engines.:Crawl.
   Human-powered search engines rely on humans to submit information that is subsequently indexed and catalogued. Only information that is submitted is put into the index.
   As of 2019, active search engine crawlers include those of Google, Sogou, Baidu, Bing, Gigablast, Mojeek, DuckDuckGo and Yandex.
  
  Section::::Approach.
  
  A search engine maintains the following processes in near real time:
  
  BULLET::::1. Web crawling
  
  BULLET::::2. Indexing
  
  BULLET::::3. Searching
   Modern web search engines are highly intricate software systems that employ technology that has evolved over the years. There are a number of sub-categories of search engine software that are separately applicable to specific 'browsing' needs. These include web search engines (e.g. Google), database or structured data search engines (e.g. Dieselpoint), and mixed search engines or enterprise search. The more prevalent search engines, such as Google and Yahoo!, utilize hundreds of thousands computers to process trillions of web pages in order to return fairly well-aimed results. Due to this high volume of queries and text processing, the software is required to run in a highly dispersed environment with a high degree of superfluity.
   Sometimes, data searched contains both database content and web pages or documents. Search engine technology has developed to respond to both sets of requirements. Most mixed search engines are large Web search engines, like Google. They search both through structured and unstructured data sources. Take for example, the word ‘ball.’ In its simplest terms, it returns more than 40 variations on Wikipedia alone. Did you mean a ball, as in the social gathering/dance? A soccer ball? The ball of the foot? Pages and documents are crawled and indexed in a separate index. Databases are indexed also from various sources. Search results are then generated for users by querying these multiple indices in parallel and compounding the results according to “rules.”
   Section::::Web Search Engines.:The Lone Wanderer.
  
  The World Wide Web Wanderer, developed by Matthew Gray in 1993 was the first robot on the Web and was designed to track the Web's growth. Initially, the Wanderer counted only Web servers, but shortly after its introduction, it started to capture URLs as it went along. The database of captured URLs became the Wandex, the first web database.
   Beyond simple keyword lookups, search engines offer their own GUI- or command-driven operators and search parameters to refine the search results. These provide the necessary controls for the user engaged in the feedback loop users create by "filtering" and "weighting" while refining the search results, given the initial pages of the first search results.
   Typically when a user enters a query into a search engine it is a few keywords. The index already has the names of the sites containing the keywords, and these are instantly obtained from the index. The real processing load is in generating the web pages that are the search results list: Every page in the entire list must be weighted according to information in the indexes. Then the top search result item requires the lookup, reconstruction, and markup of the "snippets" showing the context of the keywords matched. These are only part of the processing each search results web page requires, and further pages (next to the top) require more of this post processing.
   Nowadays, existing multimodal search engines are not very complex, and some of them are in an experimental phase. Some of the more simple engines are Google Images  or Bing , web interfaces that use text and images as inputs to find images in the output.
   To provide a set of matching items that are sorted according to some criteria quickly, a search engine will typically collect metadata about the group of items under consideration beforehand through a process referred to as indexing. The index typically requires a smaller amount of computer storage, which is why some search engines only store the indexed information and not the full content of each item, and instead provide a method of navigating to the items in the search engine result page. Alternatively, the search engine may store a copy of each item in a cache so that users can see the state of the item at the time it was indexed or for archive purposes or to make repetitive processes work more efficiently and quickly.
   Another common element that algorithms analyze is the way that pages link to other pages in the Web. By analyzing how pages link to each other, an engine can both determine what a page is about (if the keywords of the linked pages are similar to the keywords on the original page) and whether that page is considered "important" and deserving of a boost in ranking. Just as the technology is becoming increasingly sophisticated to ignore keyword stuffing, it is also becoming more savvy to Web masters who build artificial links into their sites in order to build an artificial ranking.
   Section::::Web Search Engines.:Excite.
  
  Excite, initially called Architext, was started by six Stanford undergraduates in February 1993. Their idea was to use statistical analysis of word relationships in order to provide more efficient searches through the large amount of information on the Internet.
  
  Their project was fully funded by mid-1993. Once funding was secured. they released a version of their search software for webmasters to use on their own web sites. At the time, the software was called Architext, but it now goes by the name of Excite for Web Servers.
   The essential feature of the memex [is] the process of tying two items together... When the user is building a trail, he names it in his code book, and taps it out on his keyboard. Before him are the two items to be joined, projected onto adjacent viewing positions. At the bottom of each there are a number of blank code spaces, and a pointer is set to indicate one of these on each item. The user taps a single key, and the items are permanently joined... Thereafter, at any time, when one of these items is in view, the other can be instantly recalled merely by tapping a button below the corresponding code space.
   The Web is clearly a multilingual corpus. It is estimated that 71% of the pages (453 million out of 634 million Web pages indexed by the Excite engine) were written in English, followed by Japanese (6.8%), German (5.1%), French (1.8%), Chinese (1.5%), Spanish (1.1%), Italian (0.9%), and Swedish (0.7%).
  
  A test to find contiguous words like ‘deep breath’ revealed 868,631 Web pages containing the terms in AlltheWeb. The number found through the search engines are more than three times the counts generated by the British National Corpus, indicating the significant size of the English corpus available on the Web.
   Section::::Technologies.
   Section::::Web Search Engines.
  
  Section::::Web Search Engines.:Archie.
  
  The first web search engines was Archie, created in 1990 by Alan Emtage, a student at McGill University in Montreal. The author originally wanted to call the program "archives," but had to shorten it to comply with the Unix world standard of assigning programs and files short, cryptic names such as grep, cat, troff, sed, awk, perl, and so on.
   Webmasters and content providers began optimizing websites for search engines in the mid-1990s, as the first search engines were cataloging the early Web. Initially, all webmasters only needed to submit the address of a page, or URL, to the various engines which would send a "spider" to "crawl" that page, extract links to other pages from it, and return information found on the page to be indexed. The process involves a search engine spider downloading a page and storing it on the search engine's own server. A second program, known as an indexer, extracts information about the page, such as the words it contains, where they are located, and any weight for specific words, as well as all links the page contains. All of this information is then placed into a scheduler for crawling at a later date.
   In the case of a wholly textual search, the first step in classifying web pages is to find an ‘index item’ that might relate expressly to the ‘search term.’ In the past, search engines began with a small list of URLs as a so-called seed list, fetched the content, and parsed the links on those pages for relevant information, which subsequently provided new links. The process was highly cyclical and continued until enough pages were found for the searcher's use.
   Unlike literate humans, computers do not understand the structure of a natural language document and cannot automatically recognize words and sentences. To a computer, a document is only a sequence of bytes. Computers do not 'know' that a space character separates words in a document. Instead, humans must program the computer to identify what constitutes an individual or distinct word referred to as a token. Such a program is commonly called a tokenizer or parser or lexer. Many search engines, as well as other natural language processing software, incorporate specialized programs for parsing, such as YACC or Lex.
   Section::::Sections of "HEATH".:"a history of the search engine".
  
  Lin presents a short history of the search engine and modern-day web browsing, from Archie in 1990 to Google in 1996 to Bing in 2009. The ability to immediately search for information on any topic has started to be considered an art form. Concurrently, in the 23 years that search engines have been around, other web-related forms of searching and storing information have risen, such as news feeds, open directories, and online indexes full of endless information.
   Section::::Externally-provided search services.
  
  By outsourcing the search function to a specialist search company through software as a service, a more capable search function may be available to even the smallest organisation. Two methods are popular for this:
  
  Section::::Externally-provided search services.:Web-mediated search.
  
presuppositions: It should take a long time to search the internet because it is so large. Search engines query search results from all over the Internet.
corrections: Internet searches are actually searching a pre made index that is much smaller in size.  Search engines query search results from an index rather than from webpages that are all over the Internet.
raw_presuppositions: It should take a long time to search the internet because it is so large. Search engines query search results from all over the Internet.
raw_corrections: Internet searches are actually searching a pre made index that is much smaller in size.  Search engines query search results from an index rather than from webpages that are all over the Internet.