A search engine is a software system that finds web pages that match a web search. They search the World Wide Web in a systematic way for particular information specified in a textual web search query. The search results are generally presented in a line of results, often referred to as search engine results pages (SERPs). The information may be a mix of hyperlinks to web pages, images, videos, infographics, articles, and other types of files. Some search engines also mine data available in databases or open directories. Unlike web directories and social bookmarking sites, which are maintained by human editors, search engines also maintain real-time information by running an algorithm on a web crawler. Any internet-based content that cannot be indexed and searched by a web search engine falls under the category of deep web.
A system for locating published information intended to overcome the ever-increasing difficulty of locating information in ever-growing centralized indices of scientific work was described in 1945 by Vannevar Bush, who wrote an article in The Atlantic Monthly titled "As We May Think" in which he envisioned libraries of research with connected annotations not unlike modern hyperlinks. Link analysis would eventually become a crucial component of search engines through algorithms such as Hyper Search and PageRank.
The first internet search engines predate the debut of the Web in December 1990: WHOIS user search dates back to 1982, and the Knowbot Information Service multi-network user search was first implemented in 1989. The first well documented search engine that searched content files, namely FTP files, was Archie, which debuted on 10 September 1990.
Prior to September 1993, the World Wide Web was entirely indexed by hand. There was a list of webservers edited by Tim Berners-Lee and hosted on the CERN webserver. One snapshot of the list in 1992 remains, but as more and more web servers went online the central list could no longer keep up. On the NCSA site, new servers were announced under the title "What's New!".
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Large commercial latency-sensitive services, such as web search, run on dedicated clusters provisioned for peak load to ensure responsiveness and tolerate data center outages. As a result, the average
Artificial intelligence has been an ultimate design goal since the inception of computers decades ago. Among the many attempts towards general artificial intelligence, modern machine learning successf
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Despite the high costs of acquisition and maintenance of modern data centers, machine resource utilization is often low. Servers running online interactive services are over-provisioned to support pea
Meta elements are tags used in HTML and XHTML documents to provide structured metadata about a Web page. They are part of a web page's head section. Multiple Meta elements with different attributes can be used on the same page. Meta elements can be used to specify page description, keywords and any other metadata not provided through the other head elements and attributes. The meta element has two uses: either to emulate the use of an HTTP response header field, or to embed additional metadata within the HTML document.
Web traffic is the data sent and received by visitors to a website. Since the mid-1990s, web traffic has been the largest portion of Internet traffic. Sites monitor the incoming and outgoing traffic to see which parts or pages of their site are popular and if there are any apparent trends, such as one specific page being viewed mostly by people in a particular country. There are many ways to monitor this traffic, and the gathered data is used to help structure sites, highlight security problems or indicate a potential lack of bandwidth.
Content-based image retrieval, also known as query by image content (QBIC) and content-based visual information retrieval (CBVIR), is the application of computer vision techniques to the problem, that is, the problem of searching for s in large databases (see this survey for a scientific overview of the CBIR field). Content-based image retrieval is opposed to traditional concept-based approaches (see ). "Content-based" means that the search analyzes the contents of the image rather than the metadata such as keywords, tags, or descriptions associated with the image.
Understanding the brain requires an integrated understanding of different scales of organisation of the brain. This Massive Open Online Course (MOOC) will take the you through the latest data, models
Understanding the brain requires an integrated understanding of different scales of organisation of the brain. This Massive Open Online Course (MOOC) will take the you through the latest data, models