Internet U.S. Army soldiers "surfing the Internet" at Forward Operating Base Yusifiyah, Iraq The Internet is a global system of interconnected computer networks that use the standard Internet protocol suite (TCP/IP) to link several billion devices worldwide. It is a network of networks[1] that consists of millions of private, public, academic, business, and government networks of local to global scope, linked by a broad array of electronic, wireless, and optical networking technologies. The Internet carries an extensive range of information resources and services, such as the inter-linked hypertext documents and applications of the World Wide Web (WWW), the infrastructure to support email, and peer-to-peer networks for file sharing and telephony. Most traditional communications media, including telephony and television, are being reshaped or redefined by the Internet, giving birth to new services such as voice over Internet Protocol (VoIP) and Internet Protocol television (IPTV). Terminology Users
Cluster analysis Grouping a set of objects by similarity Cluster analysis or clustering is the task of grouping a set of objects in such a way that objects in the same group (called a cluster) are more similar (in some specific sense defined by the analyst) to each other than to those in other groups (clusters). It is a main task of exploratory data analysis, and a common technique for statistical data analysis, used in many fields, including pattern recognition, image analysis, information retrieval, bioinformatics, data compression, computer graphics and machine learning. Besides the term clustering, there is a number of terms with similar meanings, including automatic classification, numerical taxonomy, botryology (from Greek: βότρυς 'grape'), typological analysis, and community detection. The notion of a "cluster" cannot be precisely defined, which is one of the reasons why there are so many clustering algorithms.[5] There is a common denominator: a group of data objects. [edit] Model-based clustering
Data mining Process of extracting and discovering patterns in large data sets Data mining is the process of extracting and discovering patterns in large data sets involving methods at the intersection of machine learning, statistics, and database systems.[1] Data mining is an interdisciplinary subfield of computer science and statistics with an overall goal of extracting information (with intelligent methods) from a data set and transforming the information into a comprehensible structure for further use.[1][2][3][4] Data mining is the analysis step of the "knowledge discovery in databases" process, or KDD.[5] Aside from the raw analysis step, it also involves database and data management aspects, data pre-processing, model and inference considerations, interestingness metrics, complexity considerations, post-processing of discovered structures, visualization, and online updating.[1] Etymology[edit] Background[edit] The manual extraction of patterns from data has occurred for centuries. Process[edit]
DBSCAN Density-based data clustering algorithm Density-based spatial clustering of applications with noise (DBSCAN) is a data clustering algorithm proposed by Martin Ester, Hans-Peter Kriegel, Jörg Sander and Xiaowei Xu in 1996.[1] It is a density-based clustering non-parametric algorithm: given a set of points in some space, it groups together points that are closely packed together (points with many nearby neighbors), marking as outliers points that lie alone in low-density regions (whose nearest neighbors are too far away). DBSCAN is one of the most common, and most commonly cited, clustering algorithms.[2] The popular follow-up HDBSCAN* was initially published by Ricardo J. History[edit] In 1972, Robert F. Preliminary[edit] Consider a set of points in some space to be clustered. A point p is a core point if at least minPts points are within distance ε of it (including p).A point q is directly reachable from p if point q is within distance ε from core point p. Algorithm[edit] where . Notes[edit]
Computer science Computer science deals with the theoretical foundations of information and computation, together with practical techniques for the implementation and application of these foundations History[edit] The earliest foundations of what would become computer science predate the invention of the modern digital computer. Machines for calculating fixed numerical tasks such as the abacus have existed since antiquity, aiding in computations such as multiplication and division. Further, algorithms for performing computations have existed since antiquity, even before sophisticated computing equipment were created. Blaise Pascal designed and constructed the first working mechanical calculator, Pascal's calculator, in 1642.[3] In 1673 Gottfried Leibniz demonstrated a digital mechanical calculator, called the 'Stepped Reckoner'.[4] He may be considered the first computer scientist and information theorist, for, among other reasons, documenting the binary number system. Contributions[edit] Philosophy[edit]
Home — TensorFlow Hypertext Markup Language Un article de Wikipédia, l'encyclopédie libre. L’Hypertext Markup Language, généralement abrégé HTML, est le format de données conçu pour représenter les pages web. C’est un langage de balisage permettant d’écrire de l’hypertexte, d’où son nom. Dénomination[modifier | modifier le code] L’anglais Hypertext Markup Language se traduit littéralement en langage de balisage d’hypertexte[1]. Le public non averti parle parfois de HTM au lieu de HTML, HTM étant l’extension de nom de fichier tronquée à trois lettres, une limitation qu’on trouve sur d’anciens systèmes d’exploitation de Microsoft. Évolution du langage[modifier | modifier le code] Durant la première moitié des années 1990, avant l’apparition des technologies web comme JavaScript, les feuilles de style en cascade et le Document Object Model, l’évolution de HTML a dicté l’évolution du World Wide Web. 1989-1992 : Origine[modifier | modifier le code] 1993 : Apports de NCSA Mosaic[modifier | modifier le code] [modifier | modifier le code]
Metasearch engine A metasearch engine is a search tool[1][2] that sends user requests to several other search engines and/or databases and aggregates the results into a single list or displays them according to their source. Metasearch engines enable users to enter search criteria once and access several search engines simultaneously. Metasearch engines operate on the premise that the Web is too large for any one search engine to index it all and that more comprehensive search results can be obtained by combining the results from several search engines. This also may save the user from having to use multiple search engines separately. The process of fusion also improves the search results.[3] The term "metasearch" is frequently used to classify a set of commercial search engines, see the list of Metasearch engine, but is also used to describe the paradigm of searching multiple data sources in real time. Operation[edit] architecture of a metasearch engine See also[edit] References[edit] External links[edit]
List of wikis This page contains a list of notable websites that use a wiki model. These websites will sometimes use different software in order to provide the best content management system for their users' needs, but they all share the same basic editing and viewing website model. §Table[edit] §See also[edit] §References[edit] §External links[edit] Wiki Type of website that visitors can edit A wiki ( WI-kee) is a form of online hypertext publication that is collaboratively edited and managed by its audience directly through a web browser. A typical wiki contains multiple pages that can either be edited by the public or limited to use within an organization for maintaining its internal knowledge base. Wikis are enabled by wiki software, otherwise known as wiki engines. There are hundreds of thousands of wikis in use, both public and private, including wikis functioning as knowledge management resources, note-taking tools, community websites, and intranets. The online encyclopedia project Wikipedia is the most popular wiki-based website, as well being one of the most popular websites on the entire internet, having been ranked consistently as such since at least 2007.[7] Wikipedia is not a single wiki but rather a collection of hundreds of wikis, with each one pertaining to a specific language. Characteristics Editing Source editing Searching
Metadata Metadata is "data about data".[1] There are two "metadata types;" structural metadata, about the design and specification of data structures or "data about the containers of data"; and descriptive metadata about individual instances of application data or the data content. The main purpose of metadata is to facilitate in the discovery of relevant information, more often classified as resource discovery. Metadata also helps organize electronic resources, provide digital identification, and helps support archiving and preservation of the resource. Metadata assists in resource discovery by "allowing resources to be found by relevant criteria, identifying resources, bringing similar resources together, distinguishing dissimilar resources, and giving location information." [2] Definition[edit] Metadata (metacontent) is defined as the data providing information about one or more aspects of the data, such as: Metadata is data. Libraries[edit] Photographs[edit] Video[edit] Web pages[edit] [edit] [edit]
Adobe Systems Adobe Systems Incorporated is an American multinational computer software company. The company is headquartered in San Jose, California, United States. Adobe has historically focused upon the creation of multimedia and creativity software products, with a more-recent foray towards rich Internet application software development. It is best known for the Portable Document Format (PDF) and Adobe Creative Suite, later Adobe Creative Cloud. Adobe was founded in February 1982[4] by John Warnock and Charles Geschke, who established the company after leaving Xerox PARC in order to develop and sell the PostScript page description language. As of 2015[update], Adobe Systems has about 13,500 employees,[3] about 40% of whom work in San Jose. §History[edit] Adobe's first products after PostScript were digital fonts, which they released in a proprietary format called Type 1. Adobe Systems entered NASDAQ in 1986. Adobe Systems Canada in Ottawa, Ontario (not far from archrival Corel). §Products[edit]