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[326] Wikipedia was also nominated for a "Best Practices" Webby award. | English |
In 2007, readers of brandchannel.com voted Wikipedia as the fourth-highest brand ranking, receiving 15 percent of the votes in answer to the question "Which brand had the most impact on our lives in 2006? | English |
"[327] In September 2008, Wikipedia received Quadriga A Mission of Enlightenment award of Werkstatt Deutschland along with Boris Tadić, Eckart Höfling, and Peter Gabriel. | English |
The award was presented to Wales by David Weinberger. | English |
[328] In 2015, Wikipedia was awarded both the annual Erasmus Prize, which recognizes exceptional contributions to culture, society or social sciences,[329] and the Spanish Princess of Asturias Award on International Cooperation. | English |
[330] Speaking at the Asturian Parliament in Oviedo, the city that hosts the awards ceremony, Jimmy Wales praised the work of the Asturian language Wikipedia users. | English |
[331] The night of the ceremony, members of the Wikimedia Foundation held a meeting with Wikipedians from all parts of Spain, including the local Asturian community. | English |
Many parodies target Wikipedia's openness and susceptibility to inserted inaccuracies, with characters vandalizing or modifying the online encyclopedia project's articles. | English |
Comedian Stephen Colbert has parodied or referenced Wikipedia on numerous episodes of his show The Colbert Report and coined the related term wikiality, meaning "together we can create a reality that we all agree on—the reality we just agreed on". | English |
[177] Another example can be found in "Wikipedia Celebrates 750 Years of American Independence", a July 2006 front-page article in The Onion,[332] as well as the 2010 The Onion article "'L.A. | English |
Law' Wikipedia Page Viewed 874 Times Today". | English |
[333] In an episode of the television comedy The Office U.S., which aired in April 2007, an incompetent office manager (Michael Scott) is shown relying on a hypothetical Wikipedia article for information on negotiation tactics to assist him in negotiating lesser pay for an employee. | English |
[334] Viewers of the show tried to add the episode's mention of the page as a section of the actual Wikipedia article on negotiation, but this effort was prevented by other users on the article's talk page. | English |
[335] "My Number One Doctor", a 2007 episode of the television show Scrubs, played on the perception that Wikipedia is an unreliable reference tool with a scene in which Perry Cox reacts to a patient who says that a Wikipedia article indicates that the raw food diet reverses the effects of bone cancer by retorting that the same editor who wrote that article also wrote the Battlestar Galactica episode guide. | English |
[336] In 2008, the comedic website CollegeHumor produced a video sketch named "Professor Wikipedia", in which the fictitious Professor Wikipedia instructs a class with a medley of unverifiable and occasionally absurd statements. | English |
[337] The Dilbert comic strip from May 8, 2009, features a character supporting an improbable claim by saying "Give me ten minutes and then check Wikipedia. | English |
"[338] In July 2009, BBC Radio 4 broadcast a comedy series called Bigipedia, which was set on a website which was a parody of Wikipedia. | English |
Some of the sketches were directly inspired by Wikipedia and its articles. | English |
[339] On August 23, 2013, the New Yorker website published a cartoon with this caption: "Dammit, Manning, have you considered the pronoun war that this is going to start on your Wikipedia page? | English |
"[340] The cartoon referred to Chelsea Elizabeth Manning (born Bradley Edward Manning), an American activist, politician, and former United States Army soldier and a trans woman. | English |
In December 2015, John Julius Norwich stated, in a letter published in The Times newspaper, that as a historian he resorted to Wikipedia "at least a dozen times a day", and had never yet caught it out. | English |
He described it as "a work of reference as useful as any in existence", with so wide a range that it is almost impossible to find a person, place, or thing that it has left uncovered and that he could never have written his last two books without it. | English |
[341][342] Wikipedia has also spawned several sister projects, which are also wikis run by the Wikimedia Foundation. | English |
These other Wikimedia projects include Wiktionary, a dictionary project launched in December 2002,[343] Wikiquote, a collection of quotations created a week after Wikimedia launched, Wikibooks, a collection of collaboratively written free textbooks and annotated texts, Wikimedia Commons, a site devoted to free-knowledge multimedia, Wikinews, for citizen journalism, and Wikiversity, a project for the creation of free learning materials and the provision of online learning activities. | English |
[344] Another sister project of Wikipedia, Wikispecies, is a catalogue of species. | English |
In 2012 Wikivoyage, an editable travel guide, and Wikidata, an editable knowledge base, launched. | English |
The most obvious economic effect of Wikipedia has been the death of commercial encyclopedias, especially the printed versions, e.g. | English |
Encyclopædia Britannica, which were unable to compete with a product that is essentially free. | English |
[345][346][347] Nicholas Carr wrote a 2005 essay, "The amorality of Web 2.0", that criticized websites with user-generated content, like Wikipedia, for possibly leading to professional (and, in his view, superior) content producers' going out of business, because "free trumps quality all the time". | English |
Carr wrote: "Implicit in the ecstatic visions of Web 2.0 is the hegemony of the amateur. | English |
I for one can't imagine anything more frightening. | English |
"[348] Others dispute the notion that Wikipedia, or similar efforts, will entirely displace traditional publications. | English |
For instance, Chris Anderson, the editor-in-chief of Wired Magazine, wrote in Nature that the "wisdom of crowds" approach of Wikipedia will not displace top scientific journals, with their rigorous peer review process. | English |
[349] There is also an ongoing debate about the influence of Wikipedia on the biography publishing business. | English |
"The worry is that, if you can get all that information from Wikipedia, what's left for biography?" | English |
said Kathryn Hughes, professor of life writing at the University of East Anglia and author of The Short Life and Long Times of Mrs Beeton and George Eliot: the Last Victorian. | English |
[350] Wikipedia has been widely used as a corpus for linguistic research in computational linguistics, information retrieval and natural language processing. | English |
In particular, it commonly serves as a target knowledge base for the entity linking problem, which is then called "wikification",[351] and to the related problem of word-sense disambiguation. | English |
[352] Methods similar to wikification can in turn be used to find "missing" links in Wikipedia. | English |
[353] In 2015, French researchers José Lages of the University of Franche-Comté in Besançon and Dima Shepelyansky of Paul Sabatier University in Toulouse published a global university ranking based on Wikipedia scholarly citations. | English |
[354][355][356] They used PageRank "followed by the number of appearances in the 24 different language editions of Wikipedia (descending order) and the century in which they were founded (ascending order)". | English |
[356] A 2017 MIT study suggests that words used on Wikipedia articles end up in scientific publications. | English |
[357][358] Studies related to Wikipedia have been using machine learning and artificial intelligence to support various operations. | English |
One of the most important areas—automatic detection of vandalism[359][360] and data quality assessment in Wikipedia. | English |
[361] Several interactive multimedia encyclopedias incorporating entries written by the public existed long before Wikipedia was founded. | English |
The first of these was the 1986 BBC Domesday Project, which included text (entered on BBC Micro computers) and photographs from more than a million contributors in the UK, and covered the geography, art, and culture of the UK. | English |
This was the first interactive multimedia encyclopedia (and was also the first major multimedia document connected through internal links), with the majority of articles being accessible through an interactive map of the UK. | English |
The user interface and part of the content of the Domesday Project were emulated on a website until 2008. | English |
[362] Several free-content, collaborative encyclopedias were created around the same period as Wikipedia (e.g. | English |
Everything2),[363] with many later being merged into the project (e.g. | English |
GNE). | English |
[364] One of the most successful early online encyclopedias incorporating entries by the public was h2g2, which was created by Douglas Adams in 1999. | English |
The h2g2 encyclopedia is relatively lighthearted, focusing on articles which are both witty and informative. | English |
Subsequent collaborative knowledge websites have drawn inspiration from Wikipedia. | English |
Some, such as Susning.nu, Enciclopedia Libre, Hudong, and Baidu Baike likewise employ no formal review process, although some like Conservapedia are not as open. | English |
Others use more traditional peer review, such as Encyclopedia of Life and the online wiki encyclopedias Scholarpedia and Citizendium. | English |
The latter was started by Sanger in an attempt to create a reliable alternative to Wikipedia. | English |
[365][366] Machine learning (ML) is the study of computer algorithms that improve automatically through experience. | English |
[1] It is seen as a part of artificial intelligence. | English |
Machine learning algorithms build a model based on sample data, known as "training data", in order to make predictions or decisions without being explicitly programmed to do so. | English |
[2] Machine learning algorithms are used in a wide variety of applications, such as email filtering and computer vision, where it is difficult or unfeasible to develop conventional algorithms to perform the needed tasks. | English |
A subset of machine learning is closely related to computational statistics, which focuses on making predictions using computers; but not all machine learning is statistical learning. | English |
The study of mathematical optimization delivers methods, theory and application domains to the field of machine learning. | English |
Data mining is a related field of study, focusing on exploratory data analysis through unsupervised learning. | English |
[4][5] In its application across business problems, machine learning is also referred to as predictive analytics. | English |
Machine learning involves computers discovering how they can perform tasks without being explicitly programmed to do so. | English |
It involves computers learning from data provided so that they carry out certain tasks. | English |
For simple tasks assigned to computers, it is possible to program algorithms telling the machine how to execute all steps required to solve the problem at hand; on the computer's part, no learning is needed. | English |
For more advanced tasks, it can be challenging for a human to manually create the needed algorithms. | English |
In practice, it can turn out to be more effective to help the machine develop its own algorithm, rather than having human programmers specify every needed step. | English |
[6] The discipline of machine learning employs various approaches to teach computers to accomplish tasks where no fully satisfactory algorithm is available. | English |
In cases where vast numbers of potential answers exist, one approach is to label some of the correct answers as valid. | English |
This can then be used as training data for the computer to improve the algorithm(s) it uses to determine correct answers. | English |
For example, to train a system for the task of digital character recognition, the MNIST dataset of handwritten digits has often been used. | English |
[6] Machine learning approaches are traditionally divided into three broad categories, depending on the nature of the "signal" or "feedback" available to the learning system: Other approaches have been developed which don't fit neatly into this three-fold categorisation, and sometimes more than one is used by the same machine learning system. | English |
For example topic modeling, dimensionality reduction or meta learning. | English |
[7] As of 2020, deep learning has become the dominant approach for much ongoing work in the field of machine learning. | English |
[6] The term machine learning was coined in 1959 by Arthur Samuel, an American IBMer and pioneer in the field of computer gaming and artificial intelligence. | English |
[8][9] A representative book of the machine learning research during the 1960s was the Nilsson's book on Learning Machines, dealing mostly with machine learning for pattern classification. | English |
[10] Interest related to pattern recognition continued into the 1970s, as described by Duda and Hart in 1973. | English |
[11] In 1981 a report was given on using teaching strategies so that a neural network learns to recognize 40 characters (26 letters, 10 digits, and 4 special symbols) from a computer terminal. | English |
[12] Tom M. Mitchell provided a widely quoted, more formal definition of the algorithms studied in the machine learning field: "A computer program is said to learn from experience E with respect to some class of tasks T and performance measure P if its performance at tasks in T, as measured by P, improves with experience E."[13] This definition of the tasks in which machine learning is concerned offers a fundamentally operational definition rather than defining the field in cognitive terms. | English |
This follows Alan Turing's proposal in his paper "Computing Machinery and Intelligence", in which the question "Can machines think?" | English |
is replaced with the question "Can machines do what we (as thinking entities) can do?". | English |
[14] Modern day machine learning has two objectives, one is to classify data based on models which have been developed, the other purpose is to make predictions for future outcomes based on these models. | English |
A hypothetical algorithm specific to classifying data may use computer vision of moles coupled with supervised learning in order to train it to classify the cancerous moles. | English |
Where as, a machine learning algorithm for stock trading may inform the trader of future potential predictions. | English |
[15] As a scientific endeavor, machine learning grew out of the quest for artificial intelligence. | English |
In the early days of AI as an academic discipline, some researchers were interested in having machines learn from data. | English |
They attempted to approach the problem with various symbolic methods, as well as what was then termed "neural networks"; these were mostly perceptrons and other models that were later found to be reinventions of the generalized linear models of statistics. | English |
[18] Probabilistic reasoning was also employed, especially in automated medical diagnosis. | English |
[19]:488 However, an increasing emphasis on the logical, knowledge-based approach caused a rift between AI and machine learning. | English |
Probabilistic systems were plagued by theoretical and practical problems of data acquisition and representation. | English |
[19]:488 By 1980, expert systems had come to dominate AI, and statistics was out of favor. | English |
[20] Work on symbolic/knowledge-based learning did continue within AI, leading to inductive logic programming, but the more statistical line of research was now outside the field of AI proper, in pattern recognition and information retrieval. | English |
[19]:708–710; 755 Neural networks research had been abandoned by AI and computer science around the same time. | English |
This line, too, was continued outside the AI/CS field, as "connectionism", by researchers from other disciplines including Hopfield, Rumelhart and Hinton. | English |
Their main success came in the mid-1980s with the reinvention of backpropagation. | English |
[19]:25 Machine learning (ML), reorganized as a separate field, started to flourish in the 1990s. | English |
The field changed its goal from achieving artificial intelligence to tackling solvable problems of a practical nature. | English |
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