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Disambiguation
Word-sense disambiguation (WSD) is the process of identifying which sense of a word is meant in a sentence or other segment of context. In human language processing and cognition, it is usually subconscious/automatic but can often come to conscious attention when ambiguity impairs clarity of communication, given the pervasive polysemy in natural language. In computational linguistics, it is an open problem that affects other computer-related writing, such as discourse, improving relevance of search engines, anaphora resolution, coherence, and inference. Given that natural language requires reflection of neurological reality, as shaped by the abilities provided by the brain's neural networks, computer science has had a long-term challenge in developing the ability in computers to do natural language processing and machine learning. Many techniques have been researched, including dictionary-based methods that use the knowledge encoded in lexical resources, supervised machine lea ... [...More Info...] [...Related Items...] OR: [Wikipedia] [Google] [Baidu] |
Word Sense
In linguistics, a word sense is one of the meanings of a word. For example, a dictionary may have over 50 different senses of the word "play", each of these having a different meaning based on the context of the word's usage in a sentence, as follows: In each sentence different collocates of "play" signal its different meanings. People and computers, as they read words, must use a process called word-sense disambiguationR. Navigli''Word Sense Disambiguation: A Survey', ACM Computing Surveys, 41(2), 2009, pp. 1-69. to reconstruct the likely intended meaning of a word. This process uses context to narrow the possible senses down to the probable ones. The context includes such things as the ideas conveyed by adjacent words and nearby phrases, the known or probable purpose and register of the conversation or document, and the orientation (time and place) implied or expressed. The disambiguation is thus context-sensitive. Advanced semantic analysis has resulted in a s ... [...More Info...] [...Related Items...] OR: [Wikipedia] [Google] [Baidu] |
Yorick Wilks
Yorick Wilks FBCS (born 27 October 1939), a British computer scientist, is emeritus professor of artificial intelligence at the University of Sheffield, visiting professor of artificial intelligence at Gresham College (a post created especially for him), Former senior research fellow at the Oxford Internet Institute, senior scientist at the Florida Institute for Human and Machine Cognition, and a member of the Epiphany Philosophers. __TOC__ Biography Wilks was educated at Torquay Boys' Grammar School, followed by Pembroke College, Cambridge, where he read Philosophy, joined the Epiphany Philosophers and obtained his Doctor of Philosophy degree (1968) under Professor R. B. Braithwaite for the thesis 'Argument and Proof'; he was an early pioneer in meaning-based approaches to the understanding of natural language content by computers. His main early contribution in the 1970s was called "Preference Semantics" (Wilks, 1973; Wilks and Fass, 1992), an algorithmic method for as ... [...More Info...] [...Related Items...] OR: [Wikipedia] [Google] [Baidu] |
Biological Neural Network
A neural circuit is a population of neurons interconnected by synapses to carry out a specific function when activated. Neural circuits interconnect to one another to form large scale brain networks. Biological neural networks have inspired the design of artificial neural networks, but artificial neural networks are usually not strict copies of their biological counterparts. Early study Early treatments of neural networks can be found in Herbert Spencer's ''Principles of Psychology'', 3rd edition (1872), Theodor Meynert's ''Psychiatry'' (1884), William James' ''Principles of Psychology'' (1890), and Sigmund Freud's Project for a Scientific Psychology (composed 1895). The first rule of neuronal learning was described by Hebb in 1949, in the Hebbian theory. Thus, Hebbian pairing of pre-synaptic and post-synaptic activity can substantially alter the dynamic characteristics of the synaptic connection and therefore either facilitate or inhibit signal transmission. In 1959, th ... [...More Info...] [...Related Items...] OR: [Wikipedia] [Google] [Baidu] |
Yehoshua Bar-Hillel
Yehoshua Bar-Hillel ( he, יהושע בר-הלל; 8 September 1915, in Vienna – 25 September 1975, in Jerusalem) was an Israeli philosopher, mathematician, and linguist. He was a pioneer in the fields of machine translation and formal linguistics. Biography Born Oscar Westreich in Vienna, Austria-Hungary, he was raised in Berlin. In 1933 he emigrated to Palestine with the Bnei Akiva youth movement, and briefly joined the kibbutz Tirat Zvi before settling in Jerusalem and marrying Shulamith. During World War II, he served in the Jewish Brigade of the British Army. He fought with the Haganah during the 1948 Arab–Israeli War, losing an eye. Bar-Hillel received his PhD in Philosophy from the Hebrew University where he also studied mathematics under Abraham Fraenkel, with whom he eventually coauthored ''Foundations of Set Theory'' (1958, 1973). Bar-Hillel was a major disciple of Rudolf Carnap, whose ''Logical Syntax of Language'' much influenced him. He began a corresp ... [...More Info...] [...Related Items...] OR: [Wikipedia] [Google] [Baidu] |
Warren Weaver
Warren Weaver (July 17, 1894 – November 24, 1978) was an American scientist, mathematician, and science administrator. He is widely recognized as one of the pioneers of machine translation and as an important figure in creating support for science in the United States. Career Weaver received three degrees from the University of Wisconsin–Madison: a Bachelor of Science in 1916, a civil engineering degree in 1917, and a Ph.D. in 1921. He became an assistant professor of mathematics at Throop College (now California Institute of Technology). He served as a second lieutenant in the Air Service during World War I. After the war, he returned to teach mathematics at Wisconsin (1920–32). Weaver was director of the Division of Natural Sciences at the Rockefeller Foundation (1932–55), and was science consultant (1947–51), trustee (1954), and vice president (from 1958) at the Sloan-Kettering Institute for Cancer Research. His chief researches were in the problems of communi ... [...More Info...] [...Related Items...] OR: [Wikipedia] [Google] [Baidu] |
Training Set
In machine learning, a common task is the study and construction of algorithms that can learn from and make predictions on data. Such algorithms function by making data-driven predictions or decisions, through building a mathematical model from input data. These input data used to build the model are usually divided in multiple data sets. In particular, three data sets are commonly used in different stages of the creation of the model: training, validation and test sets. The model is initially fit on a training data set, which is a set of examples used to fit the parameters (e.g. weights of connections between neurons in artificial neural networks) of the model. The model (e.g. a naive Bayes classifier) is trained on the training data set using a supervised learning method, for example using optimization methods such as gradient descent or stochastic gradient descent. In practice, the training data set often consists of pairs of an input vector (or scalar) and the correspo ... [...More Info...] [...Related Items...] OR: [Wikipedia] [Google] [Baidu] |
Language
Language is a structured system of communication. The structure of a language is its grammar and the free components are its vocabulary. Languages are the primary means by which humans communicate, and may be conveyed through a variety of methods, including spoken, sign, and written language. Many languages, including the most widely-spoken ones, have writing systems that enable sounds or signs to be recorded for later reactivation. Human language is highly variable between cultures and across time. Human languages have the properties of productivity and displacement, and rely on social convention and learning. Estimates of the number of human languages in the world vary between and . Precise estimates depend on an arbitrary distinction (dichotomy) established between languages and dialects. Natural languages are spoken, signed, or both; however, any language can be encoded into secondary media using auditory, visual, or tactile stimuli – for example, writ ... [...More Info...] [...Related Items...] OR: [Wikipedia] [Google] [Baidu] |
Corpus Linguistics
Corpus linguistics is the study of a language as that language is expressed in its text corpus (plural ''corpora''), its body of "real world" text. Corpus linguistics proposes that a reliable analysis of a language is more feasible with corpora collected in the field—the natural context ("realia") of that language—with minimal experimental interference. The text-corpus method uses the body of texts written in any natural language to derive the set of abstract rules which govern that language. Those results can be used to explore the relationships between that subject language and other languages which have undergone a similar analysis. The first such corpora were manually derived from source texts, but now that work is automated. Corpora have not only been used for linguistics research, they have also been used to compile dictionaries (starting with '' The American Heritage Dictionary of the English Language'' in 1969) and grammar guides, such as '' A Comprehensive Grammar ... [...More Info...] [...Related Items...] OR: [Wikipedia] [Google] [Baidu] |
Dictionary
A dictionary is a listing of lexemes from the lexicon of one or more specific languages, often arranged alphabetically (or by radical and stroke for ideographic languages), which may include information on definitions, usage, etymologies, pronunciations, translation, etc.Webster's New World College Dictionary, Fourth Edition, 2002 It is a lexicographical reference that shows inter-relationships among the data. A broad distinction is made between general and specialized dictionaries. Specialized dictionaries include words in specialist fields, rather than a complete range of words in the language. Lexical items that describe concepts in specific fields are usually called terms instead of words, although there is no consensus whether lexicology and terminology are two different fields of study. In theory, general dictionaries are supposed to be semasiological, mapping word to definition, while specialized dictionaries are supposed to be onomasiological, first ident ... [...More Info...] [...Related Items...] OR: [Wikipedia] [Google] [Baidu] |
Homograph
A homograph (from the el, ὁμός, ''homós'', "same" and γράφω, ''gráphō'', "write") is a word that shares the same written form as another word but has a different meaning. However, some dictionaries insist that the words must also be pronounced differently, while the Oxford English Dictionary says that the words should also be of "different origin". In this vein, ''The Oxford Guide to Practical Lexicography'' lists various types of homographs, including those in which the words are discriminated by being in a different ''word class'', such as ''hit'', the verb ''to strike'', and ''hit'', the noun ''a blow''. If, when spoken, the meanings may be distinguished by different pronunciations, the words are also heteronyms. Words with the same writing ''and'' pronunciation (i.e. are both homographs and homophones) are considered homonyms. However, in a looser sense the term "homonym" may be applied to words with the same writing ''or'' pronunciation. Homograph disambiguat ... [...More Info...] [...Related Items...] OR: [Wikipedia] [Google] [Baidu] |
Algorithm
In mathematics and computer science, an algorithm () is a finite sequence of rigorous instructions, typically used to solve a class of specific problems or to perform a computation. Algorithms are used as specifications for performing calculations and data processing. More advanced algorithms can perform automated deductions (referred to as automated reasoning) and use mathematical and logical tests to divert the code execution through various routes (referred to as automated decision-making). Using human characteristics as descriptors of machines in metaphorical ways was already practiced by Alan Turing with terms such as "memory", "search" and "stimulus". In contrast, a heuristic is an approach to problem solving that may not be fully specified or may not guarantee correct or optimal results, especially in problem domains where there is no well-defined correct or optimal result. As an effective method, an algorithm can be expressed within a finite amount of space ... [...More Info...] [...Related Items...] OR: [Wikipedia] [Google] [Baidu] |
Classifier (mathematics)
In statistics, classification is the problem of identifying which of a set of categories (sub-populations) an observation (or observations) belongs to. Examples are assigning a given email to the "spam" or "non-spam" class, and assigning a diagnosis to a given patient based on observed characteristics of the patient (sex, blood pressure, presence or absence of certain symptoms, etc.). Often, the individual observations are analyzed into a set of quantifiable properties, known variously as explanatory variables or ''features''. These properties may variously be categorical (e.g. "A", "B", "AB" or "O", for blood type), ordinal (e.g. "large", "medium" or "small"), integer-valued (e.g. the number of occurrences of a particular word in an email) or real-valued (e.g. a measurement of blood pressure). Other classifiers work by comparing observations to previous observations by means of a similarity or distance function. An algorithm that implements classification, especially i ... [...More Info...] [...Related Items...] OR: [Wikipedia] [Google] [Baidu] |
