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Data-oriented Parsing
Data-oriented parsing (DOP, also data-oriented processing) is a probabilistic model in computational linguistics. DOP was conceived by Remko Scha in 1990 with the aim of developing a performance-oriented grammar framework. Unlike other probabilistic models, DOP takes into account all subtrees contained in a treebank rather than being restricted to, for example, 2-level subtrees (like PCFGs), thus allowing for more context-sensitive information. Several variants of DOP have been developed. The initial version developed by Rens Bod in 1992 was based on tree-substitution grammar,R. Bod, A computational model of language performance: Data oriented parsing, in: COLING 1992 Volume 3: The 15th International Conference on Computational Linguistics, https://www.aclweb.org/anthology/C92-3126.pdf while more recently, DOP has been combined with lexical-functional grammar (LFG). The resulting DOP-LFG finds an application in machine translation. Other work on learning and parameter estimation f ... [...More Info...] [...Related Items...] OR: [Wikipedia] [Google] [Baidu] |
Probabilistic Parsing
Grammar theory to model symbol strings originated from work in computational linguistics aiming to understand the structure of natural languages. Probabilistic context free grammars (PCFGs) have been applied in probabilistic modeling of RNA structures almost 40 years after they were introduced in computational linguistics. PCFGs extend context-free grammars similar to how hidden Markov models extend regular grammars. Each production is assigned a probability. The probability of a derivation (parse) is the product of the probabilities of the productions used in that derivation. These probabilities can be viewed as parameters of the model, and for large problems it is convenient to learn these parameters via machine learning. A probabilistic grammar's validity is constrained by context of its training dataset. PCFGs have application in areas as diverse as natural language processing to the study the structure of RNA molecules and design of programming languages. Designing efficient PC ... [...More Info...] [...Related Items...] OR: [Wikipedia] [Google] [Baidu] |
Conceptual Model
A conceptual model is a representation of a system. It consists of concepts used to help people knowledge, know, understanding, understand, or simulation, simulate a subject the model represents. In contrast, physical models are physical object such as a toy model that may be assembled and made to work like the object it represents. The term may refer to models that are formed after a wikt:concept#Noun, conceptualization or generalization process. Conceptual models are often abstractions of things in the real world, whether physical or social. Semantics, Semantic studies are relevant to various stages of process of concept formation, concept formation. Semantics is basically about concepts, the meaning that thinking beings give to various elements of their experience. Overview Models of concepts and models that are conceptual The term ''conceptual model'' is normal. It could mean "a model of concept" or it could mean "a model that is conceptual." A distinction can be made bet ... [...More Info...] [...Related Items...] OR: [Wikipedia] [Google] [Baidu] |
Computational Linguistics
Computational linguistics is an Interdisciplinarity, interdisciplinary field concerned with the computational modelling of natural language, as well as the study of appropriate computational approaches to linguistic questions. In general, computational linguistics draws upon linguistics, computer science, artificial intelligence, mathematics, logic, philosophy, cognitive science, cognitive psychology, psycholinguistics, anthropology and neuroscience, among others. Sub-fields and related areas Traditionally, computational linguistics emerged as an area of artificial intelligence performed by computer scientists who had specialized in the application of computers to the processing of a natural language. With the formation of the Association for Computational Linguistics (ACL) and the establishment of independent conference series, the field consolidated during the 1970s and 1980s. The Association for Computational Linguistics defines computational linguistics as: The term "comp ... [...More Info...] [...Related Items...] OR: [Wikipedia] [Google] [Baidu] |
Remko Scha
Remko Jan Hendrik Scha (15 September 1945 – 9 November 2015) was a professor of computational linguistics at the faculty of humanities and Institute for Logic, Language and Computation at the University of Amsterdam. He made important contributions to semantics, in particular the treatment of plurals, and to discourse analysis, and laid the foundations for what became an important research paradigm in computational linguistics, Data Oriented Parsing. He was a composer and performer of algorithmic art. He made recordings of music which has been generated by motor-driven machines. One notable example of this type of music is his 1982 album of electric guitar music, "Machine Guitars", on which all guitars are played by saber saws without human intervention, except for one in which the guitar is played by a rotating wire brush, again with no human intervention. Recorded in Eindhoven and New York, it was described by Byron Coley in ''The Wire'' 231 as one of "the definitive modern NYC g ... [...More Info...] [...Related Items...] OR: [Wikipedia] [Google] [Baidu] |
Linguistic Performance
The term linguistic performance was used by Noam Chomsky in 1960 to describe "the actual use of language in concrete situations". It is used to describe both the Language production, production, sometimes called '' parole'', as well as the comprehension of language. Performance is defined in opposition to "Linguistic competence, competence"; the latter describes the mental knowledge that a speaker or listener has of language. Part of the motivation for the distinction between performance and competence comes from speech errors: despite having a perfect understanding of the correct forms, a speaker of a language may unintentionally produce incorrect forms. This is because performance occurs in real situations, and so is subject to many non-linguistic influences. For example, distractions or memory limitations can affect lexical retrieval (Chomsky 1965:3), and give rise to errors in both production and perception. Such non-linguistic factors are completely independent of the act ... [...More Info...] [...Related Items...] OR: [Wikipedia] [Google] [Baidu] |
Treebank
In linguistics, a treebank is a parsed text corpus that annotates syntactic or semantic sentence structure. The construction of parsed corpora in the early 1990s revolutionized computational linguistics, which benefitted from large-scale empirical data. Etymology The term ''treebank'' was coined by linguist Geoffrey Leech in the 1980s, by analogy to other repositories such as a seedbank or bloodbank. This is because both syntactic and semantic structure are commonly represented compositionally as a tree structure. The term ''parsed corpus'' is often used interchangeably with the term treebank, with the emphasis on the primacy of sentences rather than trees. Construction Treebanks are often created on top of a corpus that has already been annotated with part-of-speech tags. In turn, treebanks are sometimes enhanced with semantic or other linguistic information. Treebanks can be created completely manually, where linguists annotate each sentence with syntactic structure, ... [...More Info...] [...Related Items...] OR: [Wikipedia] [Google] [Baidu] |
Stochastic Context-free Grammar
Grammar theory to model symbol strings originated from work in computational linguistics aiming to understand the structure of natural languages. Probabilistic context free grammars (PCFGs) have been applied in probabilistic modeling of RNA structures almost 40 years after they were introduced in computational linguistics. PCFGs extend context-free grammars similar to how hidden Markov models extend regular grammars. Each production is assigned a probability. The probability of a derivation (parse) is the product of the probabilities of the productions used in that derivation. These probabilities can be viewed as parameters of the model, and for large problems it is convenient to learn these parameters via machine learning. A probabilistic grammar's validity is constrained by context of its training dataset. PCFGs have application in areas as diverse as natural language processing to the study the structure of RNA molecules and design of programming languages. Designing efficient PC ... [...More Info...] [...Related Items...] OR: [Wikipedia] [Google] [Baidu] |
Machine Translation
Machine translation, sometimes referred to by the abbreviation MT (not to be confused with computer-aided translation, machine-aided human translation or interactive translation), is a sub-field of computational linguistics that investigates the use of software to translate text or speech from one language to another. On a basic level, MT performs mechanical substitution of words in one language for words in another, but that alone rarely produces a good translation because recognition of whole phrases and their closest counterparts in the target language is needed. Not all words in one language have equivalent words in another language, and many words have more than one meaning. Solving this problem with corpus statistical and neural techniques is a rapidly growing field that is leading to better translations, handling differences in linguistic typology, translation of idioms, and the isolation of anomalies. Current machine translation software often allows for customizat ... [...More Info...] [...Related Items...] OR: [Wikipedia] [Google] [Baidu] |
Parameter Estimation
Estimation theory is a branch of statistics that deals with estimating the values of parameters based on measured empirical data that has a random component. The parameters describe an underlying physical setting in such a way that their value affects the distribution of the measured data. An ''estimator'' attempts to approximate the unknown parameters using the measurements. In estimation theory, two approaches are generally considered: * The probabilistic approach (described in this article) assumes that the measured data is random with probability distribution dependent on the parameters of interest * The set-membership approach assumes that the measured data vector belongs to a set which depends on the parameter vector. Examples For example, it is desired to estimate the proportion of a population of voters who will vote for a particular candidate. That proportion is the parameter sought; the estimate is based on a small random sample of voters. Alternatively, it is ... [...More Info...] [...Related Items...] OR: [Wikipedia] [Google] [Baidu] |
Journal Of Experimental And Theoretical Artificial Intelligence
The ''Journal of Experimental and Theoretical Artificial Intelligence'' is a quarterly peer-reviewed scientific journal published by Taylor and Francis. It covers all aspects of artificial intelligence and was established in 1989. The editor-in-chief is Eric Dietrich (Binghamton University), the deputy editors-in-chief are Li Pheng Khoo (School of Mechanical & Aerospace Engineering, Nanyang Technological University) and Antonio Lieto (Department of Computer Science, University of Turin). Abstracting and indexing The journal is abstracted and indexed in: According to the ''Journal Citation Reports'', the journal has a 2020/2021 impact factor The impact factor (IF) or journal impact factor (JIF) of an academic journal is a scientometric index calculated by Clarivate that reflects the yearly mean number of citations of articles published in the last two years in a given journal, as i ... of 2.340 . References External links * {{Official website, 1=http://www.tandfonli ... [...More Info...] [...Related Items...] OR: [Wikipedia] [Google] [Baidu] |
