Historical linguisticsHistorical linguistics, also termed diachronic linguistics, is the scientific study of language change over time. Principal concerns of historical linguistics include: to describe and account for observed changes in particular languages to reconstruct the pre-history of languages and to determine their relatedness, grouping them into language families (comparative linguistics) to develop general theories about how and why language changes to describe the history of speech communities to study the history of words, i.
LinguisticsLinguistics is the scientific study of language. The modern-day scientific study of linguistics takes all aspects of language into account — i.e., the cognitive, the social, the cultural, the psychological, the environmental, the biological, the literary, the grammatical, the paleographical, and the structural. Linguistics is based on a theoretical as well as descriptive study of language, and is also interlinked with the applied fields of language studies and language learning, which entails the study of specific languages.
Theoretical linguisticsTheoretical linguistics is a term in linguistics which, like the related term general linguistics, can be understood in different ways. Both can be taken as a reference to theory of language, or the branch of linguistics which inquires into the nature of language and seeks to answer fundamental questions as to what language is, or what the common ground of all languages is. The goal of theoretical linguistics can also be the construction of a general theoretical framework for the description of language.
Cognitive linguisticsCognitive linguistics is an interdisciplinary branch of linguistics, combining knowledge and research from cognitive science, cognitive psychology, neuropsychology and linguistics. Models and theoretical accounts of cognitive linguistics are considered as psychologically real, and research in cognitive linguistics aims to help understand cognition in general and is seen as a road into the human mind. There has been scientific and terminological controversy around the label "cognitive linguistics"; there is no consensus on what specifically is meant with the term.
Complexity classIn computational complexity theory, a complexity class is a set of computational problems "of related resource-based complexity". The two most commonly analyzed resources are time and memory. In general, a complexity class is defined in terms of a type of computational problem, a model of computation, and a bounded resource like time or memory. In particular, most complexity classes consist of decision problems that are solvable with a Turing machine, and are differentiated by their time or space (memory) requirements.
Structural linguisticsStructural linguistics, or structuralism, in linguistics, denotes schools or theories in which language is conceived as a self-contained, self-regulating semiotic system whose elements are defined by their relationship to other elements within the system. It is derived from the work of Swiss linguist Ferdinand de Saussure and is part of the overall approach of structuralism. Saussure's Course in General Linguistics, published posthumously in 1916, stressed examining language as a dynamic system of interconnected units.
Diachrony and synchronySynchrony and diachrony are two complementary viewpoints in linguistic analysis. A synchronic approach (from συν- "together" and χρόνος "time") considers a language at a moment in time without taking its history into account. Synchronic linguistics aims at describing a language at a specific point of time, often the present. In contrast, a diachronic (from δια- "through" and χρόνος "time") approach, as in historical linguistics, considers the development and evolution of a language through history.
Computational complexity theoryIn theoretical computer science and mathematics, computational complexity theory focuses on classifying computational problems according to their resource usage, and relating these classes to each other. A computational problem is a task solved by a computer. A computation problem is solvable by mechanical application of mathematical steps, such as an algorithm. A problem is regarded as inherently difficult if its solution requires significant resources, whatever the algorithm used.
Origin of languageThe origin of language (spoken and signed, as well as language-related technological systems such as writing), its relationship with human evolution, and its consequences have been subjects of study for centuries. Scholars wishing to study the origins of language must draw inferences from evidence such as the fossil record, archaeological evidence, contemporary language diversity, studies of language acquisition, and comparisons between human language and systems of communication existing among animals (particularly other primates).
Parameterized complexityIn computer science, parameterized complexity is a branch of computational complexity theory that focuses on classifying computational problems according to their inherent difficulty with respect to multiple parameters of the input or output. The complexity of a problem is then measured as a function of those parameters. This allows the classification of NP-hard problems on a finer scale than in the classical setting, where the complexity of a problem is only measured as a function of the number of bits in the input.
P (complexity)In computational complexity theory, P, also known as PTIME or DTIME(nO(1)), is a fundamental complexity class. It contains all decision problems that can be solved by a deterministic Turing machine using a polynomial amount of computation time, or polynomial time. Cobham's thesis holds that P is the class of computational problems that are "efficiently solvable" or "tractable". This is inexact: in practice, some problems not known to be in P have practical solutions, and some that are in P do not, but this is a useful rule of thumb.
Space complexityThe space complexity of an algorithm or a computer program is the amount of memory space required to solve an instance of the computational problem as a function of characteristics of the input. It is the memory required by an algorithm until it executes completely. This includes the memory space used by its inputs, called input space, and any other (auxiliary) memory it uses during execution, which is called auxiliary space. Similar to time complexity, space complexity is often expressed asymptotically in big O notation, such as etc.
Entropy (information theory)In information theory, the entropy of a random variable is the average level of "information", "surprise", or "uncertainty" inherent to the variable's possible outcomes. Given a discrete random variable , which takes values in the alphabet and is distributed according to : where denotes the sum over the variable's possible values. The choice of base for , the logarithm, varies for different applications. Base 2 gives the unit of bits (or "shannons"), while base e gives "natural units" nat, and base 10 gives units of "dits", "bans", or "hartleys".
Kolmogorov complexityIn algorithmic information theory (a subfield of computer science and mathematics), the Kolmogorov complexity of an object, such as a piece of text, is the length of a shortest computer program (in a predetermined programming language) that produces the object as output. It is a measure of the computational resources needed to specify the object, and is also known as algorithmic complexity, Solomonoff–Kolmogorov–Chaitin complexity, program-size complexity, descriptive complexity, or algorithmic entropy.
GenevaGeneva (dʒəˈniːvə ; Genève ʒənɛv) is the second-most populous city in Switzerland (after Zürich) and the most populous city of Romandy, the French-speaking part of Switzerland. Situated in the south west of the country, where the Rhône exits Lake Geneva, it is the capital of the Republic and Canton of Geneva, and a center for international diplomacy. The city of Geneva (ville de Genève) had a population of 203,951 in 2020 (Jan. estimate) within its small municipal territory of , but the Canton of Geneva (the city and its closest Swiss suburbs and exurbs) had a population of 504,128 (Jan.
Computational linguisticsComputational linguistics has since 2020s became a near-synonym of either natural language processing or language technology, with deep learning approaches, such as large language models, overperforming the specific approaches previously used in the field. The field overlapped with artificial intelligence since the efforts in the United States in the 1950s to use computers to automatically translate texts from foreign languages, particularly Russian scientific journals, into English.
Rényi entropyIn information theory, the Rényi entropy is a quantity that generalizes various notions of entropy, including Hartley entropy, Shannon entropy, collision entropy, and min-entropy. The Rényi entropy is named after Alfréd Rényi, who looked for the most general way to quantify information while preserving additivity for independent events. In the context of fractal dimension estimation, the Rényi entropy forms the basis of the concept of generalized dimensions. The Rényi entropy is important in ecology and statistics as index of diversity.
EntropyEntropy is a scientific concept, as well as a measurable physical property, that is most commonly associated with a state of disorder, randomness, or uncertainty. The term and the concept are used in diverse fields, from classical thermodynamics, where it was first recognized, to the microscopic description of nature in statistical physics, and to the principles of information theory.
Corpus linguisticsCorpus 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.
Text corpusIn linguistics and natural language processing, a corpus (: corpora) or text corpus is a dataset, consisting of natively digital and older, digitalized, language resources, either annotated or unannotated. Annotated, they have been used in corpus linguistics for statistical hypothesis testing, checking occurrences or validating linguistic rules within a specific language territory. In search technology, a corpus is the collection of documents which is being searched.