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The distributional hypothesis is the basis for statistical semantics. Although the Distributional Hypothesis originated in linguistics, [4] [5] it is now receiving attention in cognitive science especially regarding the context of word use. [6]
Distributionalism can be said to have originated in the work of structuralist linguist Leonard Bloomfield and was more clearly formalised by Zellig S. Harris. [1] [3]This theory emerged in the United States in the 1950s, as a variant of structuralism, which was the mainstream linguistic theory at the time, and dominated American linguistics for some time. [4]
In linguistics, Immediate Constituent Analysis (ICA) is a syntactic theory which focuses on the hierarchical structure of sentences by isolating and identifying the constituents. While the idea of breaking down sentences into smaller components can be traced back to early psychological and linguistic theories, ICA as a formal method was ...
The basic principle of Distributed Morphology is that there is a single generative engine for the formation of both complex words and complex phrases: there is no division between syntax and morphology and there is no Lexicon in the sense it has in traditional generative grammar.
Latent semantic analysis (LSA) is a technique in natural language processing, in particular distributional semantics, of analyzing relationships between a set of documents and the terms they contain by producing a set of concepts related to the documents and terms.
Statistical learning is the ability for humans and other animals to extract statistical regularities from the world around them to learn about the environment. Although statistical learning is now thought to be a generalized learning mechanism, the phenomenon was first identified in human infant language acquisition.
Statistical language acquisition, a branch of developmental psycholinguistics, studies the process by which humans develop the ability to perceive, produce, comprehend, and communicate with natural language in all of its aspects (phonological, syntactic, lexical, morphological, semantic) through the use of general learning mechanisms operating on statistical patterns in the linguistic input.
Quantitative linguistics (QL) is a sub-discipline of general linguistics and, more specifically, of mathematical linguistics. Quantitative linguistics deals with language learning, language change, and application as well as structure of natural languages.