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Distributional semantic models differ primarily with respect to the following parameters: Context type (text regions vs. linguistic items) Context window (size, extension, etc.) Frequency weighting (e.g. entropy, pointwise mutual information, [16] etc.) Dimension reduction (e.g. random indexing, singular value decomposition, etc.)
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 ...
This assumption is known in linguistics as the distributional hypothesis. [3] Emile Delavenay defined statistical semantics as the "statistical study of the meanings of words and their frequency and order of recurrence". [ 4 ] "
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.
The bag-of-words model (BoW) is a model of text which uses an unordered collection (a "bag") of words. It is used in natural language processing and information retrieval (IR). It disregards word order (and thus most of syntax or grammar) but captures multiplicity .
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.
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.