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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]
Distributional semantics [1] is a research area that develops and studies theories and methods for quantifying and categorizing semantic similarities between linguistic items based on their distributional properties in large samples of language data.
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 ...
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).
Statistical semantics is a subfield of computational semantics, which is in turn a subfield of computational linguistics and natural language processing. Many of the applications of statistical semantics (listed above) can also be addressed by lexicon -based algorithms, instead of the corpus -based algorithms of statistical semantics.
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.
In formal linguistics, discourse representation theory (DRT) is a framework for exploring meaning under a formal semantics approach. One of the main differences between DRT-style approaches and traditional Montagovian approaches is that DRT includes a level of abstract mental representations (discourse representation structures, DRS) within its formalism, which gives it an intrinsic ability to ...