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・ Distribution of justice
・ Distribution of lightning
・ Distribution of orchid species
・ Distribution of Scheduled Castes by District in Uttar Pradesh
・ Distribution of seats in the Austrian Landtage
・ Distribution of the FairTax burden
・ Distribution of wealth
・ Distribution of white South Africans
・ Distribution resource planning
・ Distribution Select
・ Distribution software
・ Distribution transformer
・ Distribution Transformer Monitor
・ Distribution uniformity
・ Distribution waterfall
Distributional semantics
・ Distributism
・ Distributive
・ Distributive case
・ Distributive category
・ Distributive efficiency
・ Distributive homomorphism
・ Distributive justice
・ Distributive lattice
・ Distributive law between monads
・ Distributive number
・ Distributive pronoun
・ Distributive property
・ Distributive shock
・ Distributive tendency


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Distributional semantics : ウィキペディア英語版
Distributional semantics
Distributional semantics 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. The basic idea of distributional semantics can be summed up in the so-called Distributional hypothesis: ''linguistic items with similar distributions have similar meanings.''
==Distributional Hypothesis==
The Distributional Hypothesis in linguistics is derived from the semantic theory of language usage, i.e. words that are used and occur in the same contexts tend to purport similar meanings.

The underlying idea that "a word is characterized by the company it keeps" was popularized by Firth.

The Distributional Hypothesis is the basis for Statistical Semantics. Although the Distributional Hypothesis originated in Linguistics,

it is now receiving attention in Cognitive Science especially regarding the context of word use.

In recent years, the distributional hypothesis has provided the basis for the theory of similarity-based generalization in language learning: the idea that children can figure out how to use words they've rarely encountered before by generalizing about their use from distributions of similar words.


The distributional hypothesis suggests that the more semantically similar two words are, the more distributionally similar they will be in turn, and thus the more that they will tend to occur in similar linguistic contexts. Whether or not this suggestion holds has significant implications for both the data-sparsity problem in computational modeling, and for the question of how children are able to learn language so rapidly given relatively impoverished input (this is also known as the problem of the poverty of the stimulus).

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