%0 Journal Article
%T Three Types of Episodic Associations for the Semantic/Syntactic/Episodic Model of Language Prospective in Applications to the Statistical Translation
%A Zi-Jian Cai
%J Open Access Library Journal
%V 4
%N 8
%P 1-12
%@ 2333-9721
%D 2017
%I Open Access Library
%R 10.4236/oalib.1103830
%X <div style="text-align:justify;">
	<span style="line-height:1.5;">Recently, it was proposed by Cai a new semantic/ syntactic/ episodic model of language encompassing the sentential meanings, while deriving three corresponding principles from it for machine translation, respective</span><span style="line-height:1.5;">ly as first to establish the dictionary of words/phrases, second to translate the grammar, and third to determine the meanings of some words/phrases of multiple meanings by statistical translation. In this article, it is discovered three types of episodic associations for this linguistic model, prospective in applications to statistical translation, as: 1) It is classified the living/natural words and phrases of multiple meanings by behavior, adopting both the zoological/&nbsp;organizational/ physical/ categorical and affective/ behavioral/ logic/ characteristic/ changing characters to classify the nouns and verbs, the affective/ behavioral/ logic/ characteristic/ changing/ spatial/ temporal characters to the adjectives and adverbs, helpful to discern the meanings of them using these episodic associations with others within the sentence. 2) Likewise, it is classified the sentence/paragraph into the category of natural/social subjects like physics, biology, art, economy, etc., which was improved by the Chinese people in television from my original sentential/thematic category. 3) It is suggested to collect the frequent word-pairs during statistical translation, such as ¡°bank money¡±, ¡°war declaration¡±, etc., helpful to determine the episodic associations of some prepositions or terminal ¡°which¡± clauses. It is suggested to use word episodic symbolization to apply them to computer. It is therefore improved the third principle of machine translation as third to determine the meanings of some words/ phrases of multiple meanings by episodic associations with others using the behavioral classification of words, the categorization of sentence/paragraph and the collection of frequent word-pairs.</span> 
</div>
%K Language
%K Semantic/syntactic/episodic linguistic model
%K Statistical translation
%K Behavioral classification of living/natural words
%K Sentential/paragraphic categorization
%K Frequent word-pairs
%U http://www.oalib.com/paper/5288494