Method of recognizing language information by applying language rule by machine

Abstract

The invention relates to a machine language information processing technology. For the purpose that the machine imitates logic thinking method of human body to understand language and master grammar function, a presentation can be made from sentence structure of a subject, a predicate, an object, an attribute, an adverbial modifier and a complement to theory and application of a noun, a verb, an adjective, a quantifier, an adverb and a function word, and the analysis process of the function of each part can be demonstrated to be used as language teaching demonstration and provide basic exercise for language learning. The method provides each language with a grammar function of analyzing, judging and understanding language information, the grammar function is established on a commonly used and communicating platform, so that the machine can not only recognize language information, but also apply the language information to inter-translate and exchange between languages.

Description

Technical field: [0001] The invention relates to a machine language information processing technology, in particular for a machine simulating a thinking analysis mode of a human, and identifying language information through analysis and judgment. Background technique: [0002] The current machine language information processing technology can only rely on the shape of the text for text exchange processing, and does not involve the phonetic and semantic information carried by the text at all. Since the machine itself does not have the function of recognizing semantics, when inputting "tolerance (gōngchāi)" or "tolerance (gōngchā)", "反(dǎo)" or "倒(dào)", the recognition results are the same. No matter whether the current machine is inputting text by voice recognition or keyboard entry, the process of processing text only depends on "glyph". [0003] In addition, the vocabulary we provide to the machine has multiple meanings and multiple meanings, and the machine itself does n...

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Problems solved by technology

[0003] In addition, the vocabulary we provide to the machine has multiple meanings and multiple meanings, and the machine itself does not have grammatical functions such as analysis and judgment. Therefore, the machine cannot understand the language information composed of multiple words into a complete semantics, can only make judgments on single words and connect them, use such results to issue instructions and process anything, the result error rate is at least 50%, and the longer the sentence, the higher the error rate

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