A business model-based semantic training system and a business model-based semantic training method

A business model and training system technology, applied in special data processing applications, instruments, electrical and digital data processing, etc., can solve problems such as high maintenance costs and difficult management of semantic training, and achieve the effect of solving difficult management and lowering the threshold

Pending Publication Date: 2019-05-03
饶竹一 +1
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Problems solved by technology

[0005] The main purpose of the present invention is to propose a semantic training method and system based on a business model, aiming at solving the problems of difficult management and high maintenance cost of semantic training

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  • A business model-based semantic training system and a business model-based semantic training method
  • A business model-based semantic training system and a business model-based semantic training method
  • A business model-based semantic training system and a business model-based semantic training method

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Embodiment Construction

[0076] It should be understood that the specific embodiments described here are only used to explain the present invention, not to limit the present invention.

[0077] Implementations of various embodiments of the present invention will now be described with reference to the accompanying drawings. In the following description, use of suffixes such as 'module', 'part' or 'unit' for denoting elements is only for facilitating description of the present invention and has no specific meaning by itself. Therefore, "module" and "component" may be used mixedly.

[0078] Such as figure 1 As shown, the present invention provides a semantic training system based on a business model, including an entry module 10 , an analysis module 20 , a training use case generation module 30 and a training execution module 40 . in:

[0079] The input module 10 is used to receive the input operation of the business model and obtain the business model data, the business model data includes objects, a...

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Abstract

The invention discloses a semantic training system and method based on a business model. The system comprises an input module which is used for receiving input operation of a business model and obtaining business model data, and the business model data comprises an object, an attribute or a method; connecting the analysis module with the input module and used for analyzing and processing the object, the attribute or the method, obtaining user language knowledge, a semantic structure or a semantic event, constructing a semantic mode according to the user language knowledge, and generating a basic corpus; connecting the training case generation module with the analysis module and make it generate training case data according to the basic corpus;and the training execution module is connectedwith the analysis module and the training case generation module and is used for generating an SPD file, a TCD file and a mapping relation file according to the semantic mode and the training case data. The method solves the problem that semantic training operation tools are difficult to use and master by application developers; and the threshold that developers in the application field have access to the semantic analysis capability is lowered.

Description

technical field [0001] The invention relates to the technical field of natural language processing, in particular to a business model-based semantic training system and a method thereof. Background technique [0002] With the penetration of artificial intelligence in various fields, the world will enter the era of artificial intelligence from the Internet era. As an important branch of artificial intelligence, natural language processing plays an important role in promoting the development of artificial intelligence. Natural Language Processing (NLP) refers to the ability of machines to understand and interpret the way humans write and speak. The goal of NLP is to make computers / machines as intelligent as humans in understanding language, and the ultimate goal is to bridge the gap between human communication (natural language) and computer understanding (machine language). NLP analysis technology is roughly divided into three levels: lexical analysis, syntactic analysis an...

Claims

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Application Information

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Patent Type & Authority Applications(China)
IPC IPC(8): G06F17/27
Inventor 饶竹一
Owner 饶竹一
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