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Semantic recognition method and equipment thereof

A semantic recognition and sentence technology, applied in the field of semantic recognition methods and equipment, can solve problems such as inability to implement complex calculations, low accuracy of natural language semantic understanding, and no

Pending Publication Date: 2020-12-04
EMOTIBOT TECH LTD
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  • Summary
  • Abstract
  • Description
  • Claims
  • Application Information

AI Technical Summary

Problems solved by technology

However, because the invention uses the OData data structure, there are some technical limitations. For example, the recognition of the user's dialogue intention based on context analysis only uses the subject or pronoun replacement method, and the accuracy of semantic understanding of natural language is not high enough; the invention Complicated calculations, such as calculation methods such as summation, averaging, and maximum value, cannot be realized; in addition, the invention cannot realize the recognition and query of Chinese natural language, and the invention does not have the function of making query results as charts and feeding them back to users

Method used

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  • Semantic recognition method and equipment thereof
  • Semantic recognition method and equipment thereof

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Experimental program
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Effect test

Embodiment 1

[0082] Such as figure 1 As shown, the present embodiment provides a semantic recognition method, including the following steps:

[0083] (1) Process judgment

[0084] User input, user input can be natural language input, including text input and voice input, the user input supports Chinese input and English input, the content of user input is called "user text" in the present invention, combined with context, judge Whether the user input is in multiple rounds of dialogue, if the user input is in multiple rounds of dialogue, enter the NLQ processing flow, if the user input is not in multiple rounds of dialogue, call the NLQ trigger module to determine whether the user input contains entities related to database queries, If the user input contains entities related to database query, it will enter the NLQ processing flow; if the user input does not contain entities related to database query, a default reply (backfill) will be triggered. The consequences of the default reply incl...

Embodiment 2

[0118] Embodiment 2: the present invention also provides a kind of semantic identification device, comprises: input module, database module, correction module, analysis analysis module, query behavior module (Query behavior module), sentence generation module, judgment module, execution module, output module.

[0119] The input module is configured to receive user input, the user input may be voice input, and the content input by the user may be natural language.

[0120] The database module is used to store or connect to the retrieved database; the database can be stored locally in the database module or connected through the database module in the cloud or the network, and the database is composed of multiple specific tables, The specific table is not limited to the sorting of information displayed in a frame form such as Excel, and the table here should be understood as a collection of information in various forms.

[0121] Further, the database module can select, suppleme...

Embodiment 3

[0140] Such as figure 2 As shown, this embodiment discloses the user-defined configuration method of the semantic recognition system of the present invention, including:

[0141] (1) Database connection

[0142] The user enters the database connection information, including the database access URI and user name and password, etc. Next, the NLQ system will access the database to determine whether it can successfully access the user database. If so, obtain all the data tables under the database and return them to the user for selection. You only need to select the data table that you want NLQ to support query; if you cannot successfully access the user database, return to the previous step. Or the user directly uploads an excel file containing data that conforms to the NLQ system format. After successfully accessing the database, the user selects the specific table that needs to support NLQ query.

[0143] (2) Multi-table configuration

[0144] Extract information such as da...

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PUM

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Abstract

The invention discloses a semantic recognition method and device, and the method comprises the following steps: receiving a user input which is the voice input or character input of a Chinese naturallanguage; correcting and optimizing user input, and performing grammatical analysis and entity analysis; triggering a Query behavior to determine a specific table of retrieval intention and retrievaltopic retrieval; eliminating ambiguity fields through contexts and / or aggregating contextual information; generating an SQL (Structured Query Language) statement according to the determined Function and Column, and completely collecting necessary elements required by the SQL statement; converting and assembling the SQL statement execution result into a natural language and / or a chart, and outputting the natural language and / or the chart. The invention further discloses semantic recognition equipment which comprises an input module, a database module, an automatic voice recognition correction module, an analysis and analysis module, an inquiry behavior module and the like. The equipment is used for realizing the semantic recognition method, is high in natural language recognition precisionand high in speed, supports custom extension and Chinese and English, and can output graphs.

Description

technical field [0001] The invention relates to the field of artificial intelligence natural language processing, in particular to a semantic recognition method and equipment thereof. Background technique [0002] With the development of technology, the human-computer interaction experience has made great progress. From the initial computer language input to the graphic interface, people are looking forward to and constantly trying new ways of human-computer interaction to obtain a better interactive experience. Taking direct voice interaction as an example, it is very popular because it is very similar to direct communication with humans, convenient and safe, and can complete computer operations while driving and exercising. Speech interaction and other human-computer interactions can be realized through the mutual conversion between natural language and computer language, that is, semantic recognition. Existing human-computer interaction technology mostly uses traditional...

Claims

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Application Information

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Patent Type & Authority Applications(China)
IPC IPC(8): G06F16/242G06F16/2452G06F40/30
CPCG06F16/2433G06F16/24522
Inventor 简仁贤王兵王彦彬沈舜锋武琰
Owner EMOTIBOT TECH LTD
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