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Query processing method and system for text big data

A processing method and big data technology, applied in the query processing method and system field of text big data, can solve problems such as slow response time, high workload and implementation complexity, and difficult search engine, so as to eliminate redundancy and improve The effect of accuracy and guaranteed efficiency

Pending Publication Date: 2020-11-06
深圳市维度数据科技股份有限公司
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  • Summary
  • Abstract
  • Description
  • Claims
  • Application Information

AI Technical Summary

Problems solved by technology

[0003] In the case of fixed conditions such as server hardware and database configuration, if the traditional query method is used, its query efficiency will continue to decrease as the amount of data continues to increase, and the response time of user queries will become slower and slower. Situations where the database is unavailable due to a query
Although it is possible to consider introducing a search engine to realize the query operation of massive data, since the search engine cannot effectively understand the business data, it is difficult to introduce the search engine to realize the rapid analysis and query of the business data of a specific industry, and the workload and implementation are complicated. too high

Method used

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  • Query processing method and system for text big data
  • Query processing method and system for text big data
  • Query processing method and system for text big data

Examples

Experimental program
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Embodiment 1

[0029] see figure 1 , figure 1 Shown is provided by the embodiment of this application figure 1 A schematic flow diagram of a query processing method for text big data provided by an embodiment of the present invention, which includes:

[0030] Step S100, acquiring semantics of text big data;

[0031] Specifically, the content entity identified and extracted in the text big data for instruction query is obtained.

[0032] In some implementations, the semantic model of the big text data is standardized and modified so that the semantic model of the big text data can be converted to each other for different query objects. For example: it can be applied to text classification through machine learning methods. The basic process is labeling. A batch of texts are accurately classified by manual labor, and used as training materials for machine learning; training, the computer digs out some texts that can be used for training. Effective classification rules generate a set of rule...

Embodiment 2

[0044] see figure 2 , figure 2 A specific schematic flowchart of a query processing method for text big data provided by an embodiment of the present invention, which includes:

[0045] Step S200, creating one or more semantic inflection models of query objects involved in the text big data query analysis;

[0046] Specifically, create a semantic morphological model of query objects in text big data, and perform semantic analysis, identification, and extraction of content entities for command queries, with different levels of semantic description specifications and conversion criteria

[0047] In some embodiments, semantic analysis refers to using various methods to learn and understand the semantic content represented by a piece of text, and any understanding of language can be classified into the category of semantic analysis. A piece of text is usually composed of words, sentences, and paragraphs. According to the different language units of the object of understanding,...

Embodiment 3

[0077] see image 3 , image 3 A schematic diagram of a query processing system module for text big data provided by an embodiment of the present invention, which includes: a specification module, used to obtain the semantics of text big data; a query module, used to configure query rules and the query rules and query conditions Correspondence; instruction module, used to integrate SQL syntax to generate text big data semantic instruction analysis and query model; control module, used to record the intermediate process variables and temporary status of the query and feedback the result.

[0078] It also includes a memory, a processor and a communication interface, the memory, the processor and the communication interface are electrically connected to each other directly or indirectly, so as to realize data transmission or interaction. For example, these components can be electrically connected to each other through one or more communication buses or signal lines. The memory ...

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Abstract

The invention provides a query processing method and system for text big data, and relates to the field of computer application. The text big data query processing method comprises the steps of obtaining text big data semantics; configuring a query rule and a corresponding relationship between the query rule and a query condition; fusing SQL syntax to generate a text big data semantic instructionanalysis and query model; and recording a queried intermediate process variable and the temporary state and feeding back a result. The semantic model can be standardized, the problems of redundancy,invalidation and the like in the query process are eliminated, the accuracy of the query process is improved, and the most effective query mode is quickly found to obtain the result. In addition, theinvention further provides a query processing system for the text big data. The query processing system comprises a specification module, a query module, an instruction module and a control module.

Description

technical field [0001] The present invention relates to the field of computer applications, in particular to a query processing method and system for text big data. Background technique [0002] With the development of the Internet, the amount of data in various business systems is increasing day by day, especially in the telecommunications and Internet industries. In the face of these big data query requirements, query performance and efficiency are the first to bear the brunt. [0003] In the case of fixed conditions such as server hardware and database configuration, if the traditional query method is used, its query efficiency will continue to decrease as the amount of data continues to increase, and the response time of user queries will become slower and slower. Situations where the database is unavailable due to a query. Although it is possible to consider introducing a search engine to realize the query operation of massive data, since the search engine cannot effe...

Claims

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Application Information

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Patent Type & Authority Applications(China)
IPC IPC(8): G06F16/332G06F16/33G06F16/35G06N20/00
CPCG06F16/332G06F16/3344G06F16/35G06N20/00
Inventor 黄海阳
Owner 深圳市维度数据科技股份有限公司
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