CN109885665A - A kind of data query method, apparatus and system - Google Patents
A kind of data query method, apparatus and system Download PDFInfo
- Publication number
- CN109885665A CN109885665A CN201910017988.5A CN201910017988A CN109885665A CN 109885665 A CN109885665 A CN 109885665A CN 201910017988 A CN201910017988 A CN 201910017988A CN 109885665 A CN109885665 A CN 109885665A
- Authority
- CN
- China
- Prior art keywords
- query
- data
- database
- data base
- cloud server
- Prior art date
- Legal status (The legal status is an assumption and is not a legal conclusion. Google has not performed a legal analysis and makes no representation as to the accuracy of the status listed.)
- Pending
Links
Abstract
The invention discloses a kind of data query method, apparatus and systems, wherein data query method include: receive it is from the user by voice or the inquiry request of text input；Data query structure is generated according to inquiry request；According to local data base type, by data query structural generation query sentence of database, wherein local data base includes the domain knowledge map stored in the form of chart database；Local data base is inquired according to query sentence of database；And return to the query result of local data base.By the invention it is possible to obtain accurate query result.
Description
Technical field
The present invention relates to communication systems, and in particular, to a kind of data query method, apparatus and system.
Background technique
Cognition, which calculates, represents a kind of completely new calculating mode, it contains information analysis, natural language processing and engineering
A large amount of technological innovations in habit field, can power-assisted policymaker outstanding see clearly is disclosed from a large amount of unstructured datas.
Currently, cognitive techniques are mainly embedded into product by the product class application for recognizing calculating, make industry cognition meter
Calculation system, Lai Shixian intelligent behavior, naturally exchange (such as and seeing) and automation.Cognition computing system can provide encyclopaedia
The information of pandect formula assists and support, the information that human use can be allowed extensive and deep, becomes the " senior special of every field
Family ", can help the mankind found in numerous and complicated information in it association and the trend emerged in large numbers.
Currently, cognition computing system such as question answering system can only search for answer mostly, and apply natural language processing
Recognize the direct calculating answer that computing system can be more friendly.But since natural language processing technique difficulty is larger, applied field
Scape is more complex, so still having many problems in the application, for example, Entity recognition is inaccurate, which results in for example personal intelligence
The such cognition computing system of energy assistant often will appear the case where giving an irrelevant answer.
Summary of the invention
In view of this, the purpose of the present invention is to provide a kind of data query method, apparatus and system, to solve existing skill
In art due to caused by cognition computing system Entity recognition inaccuracy personal intelligent assistant often will appear and give an irrelevant answer
Problem.
On the one hand, a kind of data query method is provided, this method comprises: receiving from the user by voice or text
The inquiry request of input；Data query structure is generated according to inquiry request；According to local data base type, by data query structure
Be converted to corresponding query sentence of database, wherein local data base includes the domain knowledge figure stored in the form of chart database
Spectrum；Local data base is inquired according to query sentence of database；And return to the query result of local data base.
On the other hand, a kind of data query device is provided, which includes: inquiry request receiving unit, for receiving
It is from the user by voice or the inquiry request of text input；Query structure generation unit, for being generated according to inquiry request
Data query structure；Query statement generation unit, for according to local data base type, data query structure to be converted to correspondence
Query sentence of database, wherein local data base include in the form of chart database store domain knowledge map；Cargo tracer
Member, for inquiring local data base according to query sentence of database；And query result return unit, for returning to local data
The query result in library.
In another aspect, provide a kind of data query system, the system include: privately owned Cloud Server, publicly-owned Cloud Server,
And the gateway for communication between privately owned Cloud Server and publicly-owned Cloud Server, wherein privately owned Cloud Server includes:
Local data base and above-mentioned data query device；Publicly-owned Cloud Server includes: public database and common data inquiry
Unit, wherein common data query unit includes: common query request receiving module, from the user passes through language for receiving
The publicly-owned information inquiring request of sound or text input；Common query module, it is public for being inquired according to publicly-owned information inquiring request
Database；And common query result return module, for returning to the query result of public database.
In another aspect, provide a kind of computer equipment, including memory, processor and it is stored on the memory simultaneously
The computer program that can be run on a processor, the processor execute above-mentioned method.
In another aspect, providing a kind of computer readable storage medium, which has execution
The computer program of the above method.
A technical solution in above-mentioned technical proposal has the following beneficial effects: by looking into the voice of user or text
It askes request and generates data query structure, and data query structure is converted to by corresponding database according to local data base type and is looked into
Ask sentence, later further according to query sentence of database inquiry database obtain query result, the query result obtained in this way due to
Entity recognition is relatively accurate and makes query result also more accurate, to overcome in the prior art such as personal intelligent assistant's warp
It often will appear the problem of giving an irrelevant answer.
Detailed description of the invention
By referring to the drawings to the description of the embodiment of the present invention, the above and other purposes of the present invention, feature and
Advantage will be apparent from, in the accompanying drawings:
Fig. 1 is the flow chart of data query method according to an embodiment of the present invention；
Fig. 2 is the structural schematic diagram of building domain knowledge map according to an embodiment of the present invention；
Fig. 3 is the structural block diagram of data query device according to an embodiment of the present invention；
Fig. 4 is the specific block diagram of query structure generation unit 302 according to an embodiment of the present invention；
Fig. 5 is the structural block diagram of data query system according to an embodiment of the present invention；
Fig. 6 is the detailed block diagram of data query system according to an embodiment of the present invention；
Fig. 7 is the specific block diagram of knowledge mapping generation unit 5013 according to an embodiment of the present invention；
Fig. 8 is the specific block diagram of common data query unit 5022 according to an embodiment of the present invention；
Fig. 9 is the structural schematic diagram of query result visualization adaptation chart according to an embodiment of the present invention；
Figure 10 is the flow chart of building gateway 503 according to an embodiment of the present invention；
Figure 11 is the instance graph of data query system according to an embodiment of the present invention.
Specific embodiment
Since natural language processing technique difficulty is too big, application scenarios are too complicated, so there are still many in the application
Problem, such as personal intelligent assistant often will appear the case where giving an irrelevant answer.Based on this, the embodiment of the invention provides a kind of numbers
According to query scheme, to solve the problems, such as this.
Below based on embodiment, present invention is described, but the present invention is not restricted to these embodiments.
According to an embodiment of the present invention, a kind of data query method is provided.Fig. 1 is number according to an embodiment of the present invention
According to the flow chart of querying method, as shown in Figure 1, this method comprises:
Step 101, it receives from the user by voice or the inquiry request of text input；
Step 102, data query structure is generated according to the inquiry request；
Step 103, according to local data base type, data query structure is converted into corresponding query sentence of database,
Wherein, local data base includes the domain knowledge map stored in the form of chart database；
Step 104, local data base is inquired according to query sentence of database；And
Step 105, the query result of local data base is returned.
By the way that the voice of user or text query request are generated data query structure, and will according to local data base type
Data query structure is converted to corresponding query sentence of database, obtains later further according to query sentence of database inquiry database
Query result, the query result obtained in this way make query result also more accurate since Entity recognition is relatively accurate, thus gram
It has taken in the prior art as personal intelligent assistant often will appear the problem of giving an irrelevant answer.
Data in above-mentioned domain knowledge map are mainly derived from industry data, and industry data here includes local industry
Data, and/or networking industry data.Wherein, local industry data mainly includes the structure being stored in enterprise's local data base
Change or semi-structured data, networking industry data are mainly the network text data obtained by crawler technology.
After obtaining industry data, mainly in the following way generate domain knowledge map: obtain industry data with
Entity, attribute and the relevant information of relationship；And by the information diagram data relevant to entity, attribute and relationship of industry data
Library form is stored to generate domain knowledge map.
Specifically, Fig. 2 is the structural schematic diagram of building domain knowledge map according to an embodiment of the present invention, as shown in Fig. 2,
The building of domain knowledge map specifically includes that data acquisition, information extraction, knowledge fusion and knowledge using four parts, are divided below
This four part is not described in detail.
(1) data acquire: the acquisition of industry data mainly includes two parts: a part is the net obtained by crawler technology
Network text data；Another part is structuring or semi-structured data in enterprise's local data base.
(2) information extraction: for network text data, the descriptor (for example, keyword) for extracting text is used as entity,
It exactly extracts several significant words or phrase automatically from one section of given text, utilizes the relationship between local vocabulary
Subsequent key word is ranked up, directly extracts entity and attribute from text itself.Then, using participle tool HanLP (Han
Language Processing, Chinese processing packet) interdependent parser neural network based generate interdependent syntax
Tree, obtains the information such as syntactic structure of the part of speech, dependence of all words and sentence in a short sentence, is known according to these information
It Chu not entity relationship.
For local industry data, local data base logical layer structure is extracted, local data base logical layer structure is carried out
Information relevant to entity, attribute and relationship is generated after verification amendment, for example, generating specific entity, attribute and relation information.
(3) knowledge fusion: being disambiguated by isomeric data integration, reference resolution, entity and the data processings sides such as entity alignment
Method, the data such as the entity obtained to above- mentioned information extraction step, attribute and relationship carry out fusion arrangement.
(4) knowledge application: the entity, attribute and relationship that obtain after arrangement are saved in the form of chart database.
By the domain knowledge map of above-mentioned generation, be conducive to the data query service and call operation in privately owned cloud.
It in actual operation, can be using based on depth for above-mentioned non-structured data acquisition and processing technique
The unstructured data processing method of habit, using deep learning algorithm, is completed to meet using big data platform and big data frame
The non-knots such as the image, video of big data 4V (data capacity is big, data type is various, commercial value is high and processing speed is fast) characteristic
Storage, pretreatment and the final structuring processing of structure data.The storage of magnanimity unstructured data may be implemented in this way,
The batch of unstructured data is supported to handle in real time, the efficiency of enhancing unstructured data processing improves the accurate of processing result
Property and reasonability.
In a step 102, generating data query structure according to inquiry request includes: to obtain entity word according to inquiry request；
According to the structural analysis query logic of the syntax dependence of entity word and local data base to generate data query structure.
That is, i.e. generation machine can be managed by the natural language or text generation data query result of user's input
The level of abstraction query structure of solution.Specifically, it can be mentioned by open source natural language processing kit jieba (participle tool) and Baidu
The interdependent API of the sentence of confession (Application Program Interface, application programming interfaces), to the Chinese Query of input
Sentence is handled, and entity word, part of speech and syntax result are obtained.By entity and local data library structure corresponding relationship, reality is obtained
Pronouns, general term for nouns, numerals and measure words configuration.For example, output as follows can be obtained in voice input " Zhou Xing speed box office receipts total amount in 2017 ":
Then, it by the syntax dependence of entity word and local data base structural analysis data query logic, obtains general
Data query structure, it is specific as follows shown in:
It is patrolled by obtaining entity word, and according to the structural analysis of the syntax dependence of entity word and local data base inquiry
Volume, Entity recognition can be more accurately carried out, to obtain more accurately query result.
In step 103, according to local data base type, by the corresponding data base querying language of data query structural generation
Speech.Since each database software has the query language of itself, thus the data query structure generated in a step 102 is pair
A kind of generalization expression way for inquiring content, can be converted accordingly for disparate databases.For example, above-mentioned steps
It is as follows that data query structure in 102 examples can be converted sql sentence: " the total box office select SUM (box_office) AS
' 2017 ' AND person=' Zhou Xingchi ' " of from table_film where year=
Later, data base querying is carried out according to the query sentence of database of step 103, and by query result data with interface
The request results of service return.
As seen from the above description, industry field knowledge is carried out by the methods of key phrases extraction and interdependent syntactic analysis real
Body extracts and relationship is extracted to construct accurate domain knowledge map, and is requested by local data base type user query
It is inquired, since the Entity recognition requested user query is more accurate, available relatively accurately query result, from
And it can overcome the problems, such as that such as personal intelligent assistant in the prior art often will appear and give an irrelevant answer.
According to another embodiment of the present invention, a kind of data query device is additionally provided.Fig. 3 is according to embodiments of the present invention
Data query device structural block diagram, as shown in figure 3, the device includes: that inquiry request receiving unit 301, query structure are raw
At unit 302, query statement generation unit 303, query unit 304 and query result return unit 305, in which:
Inquiry request receiving unit 301, it is from the user by voice or the inquiry request of text input for receiving；
Query structure generation unit 302, for generating data query structure according to inquiry request；
Query statement generation unit 303, for according to local data base type, data query structure to be converted to accordingly
Query sentence of database, wherein local data base includes the domain knowledge map stored in the form of chart database；
Query unit 304, for inquiring local data base according to query sentence of database；And
Query result return unit 305, for returning to the query result of local data base.
The received user query of inquiry request receiving unit 301 are requested by query structure generation unit 302 to generate number
According to query structure, data query structure is converted to corresponding number according to local data base type by query statement generation unit 303
According to library inquiry sentence, database is inquired according to query sentence of database by query unit 304 again later and obtains query result, and by
Query result return unit 305 returns result to user, and the query result obtained in this way makes since Entity recognition is relatively accurate
Query result is also more accurate, overcome in the prior art as personal intelligent assistant often will appear asking of giving an irrelevant answer
Topic.
Data in above-mentioned domain knowledge map are mainly derived from industry data, and industry data here includes local industry
Data, and/or networking industry data.
Domain knowledge map in local data base can be constructed by mode as shown in Figure 2 above, pass through structure
The domain knowledge map built is conducive to the more accurately data query service in privately owned cloud.Specific building domain knowledge map
Process, may refer to above-described embodiment, details are not described herein again.
Fig. 4 is the specific block diagram of query structure generation unit 302, as shown in figure 4, query structure generation unit 302
It include: that entity word obtains module 3021 and query structure generation module 3022, in which:
Entity word obtains module 3021, for obtaining entity word according to inquiry request；
Query structure generation module 3022, for according to the syntax dependence of entity word and the structure point of local data base
Query logic is analysed to generate data query structure.
Module 3021 is obtained by entity word and obtains entity word, and query structure generation module 3022 is according to the syntax of entity word
The structural analysis query logic of dependence and local data base obtains common data query structure, in this way can be more acurrate
Ground carries out Entity recognition, to obtain more accurately query result.
Query statement generation unit 303 is according to local data base type, by the corresponding data of data query structural generation
Database query language.The specifically implementation procedure of query statement generation unit 303 may refer to above-described embodiment step 103.
As seen from the above description, industry field knowledge is carried out by the methods of key phrases extraction and interdependent syntactic analysis real
Body extracts and relationship is extracted to construct domain knowledge map, and obtains entity word by query structure generation unit 302, according to reality
The structural analysis query logic of the syntax dependence of pronouns, general term for nouns, numerals and measure words and local data base generates data query structure, inquires language later
Data query structure is converted to corresponding data base query language according to local data base type by sentence generation unit 303, and
The query result that local data base obtains is inquired by query unit 304, since the Entity recognition requested user query is calibrated
Really, thus query result also can be more acurrate, in the prior art answered as personal intelligent assistant often will appear so as to overcome
The problem of non-asked.
According to there are one the embodiment of the present invention, a kind of data query system is provided.Fig. 5 is the data query system
Structural block diagram, as shown in figure 5, the system includes: privately owned Cloud Server 501, publicly-owned Cloud Server 502 and gateway
503, wherein gateway 503 is for the communication between privately owned Cloud Server 501 and publicly-owned Cloud Server 502.
The data query system is constructed corresponding industry hot word and known using the technologies such as participle, term vector for different field
Know library (for example, above-mentioned domain knowledge map), and artificial knowledge is combined to carry out Entity recognition, the Entity recognition information obtained in this way
Can be more acurrate, more accurate result is provided for subsequent query operation.
Fig. 6 is the detailed block diagram of data query system, as shown in fig. 6, privately owned Cloud Server 501 includes: local number
According to library 5011 and data query device 5012；Publicly-owned Cloud Server 502 includes: public database 5021 and common data cargo tracer
Member 5022.Below in conjunction with system shown in fig. 6, be described in detail respectively privately owned Cloud Server 501, publicly-owned Cloud Server 502 and
Gateway 503.
(1) privately owned Cloud Server 501
Preferably, data query device 5012 can be the data query device in above-described embodiment, data query device
5012 specific implementation procedure may refer to above-mentioned data query device.
In one embodiment, privately owned Cloud Server 501 further include: knowledge mapping generation unit 5013 (is not shown in figure
Show), for generating domain knowledge map according to industry data.
Specifically, as shown in fig. 7, the knowledge mapping generation unit 5013 includes: that data information obtains module 50131 and knows
Know map generation module 50132, in which:
Data information obtains module 50131, for obtaining the information relevant to entity, attribute and relationship of industry data；
Knowledge mapping generation module 50132, for scheming the information relevant to entity, attribute and relationship of industry data
Database form is stored to generate domain knowledge map.
Specifically the implementation procedure of knowledge mapping generation unit may refer to domain knowledge map construction mistake shown in Fig. 2
Journey, details are not described herein again.
The domain knowledge map generated by knowledge mapping generation unit 5013, can be in order to private clound server 501
Data query service and call operation.
As known from the above, user carries out voice or text query, data query device by data query device 5012
5012 pairs of inquiry requests accurately identify, and the knowledge mapping in local data base 5011 is inquired and returns to inquiry knot
Fruit, compared with the prior art, the query result that the embodiment of the present invention returns are more accurate.
(2) publicly-owned Cloud Server 502
Fig. 8 is the specific block diagram of the common data query unit 5022 in publicly-owned Cloud Server 502.As shown in figure 8,
Common data query unit 5022 specifically includes: common query request receiving module 50221, common query module 50222 and public affairs
Query result return module 50223 altogether, in which:
Common query request receiving module 50221, it is from the user by the publicly-owned of voice or text input for receiving
Information inquiring request；
Common query module 50222, for inquiring public database according to publicly-owned information inquiring request；And
Common query result return module 50223, for returning to the query result of public database.
Public database in publicly-owned Cloud Server 502 also may include common knowledge map, using based on natural language
Processing technique carries out entity extraction to domain knowledge corpus by the methods of key phrases extraction and interdependent syntactic analysis and relationship mentions
It takes, specifically can be extended to and do entity classification and cluster towards magnanimity Web corpus, open neck on a large scale can be effectively applicable to
The building of domain knowledge map.The mode for specifically constructing common knowledge map is referred to above-mentioned domain knowledge map construction side
Formula, details are not described herein again.
In one embodiment, common data query unit 5022 can also include: common query result display module
50224 (not shown), for showing query result in the form of Visual Chart according to the data characteristics of query result.
In the specific implementation, publicly-owned Cloud Server can build user terminal web services and public data services, individually below
The two services are described in detail.
User terminal web services specifically include that development of user end software, provide the inquiry of natural language interaction formula, query result
The functions such as visualization, the customized report production of user.
In actual operation, user can be inputted in inquiry input frame by voice or text, and back office interface return is looked into
It askes as a result, user can continue input inquiry sentence and carry out data drill down operator, system will save user on the basis of query result
The All Paths of data are accessed, in case searching.
Query result visualization mainly include provide line chart, histogram, cake chart, radar map, river figure, Sang Jitu,
A variety of mainstream data Visual Charts such as relational graph, map carry out automatic adaptation according to the data characteristics that user query return,
Adaptation procedure can be found in shown in Fig. 9, specifically comprise the following steps:
(1) semanteme for analyzing data, obtains data characteristics label: index, trend, accounting, relationship, geography and distribution etc.；
(2) analysis obtains data dimension and data sequence number (simple sequence or multisequencing)；
(3) the Visual Chart pattern of one group of data is judged according to allocation plan.
Later, the visualization model that inquiry obtains can be saved in collection by user, can be used for subsequent datagram
Accuse production.Specifically, module can be dragged to report editing area to be laid out, generate after the editor such as title, chart style
Report, then provide with word, pdf or picture format downloading.
Public data services specifically include that the publicly-owned cloud service software of exploitation, provide the storage of industry universal data, inquire with
And system configuration data storage, query interface.
(3) gateway 503
Gateway 503 is for realizing the communication between privately owned Cloud Server 501 and publicly-owned Cloud Server 502.In reality
In operation, the server-side of gateway 503 can be deployed in publicly-owned Cloud Server, and client deployment is in privately owned Cloud Server.
Figure 10 is the flow chart according to an embodiment of the present invention that gateway 503 is constructed using Open-Source Tools ngrok, such as
Shown in Figure 10, which includes:
Step 1001, Ubuntu operating system is installed, due to compiling the source code ratio of ngrok under linux environment
It is convenient many under windows, thus selection uses ubuntu here；
Step 1002, ngrok server and client application are generated, the source code trustship of ngrok on github,
Git can be first installed at ubuntu, the source code of ngrok is copied into local again；Installation, compiling, with postponing generation server
With client-side program.
Step 1003, the server of generation is copied on publicly-owned Cloud Server and is run by deployment services end program；
Step 1004, ngrok client is disposed, the client-side program of generation is copied on privately owned Cloud Server and is run；
Step 1005, operation service gateway.
By constructing gateway between publicly-owned Cloud Server and privately owned Cloud Server, it is logical that data encryption may be implemented
Letter, to guarantee the safety of data and user information.
In one embodiment, data query system can be using mixed cloud architecture technology come real, as shown in figure 11, number
Include multiple privately owned Cloud Servers (being as shown in the figure the proprietary cloud of tenant) according to inquiry system, rely on multiple enterprise's private clound data,
Data service is provided for the user in public cloud, the secure communication between private clound and public cloud is realized by gateway.
Referring to Figure 11, the function in private clound include: local (Local) data service, the original storage of data and
ETL (Extract-Transform-Load) function, further includes knowledge mapping and local data base.Wherein, ETL be by data from
Source terminal is by extracting (extract), interaction conversion (transform), the process for loading (load) to destination.In public cloud
Function include: analysis service, cloud (Cloud) data service, interface service and Visualization Service, further include configuration database,
Public repository and business repository.
According to an embodiment of the present invention, a kind of computer equipment is additionally provided, including memory, processor and be stored in
On memory and the computer program that can run on a processor, the processor realize above-mentioned side when executing computer program
Method.
According to an embodiment of the present invention, a kind of computer readable storage medium is additionally provided, the computer-readable storage
Media storage has the computer program for executing the above method.
In conclusion since natural language processing technique difficulty in the prior art is too big, application scenarios are too complicated, so
Many problems are still had in cognitive system application, such as personal intelligent assistant often will appear the case where giving an irrelevant answer.Base
In this, the embodiment of the invention provides data query scheme, the program is carried out by voice to user or text query request
It accurately identifies, inquiry request is first specifically generated into data query structure, then according to local data base type by data query
Structure is converted to corresponding query sentence of database, later further according to the knowledge mapping in query sentence of database inquiry database
Query result is obtained, the query result obtained in this way makes query result also more accurate since Entity recognition is relatively accurate, from
And it can overcome the problems, such as in the prior art as what personal intelligent assistant occurred gives an irrelevant answer.
Those of ordinary skill in the art will appreciate that implement the method for the above embodiments be can be with
Relevant hardware is instructed to complete by program, the program can be stored in a computer readable storage medium,
The program when being executed, includes the following steps: (the step of method), the storage medium, such as: ROM/RAM, magnetic disk, CD
Deng.
The above description is only a preferred embodiment of the present invention, is not intended to restrict the invention, for those skilled in the art
For, the invention can have various changes and changes.All any modifications made within the spirit and principles of the present invention are equal
Replacement, improvement etc., should all be included in the protection scope of the present invention.
Claims (10)
1. a kind of data query method, which is characterized in that the described method includes:
It receives from the user by voice or the inquiry request of text input；
Data query structure is generated according to the inquiry request；
According to local data base type, the data query structure is converted into corresponding query sentence of database, wherein described
Local data base includes the domain knowledge map stored in the form of chart database；
The local data base is inquired according to the query sentence of database；And
Return to the query result of the local data base.
2. data query method according to claim 1, which is characterized in that generate data query according to the inquiry request
Structure includes:
Entity word is obtained according to the inquiry request；
It is described to generate according to the structural analysis query logic of the syntax dependence of the entity word and the local data base
Data query structure.
3. data query method according to claim 1, which is characterized in that generate the domain knowledge in the following way
Map:
Obtain the information relevant to entity, attribute and relationship of industry data；
The information relevant to entity, attribute and relationship of the industry data chart database form is stored to generate
State domain knowledge map.
4. data query method according to claim 3, which is characterized in that the industry data include it is following at least it
One:
The industry data being locally stored, the industry data obtained by network.
5. a kind of data query device, which is characterized in that described device includes:
Inquiry request receiving unit, it is from the user by voice or the inquiry request of text input for receiving；
Query structure generation unit, for generating data query structure according to the inquiry request；
Query statement generation unit, for according to local data base type, the data query structure to be converted to corresponding number
According to library inquiry sentence, wherein the local data base includes the domain knowledge map stored in the form of chart database；
Query unit, for inquiring the local data base according to the query sentence of database；And
Query result return unit, for returning to the query result of the local data base.
6. a kind of data query system, which is characterized in that the system comprises: privately owned Cloud Server, publicly-owned Cloud Server and
The gateway for communication between the privately owned Cloud Server and the publicly-owned Cloud Server, wherein
The privately owned Cloud Server includes: local data base and data query device as claimed in claim 5,
The publicly-owned Cloud Server includes: public database and common data query unit, wherein the common data inquiry
Unit includes:
Common query request receiving module is asked for receiving from the user inquire by the publicly-owned information of voice or text input
It asks；
Common query module, for inquiring the public database according to the publicly-owned information inquiring request；And
Common query result return module, for returning to the query result of the public database.
7. data query system according to claim 6, which is characterized in that the privately owned Cloud Server further include:
Knowledge mapping generation unit, for generating domain knowledge map according to industry data.
8. data query system according to claim 7, which is characterized in that the common data query unit further include:
Common query result display module, for showing institute in the form of Visual Chart according to the data characteristics of the query result
State query result.
9. a kind of computer equipment, including memory, processor and it is stored on the memory and can runs on a processor
Computer program, which is characterized in that the processor is realized any in Claims 1-4 when executing the computer program
Method described in.
10. a kind of computer readable storage medium, which is characterized in that the computer-readable recording medium storage has perform claim
It is required that the computer program of any one of 1 to 4 the method.
Priority Applications (1)
| Application Number | Priority Date | Filing Date | Title |
|---|---|---|---|
| CN201910017988.5A CN109885665A (en) | 2019-01-09 | 2019-01-09 | A kind of data query method, apparatus and system |
Applications Claiming Priority (1)
| Application Number | Priority Date | Filing Date | Title |
|---|---|---|---|
| CN201910017988.5A CN109885665A (en) | 2019-01-09 | 2019-01-09 | A kind of data query method, apparatus and system |
Publications (1)
| Publication Number | Publication Date |
|---|---|
| CN109885665A true CN109885665A (en) | 2019-06-14 |
Family
ID=66925765
Family Applications (1)
| Application Number | Title | Priority Date | Filing Date |
|---|---|---|---|
| CN201910017988.5A Pending CN109885665A (en) | 2019-01-09 | 2019-01-09 | A kind of data query method, apparatus and system |
Country Status (1)
| Country | Link |
|---|---|
| CN (1) | CN109885665A (en) |
Cited By (6)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN110555153A (en) * | 2019-08-20 | 2019-12-10 | 暨南大学 | Question-answering system based on domain knowledge graph and construction method thereof |
| CN110929317A (en) * | 2019-10-17 | 2020-03-27 | 广联达科技股份有限公司 | Method, system and computer readable storage medium for automatically complementing user component modeling information |
| CN111177314A (en) * | 2019-12-11 | 2020-05-19 | 北京明略软件系统有限公司 | Method and device for querying knowledge graph and computer readable storage medium |
| CN111930778A (en) * | 2020-08-12 | 2020-11-13 | 中国银行股份有限公司 | Knowledge query method and device |
| CN112035581A (en) * | 2020-08-21 | 2020-12-04 | 北京字节跳动网络技术有限公司 | Model-based task processing method, device, equipment and medium |
| CN117112806A (en) * | 2023-10-12 | 2023-11-24 | 北京大学深圳研究生院 | Knowledge graph-based information structuring method and device |
Citations (4)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN106919655A (en) * | 2017-01-24 | 2017-07-04 | 网易（杭州）网络有限公司 | A kind of answer provides method and apparatus |
| CN107480183A (en) * | 2017-07-06 | 2017-12-15 | 广州索答信息科技有限公司 | A kind of kitchen domain knowledge collection of illustrative plates querying method, device and storage medium |
| CN108491443A (en) * | 2018-02-13 | 2018-09-04 | 上海好体信息科技有限公司 | By computer-implemented and method and computer system of user session |
| US10102291B1 (en) * | 2015-07-06 | 2018-10-16 | Google Llc | Computerized systems and methods for building knowledge bases using context clouds |
-
2019
- 2019-01-09 CN CN201910017988.5A patent/CN109885665A/en active Pending
Patent Citations (4)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| US10102291B1 (en) * | 2015-07-06 | 2018-10-16 | Google Llc | Computerized systems and methods for building knowledge bases using context clouds |
| CN106919655A (en) * | 2017-01-24 | 2017-07-04 | 网易（杭州）网络有限公司 | A kind of answer provides method and apparatus |
| CN107480183A (en) * | 2017-07-06 | 2017-12-15 | 广州索答信息科技有限公司 | A kind of kitchen domain knowledge collection of illustrative plates querying method, device and storage medium |
| CN108491443A (en) * | 2018-02-13 | 2018-09-04 | 上海好体信息科技有限公司 | By computer-implemented and method and computer system of user session |
Cited By (8)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN110555153A (en) * | 2019-08-20 | 2019-12-10 | 暨南大学 | Question-answering system based on domain knowledge graph and construction method thereof |
| CN110929317A (en) * | 2019-10-17 | 2020-03-27 | 广联达科技股份有限公司 | Method, system and computer readable storage medium for automatically complementing user component modeling information |
| CN111177314A (en) * | 2019-12-11 | 2020-05-19 | 北京明略软件系统有限公司 | Method and device for querying knowledge graph and computer readable storage medium |
| CN111930778A (en) * | 2020-08-12 | 2020-11-13 | 中国银行股份有限公司 | Knowledge query method and device |
| CN111930778B (en) * | 2020-08-12 | 2024-02-23 | 中国银行股份有限公司 | Knowledge query method and device |
| CN112035581A (en) * | 2020-08-21 | 2020-12-04 | 北京字节跳动网络技术有限公司 | Model-based task processing method, device, equipment and medium |
| CN117112806A (en) * | 2023-10-12 | 2023-11-24 | 北京大学深圳研究生院 | Knowledge graph-based information structuring method and device |
| CN117112806B (en) * | 2023-10-12 | 2024-01-26 | 北京大学深圳研究生院 | Knowledge graph-based information structuring method and device |
Similar Documents
| Publication | Publication Date | Title |
|---|---|---|
| CN112437917B (en) | Natural language interface for databases using autonomous agents and thesaurus | |
| CN109885665A (en) | A kind of data query method, apparatus and system | |
| CN109284363A (en) | A kind of answering method, device, electronic equipment and storage medium | |
| CN109408820A (en) | A kind of medical terminology mapped system and method, equipment and storage medium | |
| Diefenbach et al. | QAnswer KG: designing a portable question answering system over RDF data | |
| US11106719B2 (en) | Heuristic dimension reduction in metadata modeling | |
| WO2019169858A1 (en) | Searching engine technology based data analysis method and system | |
| JP2021507350A (en) | Reinforcement evidence retrieval of complex answers | |
| CN117271767B (en) | Operation and maintenance knowledge base establishing method based on multiple intelligent agents | |
| CN112507076A (en) | Semantic analysis searching method and device and storage medium | |
| CN111061828B (en) | Digital library knowledge retrieval method and device | |
| Sun | A natural language interface for querying graph databases | |
| José et al. | mRAT-SQL+ GAP: a Portuguese text-to-SQL transformer | |
| CN115878818B (en) | Geographic knowledge graph construction method, device, terminal and storage medium | |
| CN108932225B (en) | Method and system for converting natural language requirements into semantic modeling language statements | |
| Palopoli et al. | Experiences using DIKE, a system for supporting cooperative information system and data warehouse design | |
| CN115269862A (en) | Electric power question-answering and visualization system based on knowledge graph | |
| CN113032353A (en) | Data sharing method, system, electronic device and medium | |
| CN111563141B (en) | Method and system for processing input questions to query a database | |
| CN117235237B (en) | Text generation method and related device | |
| Pouchard et al. | Data Grid discovery and Semantic Web technologies for the earth sciences | |
| Ahmadi et al. | Automatic Data Migration between Two Databases with Different Structure | |
| Gill et al. | Natural Language Processing with Semantic Measurement | |
| Jeong et al. | Creating semantic data from Relational Database | |
| CN114090782A (en) | Knowledge base question-answer implementation method with prior structure and system thereof |
Legal Events
| Date | Code | Title | Description |
|---|---|---|---|
| PB01 | Publication | ||
| PB01 | Publication | ||
| SE01 | Entry into force of request for substantive examination | ||
| SE01 | Entry into force of request for substantive examination | ||
| TA01 | Transfer of patent application right |
Effective date of registration: 20210308 Address after: 100024 north of village committee, danaipo village, Sanjianfang Township, Chaoyang District, Beijing (Room 309, 3rd floor, tizhijie courtyard) Applicant after: Qiancheng Shuzhi (Beijing) Network Technology Co.,Ltd. Address before: 100080 01-a377, 3rd floor, 55 Suzhou street, Haidian District, Beijing Applicant before: BEIJING XIAOSHENG NETWORK TECHNOLOGY Co.,Ltd. |
|
| TA01 | Transfer of patent application right |