CN109271384A - Large database concept and its method for building up, the device and electronic equipment of interpreter's behavior - Google Patents
Large database concept and its method for building up, the device and electronic equipment of interpreter's behavior Download PDFInfo
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Abstract
The embodiment of the present invention provides the large database concept and its method for building up, device and electronic equipment of a kind of interpreter's behavior, the method comprise the steps that the record data of the external system based on interpreter assemble the behavioral data of interpreter using opening API technology；The behavioral data is handled with the storage model of big data, forms the large database concept of interpreter's behavior.The embodiment of the present invention assembles the behavioral data of user using opening API technology, and by establishing large database concept logical architecture, the data of aggregation are handled with the storage model of big data, establish the large database concept of interpreter's behavior, depth it can grasp interpreter's information to greatest extent, and translated resources are used by sufficiently shared, improve the utilization rate of resource.
Description
Technical field
The present embodiments relate to internet data administrative skill fields, more particularly, to a kind of the big of interpreter's behavior
Database and its method for building up, device and electronic equipment.
Background technique
With the fast development of Internet technology, translation industry also rapidly enters digitization, information age.But meanwhile
Translation industry utilizes also generally existing following problems to resource:
First, business variation is fast, resource uses uneven.Translation company is frequently present of business abundance interpreter's deficiency, or
The situation of interpreter's abundance business deficiency etc., business and resource cannot reach balance.
Second, development of resources is at high cost, opposite resource utilization is extremely low.Many translation companies are costly at original exploitation
Resource, but the resource utilization that developed is extremely low.
Third, rare foreign languages scarcity of resources, use cost are too high.Rare foreign languages such as Spanish, Portuguese, resource compare
Rare, resource use cost is too high.
And the main reason for above problem occur is one side resource isolation, sufficiently cannot be excavated and be shared, it is another
Aspect transparent resource, due to being unable to depth identification resource, resource utilization is low.Therefore, allow resource that can largely converge simultaneously quilt
It is sufficiently shared to use, it enables to maximum depth and grasps interpreter's information, improve the utilization rate of resource, be current industry
Urgently to be resolved needs project.
Summary of the invention
In order to overcome the above problem or at least be partially solved the above problem, the embodiment of the present invention provides a kind of interpreter's row
For large database concept and its method for building up, device and electronic equipment, grasp interpreter's information to maximum depth, and make
Translated resources can be used by sufficiently shared, improve the utilization rate of resource.
In a first aspect, the embodiment of the present invention provides a kind of large database concept method for building up of interpreter's behavior, comprising: be based on interpreter
External system record data the behavioral data of interpreter assembled using opening API technology；By the behavioral data with big data
Storage model handled, form the large database concept of interpreter's behavior.
Wherein, the behavioral data of interpreter specifically includes the essential information data of interpreter, task behavioral data, evaluation row
Be data, capacity data, empirical data, credit data, translation tool data, translation preference and login/exit in data one
Kind is a variety of.
Wherein, described the step of being handled the behavioral data with the storage model of big data, further comprises: structure
Build that have by bottom framework to upper layer framework include acquisition layer, database layer, tap layer, knowledge base layer, service layer and application layer
Large database concept logical architecture, and define the service logic of each logical layer respectively；To the behavioral data, according to the big data
Library logical architecture and the service logic are stored.
Wherein, the step of service logic for defining each logical layer respectively further comprises: defining the acquisition layer
Service logic includes: to collect the behavioral data of interpreter using opening API technology or crawler technology, and by the behavior number
According to being transmitted to the database layer；The service logic for defining the database layer includes: using NOSQL database, with big data
Form store the behavioral data；The service logic for defining the tap layer includes: to carry out to the behavioral data of interpreter
Cleaning, processing, extract the different genes of interpreter, and by the gene delivery to the knowledge base layer；Define the knowledge base layer
Service logic include: to be stored to the gene, and provide the gene for the service layer and the application layer；Definition
The service logic of the service layer includes: the api interface service provided to the gene；Define the service logic of the application layer
It include: that the APP application based on the gene is provided.
Further, described to the behavioral data, according to the large database concept logical architecture and the service logic
After the step of being stored, the method for the embodiment of the present invention further include: definition is to big in the large database concept of interpreter's behavior
The processing logic of data includes data capture logic, importing/pretreatment logic, statistical analysis logic and data mining logic.
Further, after the service logic for defining each logical layer respectively the step of, the side of the embodiment of the present invention
Method further include: carry out the open system API design based on event model.
Second aspect, the large database concept that the embodiment of the present invention provides a kind of interpreter's behavior establish device, comprising: data acquisition
Module assembles the behavioral data of interpreter using opening API technology for the external system record data based on interpreter；Export mould
Block forms the large database concept of interpreter's behavior for handling the behavioral data with the storage model of big data.
The third aspect, the embodiment of the present invention provide a kind of electronic equipment, comprising: at least one processor, at least one
Manage device, communication interface and bus；The memory, the processor and the communication interface are completed mutual by the bus
Communication, information of the communication interface for the electronic equipment and external system api interface equipment room transmits；The storage
The computer program that can be run on the processor is stored in device, it is real when the processor executes the computer program
The now large database concept method for building up of interpreter's behavior described in first aspect as above.
Fourth aspect, the embodiment of the present invention provide a kind of non-transient computer readable storage medium, the non-transient calculating
Machine readable storage medium storing program for executing stores computer instruction, and the computer instruction executes the computer described in first aspect as above
The large database concept method for building up of interpreter's behavior.
5th aspect, the embodiment of the present invention provide a kind of large database concept of interpreter's behavior, comprising: original library cluster module,
For using NOSQL MongoDB database, the behavioral data of interpreter is stored；Achievement library cluster module, for using
ORALCE database stores the gene of the interpreter of extraction；Application library cluster module, for using MYSQL or
ORACLE database store again after polymerization synchronizes to the gene of interpreter.
The large database concept and its method for building up, device and electronic equipment of interpreter's behavior provided in an embodiment of the present invention use
Opening API technology assembles the behavioral data of user, and by establishing large database concept logical architecture, to the data of aggregation with
The storage model of big data is handled, and the large database concept of interpreter's behavior is established, and depth can grasp interpreter's letter to greatest extent
Breath, and translated resources are used by sufficiently shared, improve the utilization rate of resource.
Detailed description of the invention
In order to more clearly explain the embodiment of the invention or the technical proposal in the existing technology, to embodiment or will show below
There is attached drawing needed in technical description to be briefly described, it should be apparent that, the accompanying drawings in the following description is this hair
Bright some embodiments for those of ordinary skill in the art without creative efforts, can be with root
Other attached drawings are obtained according to these attached drawings.
Fig. 1 is the flow diagram of the large database concept method for building up for interpreter's behavior that one embodiment of the invention provides；
Fig. 2 be another embodiment of the present invention provides interpreter's behavior large database concept method for building up flow diagram；
Fig. 3 is to be patrolled according to the large database concept that the large database concept method for building up of interpreter's behavior provided in an embodiment of the present invention constructs
Collect the structural schematic diagram of framework；
Fig. 4 is at the big data according to defined in the large database concept method for building up of interpreter's behavior provided in an embodiment of the present invention
Manage the flow diagram of logic；
Fig. 5 is to be set according to open system API in the large database concept method for building up of interpreter's behavior provided in an embodiment of the present invention
The schematic illustration of meter；
Fig. 6 is to define according in the large database concept method for building up of interpreter's behavior provided in an embodiment of the present invention to system event
Code schematic diagram；
Fig. 7 is to call API rule according to definition in the large database concept method for building up of interpreter's behavior provided in an embodiment of the present invention
The calling specification and calling example schematic diagram of model；
Fig. 8 is the return according to API Calls in the large database concept method for building up of interpreter's behavior provided in an embodiment of the present invention
Status diagram；
Fig. 9 is that the large database concept of interpreter's behavior provided in an embodiment of the present invention establishes the structural schematic diagram of device；
Figure 10 is the entity structure schematic diagram of electronic equipment provided in an embodiment of the present invention；
Figure 11 is the system structure diagram of the large database concept for interpreter's behavior that one embodiment of the invention provides；
Figure 12 be another embodiment of the present invention provides interpreter's behavior large database concept system structure diagram.
Specific embodiment
In order to make the object, technical scheme and advantages of the embodiment of the invention clearer, below in conjunction with the embodiment of the present invention
In attached drawing, technical scheme in the embodiment of the invention is clearly and completely described, it is clear that described embodiment is
A part of the embodiment of the embodiment of the present invention, instead of all the embodiments.Based on the embodiment in the embodiment of the present invention, ability
Domain those of ordinary skill every other embodiment obtained without making creative work, belongs to the present invention
The range of embodiment protection.
Translation industry uses uneven, resource to the fast, resource using the variation of generally existing business of resource in the prior art
Therefore the problem that development cost is high, opposite resource utilization is extremely low and rare foreign languages scarcity of resources, use cost are too high allows
Resource can be converged largely and be used by sufficiently shared, enabled to maximum depth and grasped interpreter's information, improve money
The utilization rate in source, be current industry it is urgently to be resolved need project.
In view of the above-mentioned problems, the embodiment of the present invention designs in order to which resource can largely be converged and be used by sufficiently shared
In use, the behavioural information of interpreter is recorded, analyzed and excavated, to go depth to grasp the base of interpreter to greatest extent
Plinth information, ability information, posterior infromation and credit information etc. allow each interpreter that can have high identification, fundamentally
Improve the utilization rate of resource.Expansion explanation and introduction will be carried out to the embodiment of the present invention especially by multiple embodiments below.
As the one aspect of the embodiment of the present invention, the present embodiment provides a kind of large database concept foundation sides of interpreter's behavior
Method is the flow diagram of the large database concept method for building up for interpreter's behavior that one embodiment of the invention provides, the party with reference to Fig. 1
Method can be realized by a computer program, comprising:
S101, the external system record data based on interpreter assemble the behavioral data of interpreter using opening API technology.
It is to be understood that external system can recorde these when interpreter carries out some behaviors operation by external system
Operation data records data as the external system of interpreter, or may be some intrinsic categories that interpreter inherently has
Property information.Then, for external system, open applications Program Interfaces (Open Application can be used
Programming Interface, Open API) technology, collect the behavioral data of interpreter.The behavioral data of interpreter can be for such as
Basic data, task behavioral data, evaluation behavioral data, capacity data, empirical data and credit data of interpreter etc..
It is understood that wherein external system refers to the platform of interpreter's work, system is established relative to this large database concept
It is data acquisition source platform for external system.It can be any other systems for wanting to access data acquisition system.
S102 handles behavioral data with the storage model of big data, forms the large database concept of interpreter's behavior.
It is to be understood that needing to establish a large database concept after the behavioral data for getting interpreter according to above-mentioned steps
These behavioral datas are handled and stored.I.e., it is possible to by the behavioral data being collected into the storage mould of general big data
Type is handled, can also be with customized big data storage model, and uses customized big data storage model to behavioral data
It is handled.Processing result obtains the large database concept of a behavioral data comprising all interpreters, the as big number of interpreter's behavior
According to library.
The large database concept method for building up of interpreter's behavior provided in an embodiment of the present invention, by using opening API technology to
The behavioral data at family is assembled, and by establishing large database concept logical architecture, to the data of aggregation with the storage mould of big data
Type is handled, and the large database concept of interpreter's behavior is established, and depth can grasp interpreter's information to greatest extent, and translation is provided
Source can be used by sufficiently shared, improve the utilization rate of resource.
Fig. 2 be another embodiment of the present invention provides interpreter's behavior large database concept method for building up flow diagram, root
According to above-described embodiment, the method for the embodiment of the present invention uses the mode of opening API, collects interpreter's behavioural information, and by information with
The storage model of big data is handled.And the behavioral data of interpreter may include: interpreter's basic data, task behavioral data,
Evaluate behavioral data, capacity data, empirical data or credit data etc..
Wherein, according to the above embodiments optionally, the behavioral data of interpreter can specifically include the essential information of interpreter
Data, task behavioral data, evaluation behavioral data, capacity data, empirical data, credit data, translation tool data, translation are inclined
Good and log in/exit one or more of data.
Wherein, according to the above embodiments optionally, step behavioral data handled with the storage model of big data
Suddenly further comprise: building have by bottom framework to upper layer framework include acquisition layer, database layer, tap layer, knowledge base layer,
The large database concept logical architecture of service layer and application layer, and the service logic of each logical layer is defined respectively；To behavioral data, according to
Large database concept logical architecture and service logic are stored.
The embodiment of the present invention carries out the logic frame of large database concept when establishing to the large database concept of interpreter's behavior first
Structure design, then the behavioral data of interpreter is stored by designed logical architecture.Specifically, first designing one from the bottom to top
A large database concept logic with acquisition layer, database layer, tap layer, six knowledge base layer, service layer and application layer logical layers
Framework, then the service logic of each logical layer is defined respectively, it such as defines acquisition layer and is used to use opening API technology or crawler
Technology collects the behavioral data etc. of interpreter.
Fig. 3 is to be patrolled according to the large database concept that the large database concept method for building up of interpreter's behavior provided in an embodiment of the present invention constructs
The structural schematic diagram of volume framework, it is seen that be divided into six levels in figure from the bottom to top, respectively acquisition layer, database layer, tap layer,
Knowledge base layer, service layer and application layer all have certain logic connecting relation between each level inside and variant level.
Later, it according to the service logic of the large database concept logical architecture of building and each layer logical layer of definition, will be collected into
The behavioral data of interpreter store, form the large database concept of final interpreter's behavior.
Wherein, according to the above embodiments optionally, the step of defining the service logic of each logical layer respectively is further wrapped
It includes:
The service logic for defining acquisition layer includes: to collect the behavior number of interpreter using opening API technology or crawler technology
According to, and behavioral data is transmitted to database layer；
The service logic for defining database layer includes: that behavior number is stored in the form of big data using NOSQL database
According to；
The service logic of definition mining layer includes: to clean, process to the behavioral data of interpreter, extracts the difference of interpreter
Gene, and by gene delivery to knowledge base layer；
The service logic for defining knowledge base layer includes: to store to gene, and provide gene for service layer and application layer；
The service logic for defining service layer includes: the api interface service provided to gene；
The service logic for defining application layer includes: to provide the APP application based on gene.
It is to be understood that as shown in figure 3, carrying out industry respectively for each different levels in large database concept logical architecture
Business logical definition.Specifically:
Acquisition layer is mainly used for collecting interpreter's initial data by opening API or crawler technology, and by initial data into
Enter database layer；
Database layer mainly uses NOSQL database to store the behavioral data of magnanimity interpreter in a manner of big data, different
Behavioral data can carry the basic information of interpreter, ability information, credit information, posterior infromation, mission bit stream, evaluation letter
It ceases, log in/exit the behavioural informations such as operation information, translation tool or translation preference；
Tap layer is cleaned the data in original library by tool, algorithm mainly according to interpreter's genetic model, and is added
Work obtains available data, such as the gene of interpreter, and flows into knowledge base layer；
Knowledge base layer is that height can debate knowledge, workable interpreter's information pool, can knowledge based library layer various API clothes are provided upwards
APP is applied in business；
Service layer mainly provides the API service used based on resource, for example, the matching service of intelligent recommendation API service, gene
Deng；
Application layer mainly provides the APP used based on resource, for example, resource intelligent search APP, resources index APP etc..
Further, on the basis of the various embodiments described above, to behavioral data, according to large database concept logical architecture and industry
After the step of business logic is stored, the method for the embodiment of the present invention further include: definition is in the large database concept of interpreter's behavior
The processing logic of big data includes data capture logic, importing/pretreatment logic, statistical analysis logic and data mining logic.
Fig. 4 is at the big data according to defined in the large database concept method for building up of interpreter's behavior provided in an embodiment of the present invention
The flow diagram of logic is managed, including data capture logic, importing/pretreatment logic, statistical analysis logic and data mining are patrolled
Collect four processes.The large database concept of interpreter's behavior is stored fully according to the model of big data, and according to the process flow of big data
It is handled with principle.
As shown in figure 4, the data in multiple heterogeneous data sources are passed through into automatic collection mechanism in data capture logic, into
Enter the original library of big data system.Industry universal technical solution generally uses NOSQL database, such as hadoop, MongoDB etc..
It in importing/pretreatment logic, is effectively analyzed in order to the big data to magnanimity, initial data is imported into concentration
Large-scale distributed database, and some simple cleanings and pretreatment work can be done on the basis of importing.Statistical analysis
In logic, statistics mainly utilizes distributed data base with analysis, to storage mass data in the inner carry out common analysis and
Classifying Sum etc., to meet most of common analysis demands.It is different from front statistics and analysis process in data mining logic
, carry out based on various calculations what typically no pre-set theme of data mining mainly on available data
The calculating of method to play the effect of prediction, and then realizes that the demand of some high-level data analyses (common are clustering algorithm
Deng).
Further, on the basis of the various embodiments described above, the step of defining the service logic of each logical layer respectively it
Afterwards, the method for the embodiment of the present invention further include: carry out the open system API design based on event model.
It is to be understood that the embodiment of the present invention also carries out open system API design, and open system API is based on event mould
Type, is the external api interface for providing data and acquiring, and API, interpreter for example including interpreter's log-in events submit the API etc. of the manuscript of a translation.
Its principle is as shown in figure 5, for according to open system in the large database concept method for building up of interpreter's behavior provided in an embodiment of the present invention
The schematic illustration of API design, wherein event triggering can call opening API in external each business platform, by data-pushing
To the large database concept of interpreter's behavior, common parameter is that each event all has to incoming parameter, and individual business parameter is then
It is different according to event occurred, it is passed to json string value difference, system can define many events.
Wherein, the definition example reference table 1 of common parameter, for the common parameter example defined according to the embodiment of the present invention
Table is illustrated meaning of parameter name and parameter etc. respectively in table.
Table 1, the common parameter sample table defined according to embodiments of the present invention
Wherein, the definition example of system event is as shown in table 2, for the system event example defined according to the embodiment of the present invention
Table, interpreter's behavior large database concept system are that opening API defines many events, and has carried out the detailed of parameters for event
Explanation.
Table 2, the system event sample table defined according to embodiments of the present invention
Fig. 6 is to define according in the large database concept method for building up of interpreter's behavior provided in an embodiment of the present invention to system event
Code schematic diagram, be it is some it is interface related illustrate document, be shown to be the acquisition based on event.
Wherein, when carrying out open system API design, definition is also needed to call API specification.In order to facilitate the use of API, originally
Inventive embodiments are flowed back data using the mode of the multiple events of unique interface.As shown in fig. 7, to be provided according to the embodiment of the present invention
Interpreter's behavior large database concept method for building up in definition call API specification calling specification and call example schematic diagram, wherein
Fig. 7 (a) is the code schematic diagram for calling specification, and Fig. 7 (b) is to call exemplary code schematic diagram.It is that some interfaces are related in Fig. 7
Illustrate document.
Fig. 8 is the return according to API Calls in the large database concept method for building up of interpreter's behavior provided in an embodiment of the present invention
Status diagram.It is equally some interface related to illustrate document in Fig. 8.
As the other side of the embodiment of the present invention, the embodiment of the present invention provides a kind of interpreter according to the above embodiments
The large database concept of behavior establishes device, and the device for realizing building to the large database concept of interpreter's behavior in the above embodiments
It is vertical.Therefore, the description and definition in the large database concept method for building up of interpreter's behavior of the various embodiments described above, can be used for this hair
The understanding of each execution module in bright embodiment, specifically refers to above-described embodiment, is not repeating herein.
One embodiment of present aspect embodiment according to the present invention, the large database concept of interpreter's behavior establish the structure of device such as
Shown in Fig. 9, the structural schematic diagram of device is established for the large database concept of interpreter's behavior provided in an embodiment of the present invention, which can be with
For the foundation to the large database concept of interpreter's behavior in above-mentioned each method embodiment, which includes 901 He of data acquisition module
Output module 902.Wherein:
Data acquisition module 901 records data for the external system based on interpreter, and using opening API technology, aggregation is translated
The behavioral data of member；Output module 902 forms interpreter's behavior for handling behavioral data with the storage model of big data
Large database concept.
When interpreter carries out some behaviors operation by external system, external system can recorde these operation datas, i.e.,
External system as interpreter records data, or may be some build-in attribute information that interpreter inherently has.Then, right
In external system, data acquisition module 901 can use open applications Program Interfaces (Open Application
Programming Interface, Open API) technology, collect the behavioral data of interpreter.The behavioral data of interpreter can be for such as
Basic data, task behavioral data, evaluation behavioral data, capacity data, empirical data or credit data of interpreter etc..
Output module 902 then can establish a large database concept and these behavioral datas handled and stored.That is, output
Module 902 can be handled the behavioral data being collected into the storage model of general big data, can also be with customized big
Data Storage Models, and behavioral data is handled using customized big data storage model.The processing of output module 902
As a result the large database concept of the behavioral data comprising all interpreters, the as large database concept of interpreter's behavior are obtained.
The lookup device of similar case history provided in an embodiment of the present invention, by the way that corresponding execution module is arranged, using opening
API technology assembles the behavioral data of user, and by establishing large database concept logical architecture, to the data of aggregation to count greatly
According to storage model handled, establish the large database concept of interpreter's behavior, can to greatest extent depth grasp interpreter's information, and
Translated resources are used by sufficiently shared, improve the utilization rate of resource.
It is understood that can be by hardware processor (hardware processor) come real in the embodiment of the present invention
Each relative program module in the device of existing the various embodiments described above.Also, the large database concept of interpreter's behavior of the embodiment of the present invention
Establish when the establishing of large database concept of device interpreter's behavior in above-mentioned each method embodiment, the beneficial effect of generation with it is corresponding
Above-mentioned each method embodiment it is identical, can refer to above-mentioned each method embodiment, details are not described herein again.
As the another aspect of the embodiment of the present invention, the present embodiment provides a kind of electronics according to the above embodiments and sets
It is standby, it is the entity structure schematic diagram of electronic equipment provided in an embodiment of the present invention, comprising: at least one processor with reference to Figure 10
1001, at least one processor 1002, communication interface 1003 and bus 1004.
Wherein, memory 1001, processor 1002 and communication interface 1003 complete mutual communication by bus 1004,
Communication interface 1003 is for the information transmission between the electronic equipment and external system api interface equipment；It is deposited in memory 1001
The computer program that can be run on processor 1002 is contained, when processor 1002 executes the computer program, is realized as above-mentioned
The large database concept method for building up of interpreter's behavior of embodiment.
It is to be understood that including at least memory 1001, processor 1002, communication interface 1003 and total in the electronic equipment
Line 1004, and memory 1001, processor 1002 and communication interface 1003 form mutual communication connection by bus 1004,
And achievable mutual communication, as processor 1002 reads the large database concept method for building up of interpreter's behavior from memory 1001
Program instruction etc..In addition, communication interface 1003 can also be realized between the electronic equipment and external system api interface equipment
Communication connection, and achievable mutual information transmission, such as build the large database concept of interpreter's behavior by the realization of communication interface 1003
It stands.
When electronic equipment is run, processor 1002 calls the program instruction in memory 1001, to execute above-mentioned each method
Method provided by embodiment, for example, the external system based on interpreter records data, and using opening API technology, aggregation is translated
The behavioral data of member；Behavioral data is handled with the storage model of big data, forms the large database concept etc. of interpreter's behavior.
Program instruction in above-mentioned memory 1001 can be realized and as independence by way of SFU software functional unit
Product when selling or using, can store in a computer readable storage medium.Alternatively, realizing that above-mentioned each method is real
Applying all or part of the steps of example, this can be accomplished by hardware associated with program instructions, and program above-mentioned can store in a meter
In calculation machine read/write memory medium, when being executed, execution includes the steps that above-mentioned each method embodiment to the program；And it above-mentioned deposits
Storage media includes: USB flash disk, mobile hard disk, read-only memory (Read-Only Memory, ROM), random access memory
The various media that can store program code such as (Random Access Memory, RAM), magnetic or disk.
The embodiment of the present invention provides a kind of non-transient computer readable storage medium also according to the various embodiments described above, this is non-temporarily
State computer-readable recording medium storage computer instruction, the computer instruction make computer execute translating such as the various embodiments described above
The large database concept method for building up of member's behavior.For example, external system based on interpreter records data, using opening API technology,
Assemble the behavioral data of interpreter；Behavioral data is handled with the storage model of big data, forms the big data of interpreter's behavior
Library etc..
Electronic equipment provided in an embodiment of the present invention and non-transient computer readable storage medium, by using opening API
Technology assembles the behavioral data of user, and by establishing large database concept logical architecture, to the data of aggregation with big data
Storage model handled, establish the large database concept of interpreter's behavior, depth can grasp interpreter's information to greatest extent, and make
Obtaining translated resources can be used by sufficiently shared, improve the utilization rate of resource.
As another aspect of the embodiment of the present invention, the present embodiment provides a kind of interpreter's behavior according to the above embodiments
Large database concept, with reference to Figure 11, the system structure diagram of the large database concept of the interpreter's behavior provided for one embodiment of the invention,
The large database concept is used to be collected the behavioral data of interpreter, store and share etc., which includes: original library cluster
Module 1101, achievement library cluster module 1102 and application library cluster module 1103.Wherein:
Original library cluster module 1101 is used to use NOSQL MongoDB database, deposits to the behavioral data of interpreter
Storage；Achievement library cluster module 1102 is used to use ORALCE database, stores to the gene of the interpreter of extraction；Application library collection
Group's module 1103 is used to use MYSQL ORACLE database, store again after polymerization synchronizes to the gene of interpreter.
Specifically, as shown in figure 11, the large database concept of interpreter's behavior includes at least three kinds of component parts, i.e., original library collection
Group's module 1101, achievement library cluster module 1102 and application library cluster module 1103, in which:
It for original library cluster module 1101, is made of one or more original library, is multiple original libraries
Cluster.It is understood that being flexibly extended in order to more convenient, original library uses high-performance NOSQL MongoDB number
According to library.MongoDB is a kind of database based on distributed document storage, is write by C Plus Plus, it is intended to be WEB application
Expansible high-performance data storage solution is provided, its main feature is that high-performance, easily deployment, easily use, storing data is very
It is convenient.
It for achievement library cluster module 1102, is made of one or more achievement library, is multiple achievement libraries
Cluster.Data in achievement library are all by " gold mine " workable for after excavating, cleaning.The behavior of interpreter in achievement library
Data have only carried out first layer data mining and aggregation, and further mass data is excavated for convenience, and achievement library uses
ORALCE database.
It for application library cluster module 1103, is made of one or more application library, is multiple application libraries
Cluster.More, more complicated excavation and aggregation are carried out in application library to the behavioral data of interpreter, specific to business and can be taken out
As processing.It is understood that each business is due to the service logic of itself, the difference for the treatment of process, Data View and knot
Structure will be different, and application library is that the synchronous result of higher level polymerization is carried out by achievement library.Application library is according to each business system
System is different, can take MYSQL ORACLE database etc..
Further, can refer to Figure 12, for another embodiment of the present invention provides interpreter's behavior large database concept system
Structural schematic diagram, the large database concept of interpreter's behavior includes three region contents, respectively original base area, achievement base area in figure
With apply base area.Data in original library obtain the base of interpreter through processing means such as data analysis, excavation and surface cleanings
Cause is stored into achievement library.In practical applications, the aggregated synchronization of gene data in achievement library, is applied to service application
Layer, external system carry out source to resource information in application process by accessing using API to the data in database
Source is constantly improved and is excavated, and is acquired especially by behavioral data of the applications channel to interpreter in application process, comes
It improves and the data in more new database.
The large database concept of interpreter's behavior provided in an embodiment of the present invention, the behavior by using opening API technology to user
Data are assembled, and by establishing large database concept logical architecture, to the data of aggregation with the storage model of big data at
Reason, establish the large database concept of interpreter's behavior, can to greatest extent depth grasp interpreter's information, and enable translated resources by
It is sufficiently shared to use, improve the utilization rate of resource.
It is understood that the embodiment of device described above, electronic equipment and storage medium is only schematic
, wherein unit may or may not be physically separated as illustrated by the separation member, it can both be located at one
Place, or may be distributed on heterogeneous networks unit.Some or all of modules can be selected according to actual needs
To achieve the purpose of the solution of this embodiment.Those of ordinary skill in the art are without paying creative labor
To understand and implement.
By the description of embodiment of above, those skilled in the art is it will be clearly understood that each embodiment can borrow
Help software that the mode of required general hardware platform is added to realize, naturally it is also possible to pass through hardware.Based on this understanding, above-mentioned
Substantially the part that contributes to existing technology can be embodied in the form of software products technical solution in other words, the meter
Calculation machine software product may be stored in a computer readable storage medium, such as USB flash disk, mobile hard disk, ROM, RAM, magnetic disk or light
Disk etc., including some instructions, with so that a computer equipment (such as personal computer, server or network equipment etc.)
Execute method described in certain parts of above-mentioned each method embodiment or embodiment of the method.
In addition, those skilled in the art are it should be understood that in the application documents of the embodiment of the present invention, term
"include", "comprise" or any other variant thereof is intended to cover non-exclusive inclusion, so that including a series of elements
Process, method, article or equipment not only include those elements, but also including other elements that are not explicitly listed, or
Person is to further include for elements inherent to such a process, method, article, or device.In the absence of more restrictions, by
The element that sentence "including a ..." limits, it is not excluded that in the process, method, article or apparatus that includes the element
There is also other identical elements.
In the specification of the embodiment of the present invention, numerous specific details are set forth.It should be understood, however, that the present invention is implemented
The embodiment of example can be practiced without these specific details.In some instances, it is not been shown in detail well known
Methods, structures and technologies, so as not to obscure the understanding of this specification.Similarly, it should be understood that in order to simplify implementation of the present invention
Example is open and helps to understand one or more of the various inventive aspects, above to the exemplary embodiment of the embodiment of the present invention
Description in, each feature of the embodiment of the present invention is grouped together into single embodiment, figure or descriptions thereof sometimes
In.
However, the disclosed method should not be interpreted as reflecting the following intention: i.e. the claimed invention is implemented
Example requires features more more than feature expressly recited in each claim.More precisely, such as claims institute
As reflection, inventive aspect is all features less than single embodiment disclosed above.Therefore, it then follows specific embodiment party
Thus claims of formula are expressly incorporated in the specific embodiment, wherein each claim itself is real as the present invention
Apply the separate embodiments of example.
Finally, it should be noted that above embodiments are only to illustrate the technical solution of the embodiment of the present invention, rather than it is limited
System；Although the embodiment of the present invention is described in detail with reference to the foregoing embodiments, those skilled in the art it is understood that
It is still possible to modify the technical solutions described in the foregoing embodiments, or part of technical characteristic is carried out etc.
With replacement；And these are modified or replaceed, each embodiment skill of the embodiment of the present invention that it does not separate the essence of the corresponding technical solution
The spirit and scope of art scheme.
Claims (10)
1. a kind of large database concept method for building up of interpreter's behavior characterized by comprising
External system record data based on interpreter assemble the behavioral data of interpreter using opening API technology；
The behavioral data is handled with the storage model of big data, forms the large database concept of interpreter's behavior.
2. the method according to claim 1, wherein the behavioral data of interpreter specifically includes the basic of interpreter
Information data, evaluation behavioral data, capacity data, empirical data, credit data, translation tool data, is turned over task behavioral data
Translate preference and log in/exit one or more of data.
3. the method according to claim 1, wherein it is described by the behavioral data with the storage model of big data
The step of being handled further comprises:
Building have by bottom framework to upper layer framework include acquisition layer, database layer, tap layer, knowledge base layer, service layer and
The large database concept logical architecture of application layer, and the service logic of each logical layer is defined respectively；
To the behavioral data, stored according to the large database concept logical architecture and the service logic.
4. according to the method described in claim 3, it is characterized in that, the step of the service logic for defining each logical layer respectively
Further comprise:
The service logic for defining the acquisition layer includes: to collect the behavior of interpreter using opening API technology or crawler technology
Data, and the behavioral data is transmitted to the database layer；
The service logic for defining the database layer includes: that the behavior is stored in the form of big data using NOSQL database
Data；
The service logic for defining the tap layer includes: to clean, process to the behavioral data of interpreter, extracts interpreter's
Different genes, and by the gene delivery to the knowledge base layer；
The service logic for defining the knowledge base layer includes: to store to the gene, and for the service layer and described answer
The gene is provided with layer；
The service logic for defining the service layer includes: the api interface service provided to the gene；
The service logic for defining the application layer includes: to provide the APP application based on the gene.
5. according to the method described in claim 3, it is characterized in that, described to the behavioral data, according to the big data
After the step of library logical architecture and the service logic are stored, further includes:
Definition includes data capture logic to the processing logic of big data in the large database concept of interpreter's behavior, imports/locate in advance
Manage logic, statistical analysis logic and data mining logic.
6. according to the method described in claim 3, it is characterized in that, the service logic for defining each logical layer respectively step
After rapid, further includes:
Carry out the open system API design based on event model.
7. a kind of large database concept of interpreter's behavior establishes device characterized by comprising
Data acquisition module assembles the row of interpreter using opening API technology for the external system record data based on interpreter
For data；
Output module forms interpreter's behavior for handling the behavioral data with the storage model of big data
Large database concept.
8. a kind of electronic equipment characterized by comprising at least one processor, at least one processor, communication interface and total
Line；
The memory, the processor and the communication interface complete mutual communication, the communication by the bus
Interface is for the information transmission between the electronic equipment and external system api interface equipment；
The computer program that can be run on the processor is stored in the memory, the processor executes the calculating
When machine program, the method as described in any in claim 1 to 6 is realized.
9. a kind of non-transient computer readable storage medium, which is characterized in that the non-transient computer readable storage medium is deposited
Computer instruction is stored up, the computer instruction makes the computer execute the method as described in any in claim 1 to 6.
10. a kind of large database concept of interpreter's behavior characterized by comprising
Original library cluster module stores the behavioral data of interpreter for using NOSQL MongoDB database；
Achievement library cluster module stores the gene of the interpreter of extraction for using ORALCE database；
Application library cluster module carries out polymerization synchronization to the gene of interpreter for using MYSQL ORACLE database
It is stored again afterwards.
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