CN112347054A - Personnel information comparison method, system, electronic equipment and computer readable storage medium - Google Patents
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Abstract
The invention discloses a personnel information comparison method, a personnel information comparison system, electronic equipment and a computer readable storage medium, wherein the method comprises the following steps: uploading a comparison file by a user; comparing the data of the files based on a preset comparison model; if the preset comparison model cannot meet the application scene of the comparison file, manually adding the comparison model; and comparing the data in the comparison file with the data in the comparison model to generate information meeting the requirements. The method is characterized in that data processing comparison is carried out based on the built-in comparison model DAG, if the built-in comparison model DAG does not meet the complex business scene, the customized model can be used in a user-defined mode, so that the requirement of basic data comparison is met, and meanwhile, the complex business scene is better supported.
Description
Technical Field
The present invention relates to the field of data processing technologies, and in particular, to a method and a system for comparing personal information, an electronic device, and a computer-readable storage medium.
Background
Due to the rapid development of informatization, the amount of data has increased dramatically, and the need for a function based on mining analysis of a large amount of data has increased. If a user wants to perform service check on a certain type of batch service data aggregated at multiple places and original data in a database to obtain required table data, a comparison screening technology can be applied to solve the requirement.
The comparison screening function is an application process of comparing information in actual combat, data comparison and analysis are rapidly performed in a visual operation mode, so that an analyst is helped to quickly compare and collide information meeting requirements from mass information, and various characters, time, event sequences, incidence relations and available clues related to the clue information are analyzed.
At present, when personnel information is compared and screened, common general personnel comparison models are generally set in advance and are used when the existing models are processed. The method can adapt to the existing use scenes, but has no better expansibility, and the existing model most probably cannot meet all the scenes when new service data types and application scenes appear.
Disclosure of Invention
Aiming at the technical problem that the existing comparison model cannot meet the service requirement, the invention provides a personnel information comparison method, a personnel information comparison system, electronic equipment and a computer readable storage medium.
In a first aspect, an embodiment of the present application provides a method for comparing personal information, including:
file uploading: uploading a comparison file by a user;
data comparison step: performing data processing comparison on the comparison file based on a preset comparison model;
a model adding step: if the preset comparison model cannot meet the application scene of the comparison file, manually adding the comparison model;
a batch query step: and comparing the data in the comparison file with the data in the comparison model to generate information meeting the requirements.
The personnel information comparison method comprises the following steps of:
a new construction step: newly building a model name, and adding a model service introduction case;
a data combing step: generating an expansion operator based on the node operator of the general model;
and (3) DAG construction: and generating the comparison model based on a data table and a corresponding operator.
The personnel information comparison method comprises the following steps of:
an operator expanding step: expanding a node operator in the general model;
a general operator generating step: generating a new general model operator;
information configuration step: operator summary information and operator configuration conditions are built in the general model operator;
an expansion operator generating step: and generating an expansion operator based on the configured general model operator.
The personnel information comparison method comprises the following steps of DAG construction:
a data table adding step: dragging the data table into a DAG;
and (3) filtering: dragging a corresponding filter operator or a comparison logic operator in the DAG to filter the data table;
an output step: outputting the filtered data table;
a model selection step: and selecting a model corresponding to the scene to complete the construction of the DAG.
In a second aspect, an embodiment of the present application provides a personnel information comparison system, including:
the file uploading module: uploading a comparison file by a user;
a data comparison module: performing data processing comparison on the comparison file based on a preset comparison model;
a model adding module: if the preset comparison model cannot meet the application scene of the comparison file, manually adding the comparison model;
a batch query module: and comparing the data in the comparison file with the data in the comparison model to generate information meeting the requirements.
The personnel information comparison system, wherein the model adding module comprises:
newly building a unit: newly building a model name, and adding a model service introduction case;
a data combing unit: generating an expansion operator based on the node operator of the general model;
a DAG construction unit: and generating the comparison model based on a data table and a corresponding operator.
The personnel information comparison system, wherein, the data carding unit includes:
an operator extension unit: expanding a node operator in the general model;
a general operator generation unit: generating a new general model operator;
an information configuration unit: operator summary information and operator configuration conditions are built in the general model operator;
an extension operator generation unit: and generating an expansion operator based on the configured general model operator.
The personnel information comparison system, wherein the DAG construction unit includes:
a data table adding unit: dragging the data table into a DAG;
a filtering unit: dragging a corresponding filter operator or a comparison logic operator in the DAG to filter the data table;
an output unit: outputting the filtered data table;
a model selection unit: and selecting a model corresponding to the scene to complete the construction of the DAG.
In a third aspect, an embodiment of the present application provides an electronic device, which includes a memory, a processor, and a computer program stored on the memory and executable on the processor, where the processor executes the computer program to implement the people information matching method according to the first aspect.
In a fourth aspect, an embodiment of the present application provides a computer-readable storage medium, on which a computer program is stored, where the computer program, when executed by a processor, implements the method for comparing personal information according to the first aspect.
Compared with the prior art, the invention has the advantages and positive effects that:
1. in the process of comparing the uploaded file with the comparison model, data processing and comparison are firstly carried out on the basis of the built-in comparison model DAG, if the built-in comparison model DAG does not meet the complex business scene, matched models can be manually added on the basis of the current business scene to expand the model types, and the customized comparison model is applied in a user-defined mode.
2. In the comparison process of mass data, the basic of the existing comparison model is met, and meanwhile, the situation of complex service scenes can be met, so that the basic data comparison requirements can be met, multiple complex application scenes can be well supported, and an analyst can be helped to compare and collide information meeting the requirements from mass information quickly.
Drawings
FIG. 1 is a schematic diagram illustrating steps of a personnel information comparison method according to the present invention;
FIG. 2 is a flowchart of model addition based on step S3 in FIG. 1 according to the present invention;
FIG. 3 is a flow chart of data combing method based on step S32 in FIG. 2 according to the present invention;
FIG. 4 is a flow chart of DAG construction based on step S33 in FIG. 2 according to the present invention;
FIG. 5 is a schematic diagram of a custom uploaded comparison file uploaded to multiple comparison models;
FIG. 6 is a schematic diagram of a comparison model uploaded by a personnel information sheet;
FIG. 7 is a block diagram of a people information alignment system according to the present invention;
fig. 8 is a block diagram of a computer device according to an embodiment of the present application.
Wherein the reference numerals are:
100. a file uploading module; 200. a data comparison module; 300. a model adding module; 310. building a unit newly; 320. a data combing unit; 321. an operator extension unit; 322. a general operator generating unit; 323. an information configuration unit; 324. an expansion operator generating unit; 330. a DAG construction unit; 331. a data table adding unit; 332. a filtration unit; 333. an output unit; 334. a model selection unit; 400. a batch query module; 81. a processor; 82. a memory; 83. a communication interface; 80. a bus.
Detailed Description
In order to make the objects, technical solutions and advantages of the present application more apparent, the present application will be described and illustrated below with reference to the accompanying drawings and embodiments. It should be understood that the specific embodiments described herein are merely illustrative of the present application and are not intended to limit the present application. All other embodiments obtained by a person of ordinary skill in the art based on the embodiments provided in the present application without any inventive step are within the scope of protection of the present application.
It is obvious that the drawings in the following description are only examples or embodiments of the present application, and that it is also possible for a person skilled in the art to apply the present application to other similar contexts on the basis of these drawings without inventive effort. Moreover, it should be appreciated that in the development of any such actual implementation, as in any engineering or design project, numerous implementation-specific decisions must be made to achieve the developers' specific goals, such as compliance with system-related and business-related constraints, which may vary from one implementation to another.
Reference in the specification to "an embodiment" means that a particular feature, structure, or characteristic described in connection with the embodiment can be included in at least one embodiment of the specification. The appearances of the phrase in various places in the specification are not necessarily all referring to the same embodiment, nor are separate or alternative embodiments mutually exclusive of other embodiments. Those of ordinary skill in the art will explicitly and implicitly appreciate that the embodiments described herein may be combined with other embodiments without conflict.
Unless defined otherwise, technical or scientific terms referred to herein shall have the ordinary meaning as understood by those of ordinary skill in the art to which this application belongs. Reference to "a," "an," "the," and similar words throughout this application are not to be construed as limiting in number, and may refer to the singular or the plural. The present application is directed to the use of the terms "including," "comprising," "having," and any variations thereof, which are intended to cover non-exclusive inclusions; for example, a process, method, system, article, or apparatus that comprises a list of steps or modules (elements) is not limited to the listed steps or elements, but may include other steps or elements not expressly listed or inherent to such process, method, article, or apparatus. Reference to "connected," "coupled," and the like in this application is not intended to be limited to physical or mechanical connections, but may include electrical connections, whether direct or indirect. The term "plurality" as referred to herein means two or more. "and/or" describes an association relationship of associated objects, meaning that three relationships may exist, for example, "A and/or B" may mean: a exists alone, A and B exist simultaneously, and B exists alone. The character "/" generally indicates that the former and latter associated objects are in an "or" relationship. Reference herein to the terms "first," "second," "third," and the like, are merely to distinguish similar objects and do not denote a particular ordering for the objects.
The present invention is described in detail with reference to the embodiments shown in the drawings, but it should be understood that these embodiments are not intended to limit the present invention, and those skilled in the art should understand that functional, methodological, or structural equivalents or substitutions made by these embodiments are within the scope of the present invention.
Before describing in detail the various embodiments of the present invention, the core inventive concepts of the present invention are summarized and described in detail by the following several embodiments.
According to the invention, when the existing model cannot be well applied to the current scene in the data comparison process, a new comparison model which can be applied to the current application scene is manually added, so that various complex application scenes are met.
The first embodiment is as follows:
referring to fig. 1 to 6, this example discloses a specific implementation of a personnel information comparison method (hereinafter referred to as "method").
Specifically, as shown in fig. 1, the method disclosed in this embodiment mainly includes the following steps:
step S1: and uploading the comparison file by the user.
Specifically, as shown in fig. 5, N represents the custom uploaded alignment file, M represents a preset alignment model, and DAG represents the blood-level graph of the model.
Essentially, a DAG (Database Availability Group) is a Group of Database Availability, which is the basic component of the mailbox Server high Availability and site recovery framework built into Microsoft Exchange Server. On the other hand, a DAG is a set of mailbox servers (which may contain up to 16 mailbox servers) that host a set of databases that can provide the functionality to automatically perform database-level recovery from failures that affect a single server or database.
The DAG is the boundary of mailbox database replication, database and server switching and failover, and internal components called "activity managers". An activity manager running on each mailbox server manages switchover and failover in the DAG. Any server in the DAG may carry a copy of the mailbox database from any other server in the DAG. After a server is added to the DAG, the server, in cooperation with other servers in the DAG, provides the capability to automatically perform recovery from failures that affect the mailbox database (e.g., disk, server, or network failures). CCR and SCR merge and have evolved into a more unified high availability architecture, where DAG becomes an essential component. That is, a DAG is used whether to deploy a local-level or site-level high-availability and disaster-recoverable solution.
Then, step S2 is executed: and carrying out data processing comparison on the comparison file based on a preset comparison model.
Specifically, in the process of comparing the uploaded comparison file with the model, the processing N table adopts the constructed comparison data in the model M, which is generally some common general personnel comparison models set in advance, and if the built-in comparison model can meet the requirements of the current service scene, the required information can be directly screened from the current data.
Then, referring to fig. 2, step S3 is performed: and if the preset comparison model cannot meet the application scene of the comparison file, manually adding the comparison model.
Wherein, step S3 includes the following contents:
step S31: newly building a model name, and adding a model service introduction case;
specifically, the model name and the introduction scheme matched with the applicable scene of the model are added firstly, so that the method is favorable for visually knowing the newly-built model and is favorable for better applying the model subsequently.
Step S32: generating an expansion operator based on the node operator of the general model;
specifically, there is a common concept in stream processing and interactive query is "operator", which is called "Operation" in english, and can be mathematically interpreted as a mapping O of function space to function space: x- > X, which is actually a processing unit, often refers to a function, and when an operator is used, there are often inputs and outputs, and the operator completes the conversion of corresponding data, for example: group, Sort, etc. are operators.
The operator operation supported by the existing comparison model comprises the following steps: intersection operators, difference operators, union operators, filter operators, clear operators, complement operators and the like, and can expand operators and operations aiming at models of which the required operator operations are not in the existing operator operations.
Step S33: and generating the comparison model based on a data table and a corresponding operator.
Referring to fig. 3, step S32 includes the following steps:
step S321: expanding a node operator in the general model;
step S322: generating a new general model operator;
step S323: operator summary information and operator configuration conditions are built in the general model operator;
step S324: and generating an expansion operator based on the configured general model operator.
Referring to fig. 4, step S33 includes the following steps:
step S331: dragging the data table into a DAG;
step S332: dragging a corresponding filter operator or a comparison logic operator in the DAG to filter the data table;
step S333: outputting the filtered data table;
step S334: and selecting a model corresponding to the scene to complete the construction of the DAG.
For example, as shown in fig. 6, R represents a personnel information table, the personnel information table R and a corresponding filter operator or a comparison logic operator are dragged into a DAG, the operator is used to perform a filtering operation on the personnel information table, and finally, a suitable model is selected according to actual business requirements.
Then, step S4 is executed: and comparing the data in the comparison file with the data in the comparison model to generate information meeting the requirements.
Specifically, the data of the custom uploaded comparison file and the data of the added comparison model are set under certain conditions, and data comparison and analysis are rapidly performed in a visual operation mode, so that an analyst is helped to rapidly compare and collide information meeting requirements from mass information, and various characters, time, event sequences, incidence relations and available clues related to the clue information are analyzed.
Example two:
in combination with the method for comparing personal information disclosed in the first embodiment, the present embodiment discloses a specific implementation example of a personal information comparison system (hereinafter referred to as "system").
Referring to fig. 7, the system includes:
the file upload module 100: uploading a comparison file by a user;
the data comparison module 200: performing data processing comparison on the comparison file based on a preset comparison model;
the model addition module 300: if the preset comparison model cannot meet the application scene of the comparison file, manually adding the comparison model;
batch query module 400: and comparing the data in the comparison file with the data in the comparison model to generate information meeting the requirements.
Specifically, in the data comparison module 200, in the process of comparing the uploaded comparison file with the model, the processing N table adopts the constructed comparison data in the model M, and if the built-in comparison model can meet the requirements of the current service scene, the required information can be directly screened out from the current data.
Specifically, the model adding module 300 includes:
the new unit 310: and (5) newly building a model name and adding a model service introduction case.
Specifically, adding the model name and the introduction scheme matched with the applicable scene of the model in the new building unit 310 is beneficial to visually knowing the new model and better applying the model in the following process.
Data combing unit 320: and generating an expansion operator based on the node operator of the general model.
DAG construction unit 330: and generating the comparison model based on a data table and a corresponding operator.
Specifically, the data combing unit 320 includes:
operator extension unit 321: expanding a node operator in the general model;
the general operator generation unit 322: generating a new general model operator;
the information configuration unit 323: operator summary information and operator configuration conditions are built in the general model operator;
the extension operator generating unit 324: and generating an expansion operator based on the configured general model operator.
Specifically, there is a common concept in stream processing and interactive query is "operator", which is called "Operation" in english, and can be mathematically interpreted as a mapping O of function space to function space: x- > X, which is actually a processing unit, often refers to a function, and when an operator is used, there are often inputs and outputs, and the operator completes the conversion of corresponding data, for example: group, Sort, etc. are operators.
The operator operations supported by the existing model in the data combing unit 320 include: intersection operators, difference operators, union operators, filter operators, clear operators, complement operators and the like, and can expand operators and operations aiming at models of which the required operator operations are not in the existing operator operations.
Specifically, the DAG constructing unit 330 includes:
the data table addition unit 331: dragging the data table into a DAG;
the filtering unit 332: dragging a corresponding filter operator or a comparison logic operator in the DAG to filter the data table;
output unit 333: outputting the filtered data table;
model selecting unit 334: and selecting a model corresponding to the scene to complete the construction of the DAG.
Specifically, in the DAG constructing unit 330, the staff information table R and the corresponding filter operator or the comparison logic operator are dragged into the DAG, the staff information table is filtered by using the operator, and finally, a suitable model is selected according to the actual business requirement.
Specifically, in the batch query module 400, the data of the comparison file uploaded by the user-defined and the data of the added comparison model are set under certain conditions, and the data comparison and analysis are rapidly performed in a visual operation manner, so that the analyst is helped to rapidly compare and collide information meeting the requirements from the mass information, and analyze various persons, time, event sequences, association relations and available clues related to the clue information.
Please refer to the description of the first embodiment, which is not repeated herein, for the technical solutions of the same parts in the personnel information comparison system disclosed in the present embodiment and the personnel information comparison method disclosed in the first embodiment.
Example three:
referring to FIG. 8, this embodiment discloses an embodiment of a computer device. The computer device may comprise a processor 81 and a memory 82 in which computer program instructions are stored.
Specifically, the processor 81 may include a Central Processing Unit (CPU), or A Specific Integrated Circuit (ASIC), or may be configured to implement one or more Integrated circuits of the embodiments of the present Application.
The memory 82 may be used to store or cache various data files for processing and/or communication use, as well as possible computer program instructions executed by the processor 81.
The processor 81 reads and executes the computer program instructions stored in the memory 82 to implement any one of the people information comparing methods in the above embodiments.
In some of these embodiments, the computer device may also include a communication interface 83 and a bus 80. As shown in fig. 8, the processor 81, the memory 82, and the communication interface 83 are connected via the bus 80 to complete communication therebetween.
The communication interface 83 is used for implementing communication between modules, devices, units and/or equipment in the embodiment of the present application. The communication port 83 may also be implemented with other components such as: the data communication is carried out among external equipment, image/data acquisition equipment, a database, external storage, an image/data processing workstation and the like.
In addition, in combination with the personnel information comparison method in the foregoing embodiment, the embodiment of the present application may provide a computer-readable storage medium to implement. The computer readable storage medium having stored thereon computer program instructions; the computer program instructions, when executed by a processor, implement any one of the people information comparison methods in the above embodiments.
The technical features of the embodiments described above may be arbitrarily combined, and for the sake of brevity, all possible combinations of the technical features in the embodiments described above are not described, but should be considered as being within the scope of the present specification as long as there is no contradiction between the combinations of the technical features.
In summary, the beneficial effects of the invention are that, in the process of comparing the uploaded file with the comparison model, the data processing comparison is performed based on the built-in comparison model DAG, if the built-in comparison model DAG does not satisfy the complex business scenario, the model can be manually added to expand the model type, and the customized model is used in a self-defined manner. In the comparison process of mass data, the condition of complex service scenes can be met while the existing basis of the comparison model is met, and thus the application scenes can be well supported.
The above-mentioned embodiments only express several embodiments of the present application, and the description thereof is more specific and detailed, but not construed as limiting the scope of the invention. It should be noted that, for a person skilled in the art, several variations and modifications can be made without departing from the concept of the present application, which falls within the scope of protection of the present application. Therefore, the protection scope of the present patent shall be subject to the appended claims.
Claims (10)
1. A personnel information comparison method is characterized by comprising the following steps:
file uploading: uploading a comparison file by a user;
data comparison step: performing data processing comparison on the comparison file based on a preset comparison model;
a model adding step: if the preset comparison model cannot meet the application scene of the comparison file, manually adding the comparison model;
a batch query step: and comparing the data in the comparison file with the data in the comparison model to generate information meeting the requirements.
2. The people information comparison method of claim 1, wherein the model adding step comprises:
a new construction step: newly building a model name, and adding a model service introduction case;
a data combing step: generating an expansion operator based on the node operator of the general model;
and (3) DAG construction: and generating the comparison model based on a data table and a corresponding operator.
3. The personnel information comparison method of claim 2, wherein the data combing step comprises:
an operator expanding step: expanding a node operator in the general model;
a general operator generating step: generating a new general model operator;
information configuration step: operator summary information and operator configuration conditions are built in the general model operator;
an expansion operator generating step: and generating an expansion operator based on the configured general model operator.
4. The people information comparison method of claim 2, wherein the DAG construction step comprises:
a data table adding step: dragging the data table into a DAG;
and (3) filtering: dragging a corresponding filter operator or a comparison logic operator in the DAG to filter the data table;
an output step: outputting the filtered data table;
a model selection step: and selecting a model corresponding to the scene to complete the construction of the DAG.
5. A personnel information comparison system is characterized by comprising:
the file uploading module: uploading a comparison file by a user;
a data comparison module: performing data processing comparison on the comparison file based on a preset comparison model;
a model adding module: if the preset comparison model cannot meet the application scene of the comparison file, manually adding the comparison model;
a batch query module: and comparing the data in the comparison file with the data in the comparison model to generate information meeting the requirements.
6. The people information comparison system of claim 5, wherein the model adding module comprises:
newly building a unit: newly building a model name, and adding a model service introduction case;
a data combing unit: generating an expansion operator based on the node operator of the general model;
a DAG construction unit: and generating the comparison model based on a data table and a corresponding operator.
7. The personal information comparison system of claim 6, wherein the data combing unit comprises:
an operator extension unit: expanding a node operator in the general model;
a general operator generation unit: generating a new general model operator;
an information configuration unit: operator summary information and operator configuration conditions are built in the general model operator;
an extension operator generation unit: and generating an expansion operator based on the configured general model operator.
8. The personnel information comparison system of claim 6, wherein the DAG construction unit comprises:
a data table adding unit: dragging the data table into a DAG;
a filtering unit: dragging a corresponding filter operator or a comparison logic operator in the DAG to filter the data table;
an output unit: outputting the filtered data table;
a model selection unit: and selecting a model corresponding to the scene to complete the construction of the DAG.
9. An electronic device comprising a memory, a processor, and a computer program stored on the memory and executable on the processor, wherein the processor implements the people information matching method according to any one of claims 1 to 4 when executing the computer program.
10. A computer-readable storage medium on which a computer program is stored, the program, when executed by a processor, implementing the person information comparing method according to any one of claims 1 to 4.
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| CN110909039A (en) * | 2019-10-25 | 2020-03-24 | 北京华如科技股份有限公司 | Big data mining tool and method based on drag type process |
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