CN114969169A - Sign-in data monitoring method, device, equipment and storage medium - Google Patents
Sign-in data monitoring method, device, equipment and storage medium Download PDFInfo
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- G06F16/00—Information retrieval; Database structures therefor; File system structures therefor
- G06F16/20—Information retrieval; Database structures therefor; File system structures therefor of structured data, e.g. relational data
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- G06—COMPUTING; CALCULATING OR COUNTING
- G06F—ELECTRIC DIGITAL DATA PROCESSING
- G06F16/00—Information retrieval; Database structures therefor; File system structures therefor
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- G06F16/22—Indexing; Data structures therefor; Storage structures
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- G—PHYSICS
- G06—COMPUTING; CALCULATING OR COUNTING
- G06F—ELECTRIC DIGITAL DATA PROCESSING
- G06F16/00—Information retrieval; Database structures therefor; File system structures therefor
- G06F16/20—Information retrieval; Database structures therefor; File system structures therefor of structured data, e.g. relational data
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Abstract
The invention relates to the field of logistics, and discloses a method, a device, equipment and a storage medium for monitoring signing data, wherein the method comprises the following steps: acquiring order signing data and generating a first data report according to the order signing data; carrying out structuring processing on the first data report, carrying out data analysis on the data in the first data report after the structuring processing, and calculating corresponding sign-in timeliness data; adding the signing aging data into the first data report to generate a second data report; and performing visual conversion on the second data report to generate a corresponding first visual image model, and monitoring order signing data through the first visual image model. The method processes and analyzes the order signing data, and visually converts the analyzed data report, so that data visualization and automatic generation of abnormal event strategies are realized based on the converted visual model, and the signing efficiency is improved.
Description
Technical Field
The invention relates to the field of logistics, in particular to a method, a device, equipment and a storage medium for monitoring signing data.
Background
In the field of logistics, end-of-line logistics is a logistics activity for delivering packages to customers, namely, the stage of delivering the packages from a logistics end-of-line delivery site to customers. The yield of logistics orders is the core competitiveness of the express industry, and the yield of logistics orders is improved as the subject of constant express production, so that the yield of logistics orders is improved in terminal logistics distribution. And along with the increasing data processing requirements of the signed report forms, and the manual report form copying condition exists, the current dispatch task cannot be improved in the first time, and the dispatch timeliness is not improved greatly. An efficient and stable data processing method is urgently needed to process the signed data.
Disclosure of Invention
The invention provides a method, a device, equipment and a storage medium for monitoring signing data, which are used for carrying out fine, clear, definite and comprehensive management on the signing data of logistics orders in a data visualization mode.
The first aspect of the invention provides a method for monitoring signed data, which comprises the following steps: acquiring order signing data and generating a first data report according to the order signing data; structuring the first data report, analyzing the data in the first data report after the structuring, and calculating corresponding signing time-effect data; adding the signing aging data into the first data report to generate a second data report; and carrying out visual conversion on the second data report to generate a corresponding first visual image model, and monitoring order sign-in data through the first visual image model.
Optionally, in a first implementation manner of the first aspect of the present invention, the structuring the first data report, performing data analysis on data in the first data report after the structuring, and calculating corresponding receipt time-efficient data includes: acquiring a first operation aiming at a structure field in the first data report, and carrying out structural processing on the first data report based on the first operation; and inputting the order signing data to a regression model taking a structure field corresponding to the first operation as an independent variable based on a multiple regression analysis method to obtain signing aging data.
Optionally, in a second implementation manner of the first aspect of the present invention, before the visually converting the second datagram table to generate a corresponding first visual image model and monitoring order receipt data through the first visual image model, the method includes: rejecting abnormal order signing data in the second data report to obtain a third data report; traversing and combining the structure fields in the third data report, and converting the structure fields into first coordinate point data in a data conversion mode; substituting basic service parameters and the first coordinate point data into a graph drawing model to be converted into first pixel unit data; drawing the first pixel unit data into a second visual image model; and optimizing and extracting a function curve in the second visual image model as a reference quantity.
Optionally, in a third implementation manner of the first aspect of the present invention, the visually converting the second datagram table to generate a corresponding first visual image model, and monitoring the order receipt data through the first visual image model includes: acquiring a second operation aiming at any structure field in the second data report, wherein the structure field is converted into second coordinate point data in a data conversion mode; substituting the basic service parameters and the second coordinate point data into a graph drawing model to be converted into second pixel unit data; and drawing the second pixel unit data into a first visual image model for displaying, and monitoring the order signing data based on the first visual image model.
Optionally, in a fourth implementation manner of the first aspect of the present invention, the drawing and displaying the second pixel unit data into a first visual image model, and monitoring the order receipt data based on the first visual image model includes: drawing the second pixel unit data into a first visual image model and displaying the first visual image model; judging whether the coincidence rate of the function curve in the first visual image model and the corresponding reference quantity is lower than a preset coincidence threshold value or not; if yes, acquiring and displaying order signing data which is lower than a coincidence threshold value between the function curve and the reference quantity.
Optionally, in a fifth implementation manner of the first aspect of the present invention, after performing visual conversion on the second datagram table to generate a corresponding first visual image model and monitoring order receipt data through the first visual image model, the method includes:
separating signed order receipt data and non-signed order receipt data in the second data report, wherein the signed order receipt data comprises normal receipt data and abnormal receipt data; constructing a probability distribution model based on the second data report; dividing the probability distribution model into at least two partial local function images according to percentages; extracting an abnormal coordinate point corresponding to the local function image containing the most abnormal sign-in data; searching whether the order sign-in data which is not signed in exists in a preset radius range or not based on the abnormal coordinate point; if the order is not signed, judging that the order signing data which is not signed has abnormity.
Optionally, in a sixth implementation manner of the first aspect of the present invention, after the constructing a probability distribution model based on the second datagram table, the method includes: acquiring the distribution condition of the non-signed order signing data of different types in the probability distribution model; traversing and judging the distribution condition in the probability distribution models of different types to be aggregation or regression; if the abnormal reasons are aggregated, dispersing the abnormal reasons outside the aggregation; and if the abnormal reasons are regressed, dispersing the abnormal reasons in the preset unit length of the reference quantity.
The second aspect of the present invention provides a device for monitoring signing data, comprising: the data report generating module is used for acquiring order signing data and generating a first data report according to the order signing data; the structured processing module is used for carrying out structured processing on the first data report, carrying out data analysis on the data in the first data report after structured processing, and calculating corresponding signing-in aging data; the aging data adding module is used for adding the signing aging data into the first data report to generate a second data report; and the monitoring module is used for performing visual conversion on the second data report to generate a corresponding first visual image model, and monitoring order signing data through the first visual image model.
Optionally, in a first implementation manner of the second aspect of the present invention, the structural processing module is specifically configured to: acquiring a first operation aiming at a structure field in the first data report, and carrying out structural processing on the first data report based on the first operation; and inputting the order signing data to a regression model taking a structure field corresponding to the first operation as an independent variable based on a multivariate regression analysis method to obtain signing time-effect data.
Optionally, in a second implementation manner of the second aspect of the present invention, the signing data monitoring apparatus further includes a reference quantity generating module, where the reference quantity generating module is specifically configured to: rejecting abnormal order signing data in the second data report to obtain a third data report; traversing and combining the structure fields in the third data report, and converting the structure fields into first coordinate point data in a data conversion mode; substituting basic service parameters and the first coordinate point data into a graph drawing model to be converted into first pixel unit data; drawing the first pixel unit data into a second visual image model; and optimizing and extracting a function curve in the second visual image model as a reference quantity.
Optionally, in a third implementation manner of the second aspect of the present invention, the monitoring module is specifically configured to: the coordinate point conversion unit is used for acquiring a second operation aiming at any structure field in the second data report, and the structure field is converted into second coordinate point data in a data conversion mode; the pixel unit conversion unit substitutes the basic service parameters and the second coordinate point data into a graph drawing model to convert the graph drawing model into second pixel unit data; and the display monitoring unit is used for drawing the second pixel unit data into a first visual image model and displaying the first visual image model, and monitoring the order signing data based on the first visual image model.
Optionally, in a fourth implementation manner of the second aspect of the present invention, the display monitoring unit is specifically configured to: drawing the second pixel unit data into a first visual image model and displaying the first visual image model; judging whether the coincidence rate of the function curve in the first visual image model and the corresponding reference quantity is lower than a preset coincidence threshold value or not; if yes, acquiring and displaying order signing data which is lower than a coincidence threshold value between the function curve and the reference quantity.
Optionally, in a fifth implementation manner of the second aspect of the present invention, the signing data monitoring apparatus further includes an anomaly prediction module, where the anomaly prediction module is specifically configured to: the signed order signing data separation unit is used for separating signed order signing data and non-signed order signing data in the second data report, wherein the signed order signing data comprises normal signing data and abnormal signing data; the model building unit builds a probability distribution model based on the second data report table; a function image dividing unit that divides the probability distribution model into at least two partial local function images according to percentages; a coordinate point extracting unit that extracts an abnormal coordinate point corresponding to the local function image containing the maximum abnormal receipt data; the abnormal coordinate point searching unit is used for searching whether the order sign-in data which is not signed in exists in a preset radius range or not based on the abnormal coordinate point; and the prediction unit predicts that the order sign-in data which is not signed in has abnormity if the order sign-in data exists.
Optionally, in a sixth implementation manner of the second aspect of the present invention, the abnormality predicting module further includes an abnormality determining unit, where the abnormality determining unit is specifically configured to: acquiring the distribution condition of the non-signed order signing data of different types in the probability distribution model; traversing and judging the distribution conditions in the probability distribution models of different types to be aggregation or regression; if the abnormal reasons are aggregated, the abnormal reasons are scattered outside the aggregation; and if the abnormal reasons are regressed, dispersing the abnormal reasons in the preset unit length of the reference quantity.
A third aspect of the present invention provides a sign-off data monitoring apparatus, including: a memory having instructions stored therein and at least one processor, the memory and the at least one processor interconnected by a line; the at least one processor invokes the instructions in the memory to cause the signed data monitoring device to perform the steps of the signed data monitoring method described above.
A fourth aspect of the present invention provides a computer-readable storage medium having stored therein instructions, which, when run on a computer, cause the computer to perform the steps of the above-described method of monitoring signed-for data.
According to the technical scheme, order signing data are obtained, and a first data report is generated according to the order signing data; carrying out structuring processing on the first data report, carrying out data analysis on the data in the first data report after the structuring processing, and calculating corresponding sign-in timeliness data; adding the signing aging data into the first data report to generate a second data report; and carrying out visual conversion on the second data report to generate a corresponding first visual image model, and monitoring order sign-in data through the first visual image model. The method processes and analyzes the order signing data, and visually converts the analyzed data report, so that data visualization and automatic generation of abnormal event strategies are realized based on the converted visual model, and the signing efficiency is improved.
Drawings
FIG. 1 is a diagram of a first embodiment of a method for monitoring signed data according to an embodiment of the present invention;
FIG. 2 is a diagram of a second embodiment of a method for monitoring signed-in data according to the present invention;
FIG. 3 is a diagram of a third embodiment of a method for monitoring signed-in data according to an embodiment of the present invention;
FIG. 4 is a schematic diagram of an embodiment of a device for monitoring signed data according to an embodiment of the present invention;
FIG. 5 is a schematic diagram of another embodiment of a device for monitoring signed data according to the present invention;
fig. 6 is a schematic diagram of an embodiment of a device for monitoring signed data in the embodiment of the present invention.
Detailed Description
According to the technical scheme, order signing data are obtained, and a first data report is generated according to the order signing data; carrying out structuring processing on the first data report, carrying out data analysis on the data in the first data report after the structuring processing, and calculating corresponding sign-in timeliness data; adding the signing aging data into the first data report to generate a second data report; and carrying out visual conversion on the second data report to generate a corresponding first visual image model, and monitoring order sign-in data through the first visual image model. The method processes and analyzes the order signing data, and visually converts the analyzed data report, so that data visualization and automatic generation of abnormal event strategies are realized based on the converted visual model, and the signing efficiency is improved.
The terms "first," "second," "third," "fourth," and the like in the description and in the claims, as well as in the drawings, if any, are used for distinguishing between similar elements and not necessarily for describing a particular sequential or chronological order. It will be appreciated that the data so used may be interchanged under appropriate circumstances such that the embodiments described herein may be practiced otherwise than as specifically illustrated or described herein. Furthermore, the terms "comprises," "comprising," or "having," and any variations thereof, are intended to cover non-exclusive inclusions, such that a process, method, system, article, or apparatus that comprises a list of steps or elements is not necessarily limited to those steps or elements expressly listed, but may include other steps or elements not expressly listed or inherent to such process, method, article, or apparatus.
For convenience of understanding, a detailed flow of the embodiment of the present invention is described below, and referring to fig. 1, a first embodiment of a method for monitoring receipt data according to the embodiment of the present invention includes:
101, acquiring order sign-in data and generating a first data report according to the order sign-in data;
in this embodiment, the obtained order sign-off data includes, but is not limited to, the number of necessary parts, the number of already-sent parts, and the number of unportioned parts on the obtaining server, where the number of necessary parts includes the group quantity collecting total for group to be dispatched, the regional province quantity collecting total, and the business province quantity collecting total; the dispatched quantity of the numbers comprises dispatched total of the network points, dispatched total of the large area network points and dispatched total of the service province network points; the number of unportioned pieces includes the accumulated unportioned amount of the network points, the accumulated unportioned amount of the large area network points, and the accumulated unportioned amount of the service provincial network points. The necessary number of delivered pieces, the number of delivered pieces and the number of unportioned pieces are used for generating a data report, so that the signing-in condition of the logistics order at the present stage can be clearly and comprehensively understood.
Specifically, the order signing data are converted into a first data report for subsequent visual conversion and data analysis.
102, structuring the first data report, analyzing data in the first data report after structuring, and calculating corresponding sign-in time data;
in this embodiment, the data report is structured, and the structure fields are serial number, allocation, allocated, not allocated, signed yield, and accumulated not allocated, and support the sorting according to signed yield and accumulated not allocated, and the default sorting is in descending order according to accumulated not allocated; and estimating the model parameters by using the data samples in the report by using a multivariate regression analysis method, carrying out hypothesis test on the model parameters, and finally predicting the dependent variable by using a regression model. The statistical analysis method for establishing the linear or nonlinear mathematical model quantity relation among a plurality of variables and analyzing by using sample data can deal with a large amount of logistics order sign-in data and accurately calculate the sign-in time.
103, adding the signing aging data into the first data report to generate a second data report;
and 104, performing visual conversion on the second data report to generate a corresponding first visual image model, and monitoring order sign-in data through the first visual image model.
In this embodiment, fields in the data report are screened, then data are explored and subjected to correlation analysis, and data transformation is performed according to the requirement of the algorithm model on the data. Data transformation converts data into coordinate point data suitable for drawing graphics by means of data smoothing, data aggregation, data generalization and normalization, and the like. Calculating coordinate point data of the drawing graph; inputting the basic service parameters and the coordinate point data into a data processing model corresponding to the test for operation processing to obtain drawing element data; inputting the drawing element data into a graphic drawing model corresponding to the test and converting the drawing element data into pixel unit data; and drawing a graph to be drawn by the pixel unit data.
In the embodiment, order signing data are obtained, and a first data report is generated according to the order signing data; carrying out structuring processing on the first data report, carrying out data analysis on the data in the first data report after the structuring processing, and calculating corresponding sign-in timeliness data; adding the signing aging data into the first data report to generate a second data report; and carrying out visual conversion on the second data report to generate a corresponding first visual image model, and monitoring order sign-in data through the first visual image model. The method processes and analyzes the order signing data, and visually converts the analyzed data report, so that data visualization and automatic generation of abnormal event strategies are realized based on the converted visual model, and the signing efficiency is improved.
Referring to fig. 2, a second embodiment of the method for monitoring signed data according to the embodiment of the present invention includes:
201, acquiring order signing data, and generating a first data report according to the order signing data;
202, carrying out structuring processing on the first data report, carrying out data analysis on the data in the first data report after structuring processing, and calculating corresponding sign-in time-effect data;
203, adding the signing aging data into the first data report to generate a second data report;
204, rejecting abnormal order signing data in the second data report to obtain a third data report;
in this embodiment, in order to obtain the reference quantity in the subsequent step, the abnormal order signing data in the second data report needs to be removed, and only the order signing data that is normally signed is reserved as the third data report.
Specifically, the abnormal order receipt data includes, but is not limited to, delivery time overdue, delivery time too short, failure to normally receive, delivery error, failure to correctly deliver to a designated site, etc., or a large number of orders and different delivery modes may be selectively included according to statistical requirements.
205, traversing and combining the structure fields in the third data report, and converting the structure fields into first coordinate point data in a data conversion mode;
in this embodiment, the corresponding coordinate system and the corresponding first coordinate point data are generated by combining the structure fields in the order receipt data for any structure field in the third data report, for example, the delivery time and the delivery distance, the delivery time and the number of related websites, the order category and the delivery time, and the like. Wherein each order receipt data corresponds to a first coordinate point data.
206, substituting the basic service parameter and the first coordinate point data into the graph drawing model to be converted into first pixel unit data;
in the embodiment, basic service parameters and first coordinate point data are input into a data processing model corresponding to a test for operation processing, and pixel unit data are obtained; and summarizing the pixel unit data to obtain a graph to be drawn. And finally, generating a set of visual AI data preview model. 207, drawing the first pixel unit data into a second visual image model;
208, optimizing and extracting a function curve in the second visual image model as a reference quantity;
in this embodiment, the optimization refers to aggregating discrete coordinate points into a function curve with a specific rule through data smoothing, data aggregation, data generalization, normalization, and other manners, and obtaining a reasonable function formula expression based on a specific combination of structure fields by extracting a function formula corresponding to the function curve.
Specifically, by obtaining a function formula corresponding to the specific structure field, when order sign-off data is introduced subsequently, by checking the position of a coordinate point corresponding to the order sign-off data in a coordinate system, order sign-off time is predicted, researched and monitored.
209, acquiring a second operation aiming at any structure field in the second data report, wherein the structure field is converted into second coordinate point data in a data conversion mode;
in this embodiment, a combination of any structure fields selected by a user is obtained, a corresponding coordinate system is generated, and order receipt data in the second data is converted into second coordinate point data, where the second coordinate point data is stored in the order receipt data as a coordinate array or forms a mapping relationship with the order receipt data, so as to facilitate subsequent calling.
210, substituting the basic service parameter and the second coordinate point data into the graph drawing model to be converted into second pixel unit data;
in this embodiment, the basic service parameters include, but are not limited to, an order receipt data source, upload time, upload sites, customers, and the like, and by screening different basic service parameters, corresponding visualization models for different time periods, different regions, different delivery modes, and different customers are implemented.
211, drawing the second pixel unit data into a first visual image model and displaying the first visual image model;
in this embodiment, the screened second pixel unit data is aggregated and drawn into the first visual image model by obtaining the basic service parameters to be screened, and is displayed through the terminal.
212, determining whether the coincidence rate of the function curve in the first visual image model and the corresponding reference quantity is lower than a preset coincidence threshold value;
in this embodiment, when the obtained reference amount is given to the corresponding unspecific preset deviation range, it is determined whether order receipt data exceeding the preset deviation range exists in the brought order receipt data, or whether the order receipt data brought by the current batch is determined, and whether the reference amount in the generated first visual image model and the corresponding reference amount are lower than a certain coincidence threshold value. It is determined whether order receipt data exists or will be abnormal for the order.
The order exception can be embodied as any condition of exceeding the preset delivery time, wrong delivery address, too short delivery time and the like.
And 213, if so, acquiring and displaying the order signing data of which the function curve is lower than the coincidence threshold value with the reference quantity.
In this embodiment, if the order signing data is lower than the preset overlapping threshold or exceeds the preset deviation range, the order signing data lower than the overlapping threshold between the existing or predicted function curve and the reference quantity is displayed.
On the basis of the previous embodiment, the embodiment describes in detail that signed order receipt data and non-signed order receipt data in the second data report are separated, wherein the signed order receipt data comprises normal receipt data and abnormal receipt data; constructing a probability distribution model based on the second data report; dividing the probability distribution model into at least two partial local function images according to percentages; extracting an abnormal coordinate point corresponding to the local function image containing the most abnormal sign-in data; searching whether the order signing data which is not signed exists in a preset radius range or not based on the abnormal coordinate point; and if the order signing data exists, predicting that the process of abnormality exists in the order signing data which is not signed. Compared with the traditional method, the method has the advantages that the comparison between the reference quantity and the actual data is detailed, and the order signing data are accurately screened.
Referring to fig. 3, a third embodiment of the method for monitoring signed data according to the embodiment of the present invention includes:
301, acquiring order sign-in data, and generating a first data report according to the order sign-in data;
302, acquiring a first operation aiming at a structure field in a first data report, and carrying out structural processing on the first data report based on the first operation;
in this embodiment, the data report is structurally arranged, and the structural fields are sequence number, allocation, allocated, not allocated, allocation rate, and accumulated not allocated, and support the ordering according to allocation rate and accumulated not allocated, and default to descending order according to accumulated not allocated; and estimating the model parameters by using the data samples in the report by using a multiple regression analysis method, carrying out hypothesis test on the model parameters, and finally predicting the dependent variable by using the multiple regression analysis. The statistical analysis method for establishing the linear or nonlinear mathematical model quantity relation among a plurality of variables and analyzing by using sample data can deal with a large amount of logistics order sign-in data and accurately calculate sign-in time-effect data.
303, inputting order signing data to a regression model taking a structure field corresponding to the first operation as an independent variable based on a multivariate regression analysis method to obtain signing time-effect data;
in this embodiment, the multiple regression analysis refers to a statistical analysis method in which one variable is regarded as a dependent variable and one or more other variables are regarded as independent variables, and a linear or nonlinear mathematical model quantitative relation between the variables is established and analyzed using sample data.
304, adding the signing aging data into the first data report to generate a second data report;
305, performing visual conversion on the second data report to generate a corresponding first visual image model, and monitoring order sign-in data through the first visual image model;
306, separating the signed order receipt data and the non-signed order receipt data in the second data report;
in this embodiment, the data sources of the order sign-in data in the second data report are divided into the signed order sign-in data and the non-signed order sign-in data based on whether the order sign-in data is signed in or not, and then the data sources are distinguished by different colors or line types in the generated visual image model. And a button can be provided for displaying the signed order receipt data or the non-signed order receipt data after clicking separately or in a combined way.
307, constructing a probability distribution model based on the second data report;
308, dividing the probability distribution model into at least two partial local function images according to the percentage;
in this embodiment, the probability distribution model constructed based on the second datagram divides the image according to the function in the probability distribution model therein into at least, but not limited to, two parts.
Specifically, the dividing method may be based on the percentage of distribution of the order receipt data, for example, in a coordinate system constructed by using the structure field as the distribution time and the distribution distance, the reference amount should be y ═ kx + b, where both the values k and b are obtained by data optimization in the process of generating the reference amount, each pixel unit data in the input order receipt data generation actual probability distribution model corresponds to one order receipt data, and the dividing of the percentage may be performed based on any structure field in the coordinate system, for example, dividing the distribution time from fast to slow into 0% -50% and 50% -100%, or dividing the function image into more parts.
309, extracting abnormal coordinate points corresponding to the local function image containing the most abnormal sign-in data;
specifically, in the actual monitoring, the order sign-in data is input to generate an actual probability distribution model, and pixel unit data which is deviated from a reference amount necessarily exists, wherein the deviated pixel unit data is used as an abnormal coordinate point, the corresponding order sign-in data is abnormal, and aggregated structure fields in the abnormal order sign-in data are summarized, so that the monitoring and the improvement of the sign-in data are realized.
310, searching whether the order sign-in data which is not signed in exists in a preset radius range or not based on the abnormal coordinate point;
if the data exists, it is predicted that the order receipt data which has not been received is abnormal 311.
On the basis of the previous embodiment, the embodiment describes in detail that signed order receipt data and non-signed order receipt data in the second data report are separated, wherein the signed order receipt data comprises normal receipt data and abnormal receipt data; constructing a probability distribution model based on the second data report; dividing the probability distribution model into at least two partial local function images according to percentages; extracting an abnormal coordinate point corresponding to the local function image containing the most abnormal sign-in data; based on the abnormal coordinate point, whether order signing data exist or not is searched in a preset radius range; and if the order signing data exists, predicting that the process of abnormality exists in the order signing data which is not signed. Compared with the traditional method, the method has the advantages that the division mode of the function images is refined, and large-range and approximate-class abnormal order signing data are rapidly acquired through comparing the function images of different parts based on the division of the function images in the visual model.
In the above description of the method for monitoring the signed data in the embodiment of the present invention, the following description of the device for monitoring the signed data in the embodiment of the present invention refers to fig. 4, and an embodiment of the device for monitoring the signed data in the embodiment of the present invention includes:
the data report generation module 401 is configured to obtain order signing data and generate a first data report according to the order signing data;
the structural processing module 402 is configured to perform structural processing on the first data report, perform data analysis on data in the first data report after the structural processing, and calculate corresponding sign-in aging data;
the timeliness data adding module 403 is configured to add the sign-in timeliness data into the first data report to generate a second data report;
and the monitoring module 404 is configured to perform visual conversion on the second datagram table to generate a corresponding first visual image model, and monitor order receipt data through the first visual image model.
In the embodiment of the invention, the signing data monitoring device runs the signing data monitoring method, and comprises the steps of acquiring order signing data and generating a first data report according to the order signing data; carrying out structuring processing on the first data report, carrying out data analysis on the data in the first data report after the structuring processing, and calculating corresponding sign-in timeliness data; adding the signing aging data into the first data report to generate a second data report; and carrying out visual conversion on the second data report to generate a corresponding first visual image model, and monitoring order sign-in data through the first visual image model. The method processes and analyzes the order signing data, and visually converts the analyzed data report, so that data visualization and automatic generation of abnormal event strategies are realized based on the converted visual model, and the signing efficiency is improved.
Referring to fig. 5, a second embodiment of the device for monitoring signed data according to the embodiment of the present invention includes:
the data report generation module 401 is configured to obtain order signing data and generate a first data report according to the order signing data;
the structural processing module 402 is configured to perform structural processing on the first data report, perform data analysis on data in the first data report after the structural processing, and calculate corresponding sign-in aging data;
the timeliness data adding module 403 is configured to add the sign-in timeliness data into the first data report to generate a second data report;
and the monitoring module 404 is configured to perform visualization conversion on the second datagram to generate a corresponding first visualization image model, and monitor order sign-in data through the first visualization image model.
In this embodiment, the structural processing module 402 is specifically configured to:
acquiring a first operation aiming at a structure field in the first data report, and carrying out structural processing on the first data report based on the first operation; and inputting the order signing data to a regression model taking a structure field corresponding to the first operation as an independent variable based on a multivariate regression analysis method to obtain signing time-effect data.
In this embodiment, the signing data monitoring apparatus further includes a reference amount generating module 405, where the reference amount generating module 405 is specifically configured to:
rejecting abnormal order signing data in the second data report to obtain a third data report; traversing and combining the structure fields in the third data report, and converting the structure fields into first coordinate point data in a data conversion mode; substituting basic service parameters and the first coordinate point data into a graph drawing model to be converted into first pixel unit data; drawing the first pixel unit data into a second visual image model; and optimizing and extracting a function curve in the second visual image model as a reference quantity.
In this embodiment, the monitoring module 404 is specifically configured to:
a coordinate point conversion unit 4041, configured to obtain a second operation for any structure field in the second data report, where the structure field is converted into second coordinate point data in a data conversion manner; a pixel unit conversion unit 4042, which substitutes the basic service parameter and the second coordinate point data into the graphic drawing model to convert into second pixel unit data; the display monitoring unit 4043 is configured to draw and display the second pixel unit data into a first visual image model, and monitor the order receipt data based on the first visual image model.
In this embodiment, the display monitoring unit 4043 is specifically configured to:
drawing the second pixel unit data into a first visual image model and displaying the first visual image model; judging whether the coincidence rate of the function curve in the first visual image model and the corresponding reference quantity is lower than a preset coincidence threshold value or not; if yes, acquiring and displaying order signing data which is lower than a coincidence threshold value between the function curve and the reference quantity.
The apparatus for monitoring signed-in data further comprises an anomaly prediction module 406, wherein the anomaly prediction module 406 is specifically configured to:
the sign-in data separation unit 4061 is used for separating the sign-in data of the signed order and the sign-in data of the non-signed order in the second data report, wherein the sign-in data of the signed order comprises normal sign-in data and abnormal sign-in data; a model building unit 4062, which builds a probability distribution model based on the second datagram table; a function image dividing unit 4063, which divides the probability distribution model into at least two partial local function images according to percentage; a coordinate point extraction unit 4064 that extracts an abnormal coordinate point corresponding to the local function image including the most abnormal receipt data; an abnormal coordinate point searching unit 4065, which searches whether the order sign-in data that has not been signed in exists in a preset radius range based on the abnormal coordinate point; the predicting unit 4066 predicts that the order receipt non-receipt data is abnormal if the order receipt non-receipt data exists.
In this embodiment, the abnormality predicting module further includes an abnormality determining unit 4067, where the abnormality determining unit 4067 is specifically configured to:
acquiring the distribution condition of the non-signed order signing data of different types in the probability distribution model; traversing and judging the distribution conditions in the probability distribution models of different types to be aggregation or regression; if the abnormal reasons are aggregated, the abnormal reasons are scattered outside the aggregation; and if the abnormal reasons are regressed, dispersing the abnormal reasons in the preset unit length of the reference quantity.
On the basis of the previous embodiment, the specific functions of each module and the unit composition of partial modules are described in detail, the specific functions of the original modules are detailed through the modules, the operation of the signing data monitoring device is perfected, the reliability of the device in operation is improved, the actual logic among all steps is clarified, and the practicability of the device is improved.
The above fig. 4 and fig. 5 describe the signing data monitoring apparatus in the embodiment of the present invention in detail from the perspective of the modular functional entity, and the following describes the signing data monitoring apparatus in the embodiment of the present invention in detail from the perspective of hardware processing.
Fig. 6 is a schematic structural diagram of a signing data monitoring apparatus according to an embodiment of the present invention, where the signing data monitoring apparatus 600 may generate relatively large differences due to different configurations or performances, and may include one or more processors (CPUs) 610 (e.g., one or more processors) and a memory 620, one or more storage media 630 (e.g., one or more mass storage devices) storing applications 633 or data 632. Memory 620 and storage medium 630 may be, among other things, transient or persistent storage. The program stored on the storage medium 630 may include one or more modules (not shown), each of which may include a sequence of instructions operating on the signed data monitoring apparatus 600. Still further, the processor 610 may be configured to communicate with the storage medium 630 to execute a series of instruction operations in the storage medium 630 on the signed data monitoring apparatus 600 to implement the steps of the signed data monitoring method described above.
The signed data monitoring apparatus 600 may also include one or more power supplies 640, one or more wired or wireless network interfaces 650, one or more input-output interfaces 660, and/or one or more operating systems 631, such as Windows Server, Mac OS X, Unix, Linux, FreeBSD, and the like. Those skilled in the art will appreciate that the configuration of the signoff data monitoring device shown in fig. 6 does not constitute a limitation of the signoff data monitoring devices provided herein and may include more or fewer components than shown, or some components in combination, or a different arrangement of components.
The present invention also provides a computer-readable storage medium, which may be a non-volatile computer-readable storage medium, or a volatile computer-readable storage medium, having stored therein instructions, which, when executed on a computer, cause the computer to perform the steps of the method for monitoring signed data.
It is clear to those skilled in the art that, for convenience and brevity of description, the specific working processes of the above-described systems, apparatuses, and units may refer to the corresponding processes in the foregoing method embodiments, and are not described herein again.
The integrated unit, if implemented in the form of a software functional unit and sold or used as a stand-alone product, may be stored in a computer readable storage medium. Based on such understanding, the technical solution of the present invention may be embodied in the form of a software product, which is stored in a storage medium and includes instructions for causing a computer device (which may be a personal computer, a server, or a network device) to execute all or part of the steps of the method according to the embodiments of the present invention. And the aforementioned storage medium includes: various media capable of storing program codes, such as a usb disk, a removable hard disk, a read-only memory (ROM), a Random Access Memory (RAM), a magnetic disk, or an optical disk.
The above-mentioned embodiments are only used for illustrating the technical solutions of the present invention, and not for limiting the same; although the present invention has been described in detail with reference to the foregoing embodiments, it will be understood by those of ordinary skill in the art that: the technical solutions described in the foregoing embodiments may still be modified, or some technical features may be equivalently replaced; and such modifications or substitutions do not depart from the spirit and scope of the corresponding technical solutions of the embodiments of the present invention.
Claims (10)
1. A method for monitoring signed data is characterized in that the method for monitoring the signed data comprises the following steps:
acquiring order sign-off data and generating a first data report according to the order sign-off data;
carrying out structuring processing on the first data report, carrying out data analysis on the data in the first data report after the structuring processing, and calculating corresponding sign-in timeliness data;
adding the signing aging data into the first data report to generate a second data report;
and carrying out visual conversion on the second data report to generate a corresponding first visual image model, and monitoring order sign-in data through the first visual image model.
2. The method for monitoring receipt data according to claim 1, wherein the step of performing structuring processing on the first data report, performing data analysis on the data in the first data report after the structuring processing, and calculating corresponding receipt aging data comprises:
acquiring a first operation aiming at a structure field in the first data report, and carrying out structural processing on the first data report based on the first operation;
and inputting the order signing data to a regression model taking a structure field corresponding to the first operation as an independent variable based on a multivariate regression analysis method to obtain signing time-effect data.
3. A method for monitoring receipt data according to claim 2, wherein before visually converting the second datagram to generate a corresponding first visual image model and monitoring the order receipt data through the first visual image model, the method comprises:
rejecting abnormal order signing data in the second data report to obtain a third data report;
traversing and combining the structure fields in the third data report, and converting the structure fields into first coordinate point data in a data conversion mode;
substituting basic service parameters and the first coordinate point data into a graph drawing model to be converted into first pixel unit data;
drawing the first pixel unit data into a second visual image model;
and optimizing and extracting a function curve in the second visual image model as a reference quantity.
4. A method as claimed in claim 3, wherein said visually converting said second datagram table to generate a corresponding first visual image model, and monitoring the order receipt data through said first visual image model comprises:
acquiring a second operation aiming at any structure field in the second data report, wherein the structure field is converted into second coordinate point data in a data conversion mode;
substituting the basic service parameters and the second coordinate point data into a graphic drawing model to be converted into second pixel unit data;
and drawing the second pixel unit data into a first visual image model for displaying, and monitoring the order signing data based on the first visual image model.
5. A method as claimed in claim 4, wherein the step of drawing the second pixel unit data into a first visual image model and displaying the first pixel unit data, and the step of monitoring the order receipt data based on the first visual image model comprises:
drawing the second pixel unit data into a first visual image model and displaying the first visual image model;
judging whether the coincidence rate of the function curve in the first visual image model and the corresponding reference quantity is lower than a preset coincidence threshold value or not;
if yes, obtaining and displaying order signing data with the function curve and the reference quantity lower than a coincidence threshold value.
6. A method as claimed in claim 3, wherein said visually converting said second datagram table to generate a corresponding first visual image model, and after monitoring the order receipt data through said first visual image model, the method comprises:
separating signed order receipt data and non-signed order receipt data in the second data report, wherein the signed order receipt data comprises normal receipt data and abnormal receipt data;
constructing a probability distribution model based on the second data report;
dividing the probability distribution model into at least two partial local function images according to percentages;
extracting an abnormal coordinate point corresponding to the local function image containing the most abnormal sign-in data;
searching whether the order sign-in data which is not signed in exists in a preset radius range or not based on the abnormal coordinate point;
if the order is not signed, judging that the order signing data which is not signed has abnormity.
7. A method of monitoring signoff data according to claim 6 and after said building a probability distribution model based on said second datagram table comprises:
acquiring the distribution condition of the non-receipt order receipt data of different types in the probability distribution model;
traversing and judging the distribution conditions in the probability distribution models of different types to be aggregation or regression;
if the abnormal reasons are aggregated, the abnormal reasons are scattered outside the aggregation;
and if the abnormal reasons are regressed, dispersing the abnormal reasons in the preset unit length of the reference quantity.
8. An apparatus for monitoring signed-for data, comprising:
the data report generating module is used for acquiring order signing data and generating a first data report according to the order signing data;
the structural processing module is used for carrying out structural processing on the first data report, carrying out data analysis on data in the first data report after the structural processing and calculating corresponding signing time-effect data;
the aging data adding module is used for adding the signing aging data into the first data report to generate a second data report;
and the monitoring module is used for performing visual conversion on the second data report to generate a corresponding first visual image model, and monitoring order signing data through the first visual image model.
9. An apparatus for monitoring signed-for data, the apparatus comprising: a memory having instructions stored therein and at least one processor, the memory and the at least one processor interconnected by a line;
the at least one processor invoking the instructions in the memory to cause the signoff data monitoring device to perform the steps of the signoff data monitoring method of any of claims 1-7.
10. A computer-readable storage medium, on which a computer program is stored which, when being executed by a processor, carries out the steps of the method for monitoring signed-in data according to any one of claims 1 to 7.
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