CN116821553A - Intelligent government affair public management platform based on data sharing - Google Patents
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Abstract
The application relates to the technical field of government affair management platforms and discloses a data sharing-based intelligent government affair disclosure management platform which comprises a login management module, a data uploading module, a background data acquisition module, a first class data analysis module, a second class data analysis module, a platform optimization analysis module and a system maintenance module.
Description
Technical Field
The application relates to the technical field of government affair management platforms, in particular to an intelligent government affair disclosure management platform based on data sharing.
Background
In recent years, government of China continuously deepens government open, thus raise the government service level, government open mainly refer to administrative authorities and law to public each work content and process to public through multiple ways open, but government open management platform is one of important ways, under the background that the internet technology is continuously developed, especially after government of China has proposed "Internet+" development tactics, government portal website and platform bear more and more functions, it is also more and more prominent in society, government portal website and platform are important platform of public expression opinion, consulting business, also important channel of network public opinion supervision, dredge public emotion, therefore the significance of government open management platform is apparent.
However, the existing government affair disclosure management platform does not deeply excavate platform data, so that scientific auxiliary decision support cannot be provided for optimization of the platform, whether the coverage rate of the platform is comprehensive or not cannot be judged through the data, whether propaganda needs to be increased or not is judged, and whether upgrading optimization of the platform needs to be carried out or not cannot be judged through the data.
Disclosure of Invention
In order to overcome the defects in the prior art, the application provides an intelligent government affair disclosure management platform based on data sharing, which solves the problems in the background art.
The application provides the following technical scheme: the intelligent government affair disclosure management platform based on data sharing comprises a login management module, a data uploading module, a background data acquisition module, a class-one data analysis module, a class-two data analysis module, a platform optimization analysis module and a system maintenance module;
the login management module is used for logging in the intelligent government affair disclosure management platform by the common user and the management user;
the data uploading module is used for uploading platform contents input by a management user to the intelligent government affair disclosure management platform;
the background data acquisition module is used for acquiring background data of the intelligent government affair public management platform, and comprises a class-one data acquisition unit and a class-two data acquisition unit, wherein the class-one data acquisition unit is used for acquiring class-one data, the class-two data acquisition unit is used for acquiring class-two data, the class-one data acquisition unit transmits the acquired data to the class-one data analysis module for analysis, and the class-two data acquisition unit transmits the acquired data to the class-two data analysis module for analysis;
the data analysis module is used for analyzing the data transmitted by the data acquisition unit to obtain a data transmission coefficient alpha and transmitting the data transmission coefficient alpha to the platform optimization analysis module;
the second-class data analysis module is used for analyzing the second-class data transmitted by the second-class data acquisition unit, obtaining a propaganda data coefficient beta and transmitting the propaganda data coefficient beta to the platform optimization analysis module;
the platform optimization analysis module receives the data of the first class data analysis module and the second class data analysis module, obtains the platform optimizable index gamma through comprehensive analysis, judges the optimizable direction at the same time, and transmits the judging result to the system maintenance module;
the system maintenance module is used for receiving the platform optimizing index gamma and the judging result data of the platform optimizing analysis module, displaying the platform optimizing index gamma, carrying out corresponding warning display according to different judging results, and simultaneously carrying out corresponding maintenance on the platform during the system optimization of the platform.
Preferably, the analyzing the class of data analysis module to obtain the class of data transmission coefficients α includes the following steps:
step S01: marking the time point of uploading the platform content by the management user in the data as t, and marking the platform content as 1, 2 and 3 … … n in sequence, wherein the uploading time point corresponding to each platform content is t 1 、t 2 、t 3 ……t n ；
Step S02: the time point of successful uploading corresponding to each platform content is marked as t 1 ´、t 2 ´、t 3 ´……t n If so, the uploading time difference corresponding to each platform content is recorded as delta t 1 、Δt 2 、Δt 3 ……Δt n The calculation formula of the uploading time difference is as follows:wherein i=1, 2, 3 … … n;
step S03: extracting event time points based on deep learning model and marking as T, and then uploading event time points corresponding to each platform content as T 1 、T 2 、T 3 ……T n The event time point is the time point of event occurrence mentioned in the uploaded platform content text, if the event occurrence time point is not mentioned in the uploaded ith platform content text, T i Marking as 0, and simultaneously marking the publication time difference corresponding to each platform content as delta T 1 、ΔT 2 、ΔT 3 ……ΔT n ；
Step S04: calculating a class of data transmission coefficients alpha:wherein->，i=1、2、3……n，µ 1 、µ 2 For the corresponding scaling factor, mu 1 、µ 2 Are all greater than 0.
Preferably, the second-class data analysis module analyzes and obtains the propaganda data coefficient beta, which comprises the following steps:
step S11: for successfully uploaded platform content, the first clicked time point is marked as c 1 The mth click-to-view time point of the platform content is marked as c m Since the intelligent government affair disclosure management platform has n successfully uploaded platform contents, marking the point of time when the ith successfully uploaded platform content is clicked and checked for the first time as c i1 The mth point in time when the ith successfully uploaded platform content is clicked and viewed for the mth time is marked as c im Wherein i=1, 2, 3 … … n;
step S12: for the ith successfully uploaded platform content, browsing the page after being clicked and viewed for the first timeLong term d i1 The page browsing time after the mth clicked view is marked as d im Wherein i=1, 2, 3 … … n;
step S13: invalid data is removed, and valid data is reserved: for the clicked and checked platform content, each IP address only keeps the earliest clicked and checked time point data and browsing time length data, the checked time point data and the browsing time length data of repeated IP addresses are invalid data, and meanwhile, the browsing time length data which is not in the normal browsing time length threshold range is invalid data;
step S14: calculating a propaganda data coefficient beta:wherein Δc is the interval time difference number, Δc j Delta c, the difference between the j-th viewed and j+1th viewed of the platform content ij For the interval time difference between the jth checked and the (j+1) th checked of the ith successfully uploaded platform content,/for the (i)>，k i Index constant k corresponding to ith successfully uploaded platform content i Are all less than 0.
Preferably, the calculation formula of the platform optimizable index gamma obtained by the platform optimization analysis module through comprehensive analysis is as follows:wherein δ is an index influencing factor.
Preferably, the calculation of the index influence factor δ includes the steps of:
step S21: for each common user logging in the intelligent government affair public management platform, corresponding to one IP address, each IP address is expressed as (x) in a coordinate point form according to the successful logging-in sequence 1 ，y 1 ）、（x 2 ，y 2 ）、（x 3 ，y 3 ）……（x p ，y p ）；
Step S22: each IP address is sequentially subjected to coordinate cross representation and marked as @x 1 ´，y 1 ´）、（x 2 ´，y 2 ´）、（x 3 ´，y 3 ´）……（x p ´，y p (v), wherein x i ´=x i+1 -x i ，y i ´=y i+1 +y i ，i=1、2、3……p；
Step S23: calculating an index influence factor delta:。
preferably, the determining the optimizable direction by the platform optimization analysis module includes the following steps:
step S31: determining a platform optimizable index gamma: if the optimizing index gamma of the platform is larger than the optimizing limit value K, executing the step S32, and if the optimizing index gamma of the platform is smaller than or equal to the optimizing limit value K, executing the step S33;
step S32: judging the optimization direction as two directions of a platform system optimization direction and a platform propaganda optimization direction, namely optimizing both directions;
step S33: when the data transmission coefficient alpha is larger than the propaganda data coefficient beta, the optimizable direction is judged to be the platform system optimization direction, when the data transmission coefficient alpha is smaller than the propaganda data coefficient beta, the optimizable direction is judged to be the platform propaganda optimization direction, and when the data transmission coefficient alpha is equal to the propaganda data coefficient beta, both directions can be optimized or neither direction can be optimized.
The application has the technical effects and advantages that:
1. the application is beneficial to deep mining of hidden data by analyzing the time point of uploading platform content by a management user, the time point of successful uploading of the platform content by the management user and the quantity of the platform content uploaded by the management user and obtaining a class of data transmission coefficient by utilizing a formula through arranging a class of data analysis module.
2. The application is beneficial to analyzing the browsing data of the platform content and the IP data of the common user by arranging the second-class data analysis module and obtaining the propaganda data system by utilizing a formula, thereby judging whether the platform utilization rate, the popularity and the propaganda degree need to be improved and optimized or not and increasing the propaganda strength in time.
3. The platform optimization analysis module is arranged, so that the data of the first class data analysis module and the second class data analysis module are combined with index influence factors to deeply mine the platform data, whether the platform needs to be upgraded and optimized is comprehensively judged, and scientific auxiliary decision support is provided for the optimization of the platform.
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FIG. 1 is a diagram of a system for creating a data sharing-based intelligent government affair disclosure management platform.
Detailed Description
The following will be described in detail and with reference to the drawings in the present application, and the configurations of the structures described in the following embodiments are merely examples, and the smart government affair disclosure management platform based on data sharing according to the present application is not limited to the structures described in the following embodiments, and all other embodiments obtained by a person skilled in the art without making any creative effort are within the scope of the present application.
The application provides an intelligent government affair disclosure management platform based on data sharing, which comprises a login management module, a data uploading module, a background data acquisition module, a first class data analysis module, a second class data analysis module, a platform optimization analysis module and a system maintenance module;
the login management module is used for enabling a common user to log in the intelligent government affair disclosure management platform with a management user, the common user can log in the platform through the login management module so as to click and browse each content in the platform, the management user can log in the platform through the login management module, upload the platform content, and the user can be regarded as successful in logging in when entering the intelligent government affair disclosure management platform page;
the data uploading module is used for uploading platform contents input by a management user to the intelligent government affair disclosure management platform, wherein the platform contents comprise but are not limited to government affair notices, news articles and news pictures;
the background data acquisition module is used for acquiring background data of the intelligent government affair disclosure management platform, the background data comprises one type of data and two types of data, the one type of data comprises but is not limited to a time point when a management user uploads platform content, a time point when the management user uploads the platform content and the number of the platform content uploaded by the management user, the two types of data comprise but are not limited to browsing data of the platform content and IP data of a common user, the browsing data of the platform content comprise but are not limited to a time point when the platform content is clicked each time and a period when a platform page is browsed, the IP data comprise but are not limited to IP addresses when the user logs in the intelligent government affair disclosure management platform, the background data acquisition module comprises one type of data acquisition unit and two types of data acquisition unit, the two types of data acquisition unit is used for acquiring one type of data, the one type of data acquisition unit transmits the acquired data to the two types of data analysis module for analysis, and the data acquisition unit transmits the acquired data to the two types of data analysis module for analysis;
the system comprises a data acquisition unit, a platform optimization analysis module, a data analysis module and a data analysis module, wherein the data analysis module is used for analyzing one type of data transmitted by the data acquisition unit to obtain one type of data transmission coefficient alpha, and transmitting the data to the platform optimization analysis module;
the second-class data analysis module is used for analyzing the second-class data transmitted by the second-class data acquisition unit to obtain a propaganda data coefficient beta, and transmitting the propaganda data coefficient beta to the platform optimization analysis module, when the propaganda data coefficient beta is higher, the more the number of users of the intelligent government separated management platform is indicated, namely, the propaganda effect is better;
the platform optimization analysis module receives the data of the first class data analysis module and the second class data analysis module, obtains a platform optimizable index gamma through comprehensive analysis, judges an optimizable direction, wherein the optimizable direction comprises a platform system optimization direction and a platform propaganda optimization direction, and transmits a judging result to the system maintenance module;
the system maintenance module is used for receiving the platform optimizing index gamma and the judging result data of the platform optimizing analysis module, displaying the platform optimizing index gamma, carrying out corresponding warning display according to different judging results, and simultaneously carrying out corresponding maintenance on the platform during the system optimization of the platform.
In this embodiment, it should be specifically described that the analysis of the first class of data transmission coefficients α by the first class of data analysis module includes the following steps:
step S01: marking the time point of uploading the platform content by the management user in the data as t, and marking the platform content as 1, 2 and 3 … … n in sequence, wherein the uploading time point corresponding to each platform content is t 1 、t 2 、t 3 ……t n ；
Step S02: the time point of successful uploading corresponding to each platform content is marked as t 1 ´、t 2 ´、t 3 ´……t n If so, the uploading time difference corresponding to each platform content is recorded as delta t 1 、Δt 2 、Δt 3 ……Δt n The calculation formula of the uploading time difference is as follows:wherein i=1, 2, 3 … … n;
step S03: extracting event time points based on deep learning model and marking as T, and then uploading event time points corresponding to each platform content as T 1 、T 2 、T 3 ……T n The event time point is the time point of event occurrence mentioned in the uploaded platform content text, if the event occurrence time point is not mentioned in the uploaded ith platform content text, T i Marking as 0, and simultaneously marking the publication time difference corresponding to each platform content as delta T 1 、ΔT 2 、ΔT 3 ……ΔT n ；
Step S04: calculating a class of data transmission coefficients alpha:wherein->，i=1、2、3……n，µ 1 、µ 2 For the corresponding scaling factor, mu 1 、µ 2 All are greater than 0, and the specific numerical values are not specifically limited in this embodiment.
In this embodiment, it should be specifically described that the analysis of the propaganda data coefficient β by the second class data analysis module includes the following steps:
step S11: for successfully uploaded platform content, the first clicked time point is marked as c 1 The mth click-to-view time point of the platform content is marked as c m Since the intelligent government affair disclosure management platform has n successfully uploaded platform contents, marking the point of time when the ith successfully uploaded platform content is clicked and checked for the first time as c i1 The mth point in time when the ith successfully uploaded platform content is clicked and viewed for the mth time is marked as c im Wherein i=1, 2, 3 … … n;
step S12: for the ith successfully uploaded platform content, marking the page browsing duration after the first clicked and checked as d i1 The page browsing time after the mth clicked view is marked as d im Wherein i=1, 2, 3 … … n;
step S13: invalid data is removed, and valid data is reserved: for the clicked and checked platform content, each IP address only keeps the earliest clicked and checked time point data and browsing time length data, the checked time point data and the browsing time length data of repeated IP addresses are invalid data, meanwhile, the browsing time length data which is not in the normal browsing time length threshold range is invalid data, and the upper limit of the browsing time length threshold is P 2 The lower limit of the browsing duration threshold is P 1 The P is 2 The duration value used for reading the corresponding platform content by adopting the slowest reading rate, wherein P is 1 A duration value used for reading the corresponding platform content by using the slowest reading rate;
step S14: calculating a propaganda data coefficient beta:wherein Δc is the interval time difference number, Δc j Delta c, the difference between the j-th viewed and j+1th viewed of the platform content ij For the interval time difference between the jth checked and the (j+1) th checked of the ith successfully uploaded platform content,/for the (i)>，k i Index constant k corresponding to ith successfully uploaded platform content i All of which are smaller than 0, and the specific values are not particularly limited in this embodiment.
In this embodiment, it should be specifically described that the calculation formula of the platform optimizable index γ obtained by the platform optimization analysis module through comprehensive analysis is:wherein δ is an index influencing factor.
In this embodiment, it should be specifically described that the calculation of the index influence factor δ includes the following steps:
step S21: for each common user logging in the intelligent government affair public management platform, corresponding to one IP address, each IP address is expressed as (x) in a coordinate point form according to the successful logging-in sequence 1 ，y 1 ）、（x 2 ，y 2 ）、（x 3 ，y 3 ）……（x p ，y p ）；
Step S22: each IP address is in turn represented by a coordinate cross, labeled (x 1 ´，y 1 ´）、（x 2 ´，y 2 ´）、（x 3 ´，y 3 ´）……（x p ´，y p (v), wherein x i ´=x i+1 -x i ，y i ´=y i+1 +y i ，i=1、2、3……p；
Step S23: calculating an index influence factor delta:。
in this embodiment, it needs to be specifically described that the determining, by the platform optimization analysis module, the optimizable direction includes the following steps:
step S31: determining a platform optimizable index gamma: if the optimizing index gamma of the platform is larger than the optimizing limit value K, executing the step S32, and if the optimizing index gamma of the platform is smaller than or equal to the optimizing limit value K, executing the step S33;
step S32: judging the optimization direction as two directions of a platform system optimization direction and a platform propaganda optimization direction, namely optimizing both directions;
step S33: when the data transmission coefficient alpha is larger than the propaganda data coefficient beta, the optimizable direction is judged to be the platform system optimization direction, when the data transmission coefficient alpha is smaller than the propaganda data coefficient beta, the optimizable direction is judged to be the platform propaganda optimization direction, and when the data transmission coefficient alpha is equal to the propaganda data coefficient beta, both directions can be optimized or neither direction can be optimized.
Finally: the foregoing description of the preferred embodiments of the application is not intended to limit the application to the precise form disclosed, and any such modifications, equivalents, and alternatives falling within the spirit and principles of the application are intended to be included within the scope of the application.
The foregoing is merely illustrative of the present application, and the present application is not limited thereto, and any person skilled in the art will readily recognize that variations or substitutions are within the scope of the present application. Therefore, the protection scope of the present application shall be subject to the protection scope of the claims.
Claims (6)
1. An wisdom government affair publicity management platform based on data sharing, its characterized in that: the system comprises a login management module, a data uploading module, a background data acquisition module, a first class data analysis module, a second class data analysis module, a platform optimization analysis module and a system maintenance module;
the login management module is used for logging in the intelligent government affair disclosure management platform by the common user and the management user;
the data uploading module is used for uploading platform contents input by a management user to the intelligent government affair disclosure management platform;
the background data acquisition module is used for acquiring background data of the intelligent government affair public management platform, and comprises a class-one data acquisition unit and a class-two data acquisition unit, wherein the class-one data acquisition unit is used for acquiring class-one data, the class-two data acquisition unit is used for acquiring class-two data, the class-one data acquisition unit transmits the acquired data to the class-one data analysis module for analysis, and the class-two data acquisition unit transmits the acquired data to the class-two data analysis module for analysis;
the data analysis module is used for analyzing the data transmitted by the data acquisition unit to obtain a data transmission coefficient alpha and transmitting the data transmission coefficient alpha to the platform optimization analysis module;
the second-class data analysis module is used for analyzing the second-class data transmitted by the second-class data acquisition unit, obtaining a propaganda data coefficient beta and transmitting the propaganda data coefficient beta to the platform optimization analysis module;
the platform optimization analysis module receives the data of the first class data analysis module and the second class data analysis module, obtains the platform optimizable index gamma through comprehensive analysis, judges the optimizable direction at the same time, and transmits the judging result to the system maintenance module;
the system maintenance module is used for receiving the platform optimizing index gamma and the judging result data of the platform optimizing analysis module, displaying the platform optimizing index gamma, carrying out corresponding warning display according to different judging results, and simultaneously carrying out corresponding maintenance on the platform during the system optimization of the platform.
2. The intelligent government affair disclosure management platform based on data sharing according to claim 1, wherein: the data analysis module analyzes and obtains a data transmission coefficient alpha, which comprises the following steps:
step S01: marking the time point of uploading the platform content by the management user in the data as t, and marking the platform content as 1, 2 and 3 … … n in sequence, wherein the uploading time point corresponding to each platform content is t 1 、t 2 、t 3 ……t n ；
Step S02: the time point of successful uploading corresponding to each platform content is marked as t 1 ´、t 2 ´、t 3 ´……t n If so, the uploading time difference corresponding to each platform content is recorded as delta t 1 、Δt 2 、Δt 3 ……Δt n The calculation formula of the uploading time difference is as follows:wherein i=1, 2, 3 … … n;
step S03: extracting event time points based on deep learning model and marking as T, and then uploading event time points corresponding to each platform content as T 1 、T 2 、T 3 ……T n The event time point is the time point of event occurrence mentioned in the uploaded platform content text, if the event occurrence time point is not mentioned in the uploaded ith platform content text, T i Marking as 0, and simultaneously marking the publication time difference corresponding to each platform content as delta T 1 、ΔT 2 、ΔT 3 ……ΔT n ；
Step S04: calculating a class of data transmission coefficients alpha:wherein->，i=1、2、3……n，µ 1 、µ 2 For the corresponding scaling factor, mu 1 、µ 2 Are all greater than 0.
3. The intelligent government affair disclosure management platform based on data sharing according to claim 1, wherein: the second-class data analysis module analyzes and obtains the propaganda data coefficient beta, which comprises the following steps:
step S11: for successfully uploaded platform content, the first clicked time point is marked as c 1 The mth click-to-view time point of the platform content is marked as c m Since the intelligent government affair disclosure management platform has n successfully uploaded platform contents, marking the point of time when the ith successfully uploaded platform content is clicked and checked for the first time as c i1 The mth point in time when the ith successfully uploaded platform content is clicked and viewed for the mth time is marked as c im Wherein i=1, 2, 3 … … n;
step S12: for the ith successfully uploaded platform content, marking the page browsing duration after the first clicked and checked as d i1 The page browsing time after the mth clicked view is marked as d im Wherein i=1, 2, 3 … … n;
step S13: invalid data is removed, and valid data is reserved: for the clicked and checked platform content, each IP address only keeps the earliest clicked and checked time point data and browsing time length data, the checked time point data and the browsing time length data of repeated IP addresses are invalid data, and meanwhile, the browsing time length data which is not in the normal browsing time length threshold range is invalid data;
step S14: calculating a propaganda data coefficient beta:wherein Δc is the interval time difference number, Δc j Delta c, the difference between the j-th viewed and j+1th viewed of the platform content ij For the interval time difference between the jth checked and the (j+1) th checked of the ith successfully uploaded platform content,/for the (i)>，k i Index constant k corresponding to ith successfully uploaded platform content i Are all less than 0.
4. According to claimThe intelligent government affair disclosure management platform based on data sharing as set forth in claim 1, wherein: the calculation formula of the platform optimizable index gamma obtained by the platform optimization analysis module through comprehensive analysis is as follows:wherein δ is an index influencing factor.
5. The intelligent government affair disclosure management platform based on data sharing according to claim 4, wherein: the calculation of the index influence factor delta comprises the following steps:
step S21: for each common user logging in the intelligent government affair public management platform, corresponding to one IP address, each IP address is expressed as (x) in a coordinate point form according to the successful logging-in sequence 1 ，y 1 ）、（x 2 ，y 2 ）、（x 3 ，y 3 ）……（x p ，y p ）；
Step S22: each IP address is in turn represented by a coordinate cross, labeled (x 1 ´，y 1 ´）、（x 2 ´，y 2 ´）、（x 3 ´，y 3 ´）……（x p ´，y p (v), wherein x i ´=x i+1 -x i ，y i ´=y i+1 +y i ，i=1、2、3……p；
Step S23: calculating an index influence factor delta:。
6. the intelligent government affair disclosure management platform based on data sharing according to claim 4, wherein: the platform optimization analysis module judges the optimizable direction, and comprises the following steps:
step S31: determining a platform optimizable index gamma: if the optimizing index gamma of the platform is larger than the optimizing limit value K, executing the step S32, and if the optimizing index gamma of the platform is smaller than or equal to the optimizing limit value K, executing the step S33;
step S32: judging the optimization direction as two directions of a platform system optimization direction and a platform propaganda optimization direction, namely optimizing both directions;
step S33: when the data transmission coefficient alpha is larger than the propaganda data coefficient beta, the optimizable direction is judged to be the platform system optimization direction, when the data transmission coefficient alpha is smaller than the propaganda data coefficient beta, the optimizable direction is judged to be the platform propaganda optimization direction, and when the data transmission coefficient alpha is equal to the propaganda data coefficient beta, both directions can be optimized or neither direction can be optimized.
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