Comprehensive fee payment query management system based on data analysis

Abstract

The invention relates to the technical field of fee payment query management, in particular to a comprehensive fee payment query management system based on data analysis. Comprising a payment query management center, a platform information base, a query obstruction division unit, a query fluency analysis unit, an interactive obstruction analysis unit, a query form authentication unit, a query tracking evaluation unit and a query display unit. Analysis is carried out from two points of information processing and information fluency of the payment query platform to understand the risk degree of query difficulty of the payment query platform, the payment query efficiency and reliability of the user are improved, query matching quantitative feedback analysis is deeply carried out on the user in an information progressive mode, and the user experience is improved. Therefore, the payment information can be accurately inquired, the inquiry rate and the inquiry safety of the user are improved, the inquiry result is displayed and evaluated, the inquiry efficiency of the user is improved, and the information integrity and the historical record accuracy of the payment inquiry platform are improved.

Description

Technical Field

[0001] The present invention relates to the technical field of fee payment inquiry management, and in particular to a fee comprehensive fee payment inquiry management system based on data analysis. Background Art

[0002] The comprehensive payment system is a comprehensive platform for handling various payment services through the Internet. The comprehensive payment system provides you with easy-to-operate, multi-faceted payment services; using this system can help physical stores reduce the capital occupied by physical cards such as phone bills and game point cards, improve the utilization rate of funds to a greater extent, meet the various payment needs of customers, and at the same time, store owners can obtain higher profits;

[0003] However, in the prior art, it is impossible to conduct security supervision from the two points of information processing and information flow of the payment inquiry platform, which leads to increased query difficulty of the payment inquiry platform, while reducing the query efficiency and timeliness of query management of users, and it is impossible to conduct security authentication matching and display evaluation of user query information, thereby reducing the display integrity and accuracy of user query results and reducing the user query experience;

[0004] In view of the above technical defects, a solution is now proposed. Summary of the invention

[0005] The purpose of the present invention is to provide a comprehensive fee payment inquiry and management system based on data analysis to solve the technical defects mentioned above. The present invention analyzes the information processing and information flow of the payment inquiry platform to understand the risk level of the inquiry difficulty of the payment inquiry platform, which helps to improve the user's payment inquiry efficiency and reliability. Through the progressive information method, the user's query matching quantitative feedback analysis is carried out in depth to accurately query payment information, while improving the user's query rate and query security, and displaying and evaluating the query results to improve the user's query efficiency, while improving the information integrity and historical record accuracy of the payment inquiry platform.

[0006] The object of the present invention can be achieved by the following technical solutions: a fee comprehensive payment query management system based on data analysis, comprising a payment query management center, a platform information base, a query obstacle division unit, a query smoothness analysis unit, an interactive obstacle analysis unit, a query form authentication unit, a query tracking and evaluation unit, and a query display unit;

[0007] The payment inquiry management center is used to retrieve the information update data and inquiry risk information of the payment inquiry platform from the platform information database, and send the information update data and inquiry risk information to the inquiry obstacle classification unit and the inquiry smoothness analysis unit respectively;

[0008] The query obstacle partitioning unit is used to perform query impact partitioning analysis on the received information update data, perform discriminant analysis on the obtained information reliability index, and obtain the query impact level CD;

[0009] The query fluency analysis unit is used to perform a quantitative analysis of the query information fluency of the received query risk information to obtain a query fluency level CL;

[0010] The interactive obstacle analysis unit is used to perform interactive query difficulty analysis on the query impact level CD and the query fluency level CL, and to perform discrimination processing on the obtained query obstacle coefficient to obtain a normal signal or an alarm signal;

[0011] The query form authentication unit is used to respond to normal signals, collect the user's query method, perform query matching quantitative feedback analysis on the query method, and obtain a query matching page;

[0012] The query tracking and evaluation unit is used to respond to the query matching page and collect the display information of the query matching page, and at the same time perform query information integrity evaluation and analysis on the display information to obtain a qualified signal or a unqualified signal.

[0013] Preferably, the query impact partition analysis process is as follows:

[0014] A monitoring period is set and set as a time threshold, and information update data of the payment inquiry platform within the time threshold is obtained, the information update data including an effectiveness information index and an information processing coefficient, and the effectiveness information index and the information processing coefficient are compared and analyzed with a preset effectiveness information index threshold and a preset information processing coefficient threshold, and the number of effectiveness information indexes and information processing coefficients that are greater than or equal to the preset effectiveness information index threshold and the preset information processing coefficient threshold is set as the information reliability index, and a discriminant analysis is performed on the information reliability index to obtain a first-level impact, a second-level impact and a third-level impact, and the first-level impact, the second-level impact and the third-level impact are set as the query impact level CD, CD=1, 2, 3.

[0015] Preferably, the timeliness information index indicates the portion of the time between the most recent payment time and the time that can be queried and displayed on the payment inquiry platform that exceeds the preset time; the information processing coefficient indicates the ratio between the total number of historical times corresponding to the mismatch between the payment information of the payment inquiry platform and the set payment classification items and the total number of payments, the payment information includes water charges, electricity charges, and property fees, and the payment classification items include water charges, electricity charges, property fees, and rent items.

[0016] Preferably, the query information fluency quantitative analysis process is as follows:

[0017] Obtain the query risk information of the payment query platform within the time threshold, including the loading risk index and the query fluency index;

[0018] The loading risk index represents the product of the average page loading time of the payment query platform and the total number of loading failures after data normalization processing, and the number of loading failures represents the number of times the query result page or the complete query result page is not loaded; the query fluency index represents the product of the page freeze frequency of the payment query platform and the total freeze time after data normalization processing.

[0019] Preferably, the loading risk index and the query fluency index are compared and analyzed with the preset loading risk index threshold and the preset query fluency index threshold to obtain the first level fluency and the second level fluency, and the first level fluency and the second level fluency are set as the query fluency level CL, CL=1,2.

[0020] Preferably, the interactive query difficulty analysis process is as follows:

[0021] The query impact level CD and query fluency level CL of the payment query platform are obtained, and the value obtained by multiplying the query impact level CD and the query fluency level CL is set as the query barrier coefficient, and the query barrier coefficient is judged:

[0022] If the query obstruction coefficient = 1, a normal signal is generated; if the query obstruction coefficient ≠ 1, an alarm signal is generated.

[0023] Preferably, the query matching quantitative feedback analysis process is as follows:

[0024] The query mode of the user within the time threshold is obtained, and the query mode includes search query and non-search query. The query mode of the user is judged and processed. If the query mode of the user is search query, a search signal is generated. When the search signal is generated, the filled-in information of the user within the time threshold is obtained, and the filled-in information includes year, month, and day. The filled-in information is set to g, where g is a natural number greater than zero.

[0025] And perform character extraction on each filled-in information, and set the character string composed of the character extraction of the user's filled-in information as the query identification string [CX1, CX2, ..., CXg];

[0026] Obtain the query identification string corresponding to the user account number of the user within the time threshold, set it as the preliminary verification identification string, and compare and analyze the preliminary verification identification string with the set query identification string list one by one. If the preliminary verification identification string belongs to the set query identification string list, generate an authorization instruction; if the preliminary verification identification string does not belong to the set query identification string list, generate a jump instruction;

[0027] When an authorization instruction is generated, each query identification string corresponding to the user's filled-in information within the time threshold is obtained, and characters are extracted from each query identification string, and the character string composed of the character extractions of each query identification string is set as the actual query identification string, and the actual query identification string is compared and analyzed with the set query identification string list one by one, and then the query page corresponding to the actual query identification string in the set query identification string list is obtained, and it is set as the query matching page.

[0028] Preferably, the query information integrity evaluation and analysis process is as follows:

[0029] Obtain display information of query matching pages within a time threshold, the display information including a page performance index and a page matching index, compare and analyze the page performance index and the page matching index with a preset page performance index threshold and a preset page matching index threshold, obtain the number of page performance indexes and page matching indexes that are not equal to the preset page performance index threshold and the preset page matching index threshold, set it as a query display deviation index, and perform discrimination processing on the query display deviation index to obtain a qualified signal or an unqualified signal.

[0030] The beneficial effects of the present invention are as follows:

[0031] (1) The present invention analyzes the information processing and information flow of the fee inquiry platform to understand the risk level of the inquiry difficulty of the fee inquiry platform, and interactively analyzes the inquiry impact level CD and the inquiry flow level CL in an information interactive manner, so as to timely manage and adjust the fee inquiry platform to reduce the impact of the fee inquiry platform on subsequent payment inquiries, thereby helping to improve the efficiency and reliability of user payment inquiries;

[0032] (2) The present invention conducts in-depth quantitative feedback analysis of user query matching in an information progressive manner, so as to accurately query payment information, improve the user's query speed and query security, and display and evaluate the query results, so as to timely manage, adjust and sort the query matching page of the payment query platform, so as to improve the user's query efficiency and improve the information integrity and historical record accuracy of the payment query platform. BRIEF DESCRIPTION OF THE DRAWINGS

[0033] The present invention will be further described below in conjunction with the accompanying drawings;

[0034] Figure 1 It is a flowchart of the system of the present invention;

[0035] Figure 2 It is a local analysis reference diagram of the present invention. DETAILED DESCRIPTION

[0036] The following will be combined with the drawings in the embodiments of the present invention to clearly and completely describe the technical solutions in the embodiments of the present invention. Obviously, the described embodiments are only part of the embodiments of the present invention, not all of the embodiments. Based on the embodiments of the present invention, all other embodiments obtained by ordinary technicians in this field without creative work are within the scope of protection of the present invention.

[0037] Embodiment 1:

[0038] See also Figure 1 to Figure 2 As shown, the present invention is a fee comprehensive payment inquiry management system based on data analysis, including a payment inquiry management center, a platform information database, an inquiry obstacle division unit, an inquiry fluency analysis unit, an interactive obstacle analysis unit, an inquiry form authentication unit, an inquiry tracking evaluation unit and an inquiry display unit, wherein the platform information database is connected to the payment inquiry management center in a one-way communication manner, the payment inquiry management center is connected to the inquiry obstacle division unit and the inquiry fluency analysis unit in a one-way communication manner, the inquiry obstacle division unit and the inquiry fluency analysis unit are connected to the interactive obstacle analysis unit in a one-way communication manner, the interactive obstacle analysis unit is connected to the inquiry form authentication unit and the inquiry display unit in a one-way communication manner, the inquiry form authentication unit is connected to the inquiry tracking evaluation unit and the inquiry display unit in a one-way communication manner, and the inquiry tracking evaluation unit is connected to the inquiry display unit in a one-way communication manner;

[0039] The payment inquiry management center is used to retrieve the information update data and inquiry risk information of the payment inquiry platform from the platform information database, and send the information update data and inquiry risk information to the inquiry obstacle classification unit and the inquiry smoothness analysis unit respectively;

[0040] The query barrier division unit is used to perform query impact division analysis on the received information update data to understand the potential risk of payment query on the payment query platform. The specific query impact division analysis process is as follows:

[0041] Set a monitoring cycle and set it as a time threshold, obtain the information update data of the payment query platform within the time threshold, the information update data includes the timeliness information index and the information processing coefficient, compare and analyze the timeliness information index and the information processing coefficient with the preset timeliness information index threshold and the preset information processing coefficient threshold, set the number of timeliness information indexes and information processing coefficients that are greater than or equal to the preset timeliness information index threshold and the preset information processing coefficient threshold as the information reliability index, and perform discriminant analysis on the information reliability index:

[0042] If the information reliability index = 0, it indicates a first-level impact;

[0043] If the information reliability index = 1, it indicates secondary impact;

[0044] If the information reliability index = 2, it indicates a third-level impact, among which the payment query impact corresponding to the first-level impact, the second-level impact and the third-level impact is abnormally increased, and the first-level impact, the second-level impact and the third-level impact are set as the query impact level CD, CD = 1, 2, 3, that is, the query impact level CD = 1 indicates a first-level impact, the query impact level CD = 2 indicates a second-level impact, and the query impact level CD = 3 indicates a third-level impact;

[0045] In the embodiment of the present invention, the timeliness information index indicates the portion of the time between the most recent payment time and the queryable display time on the payment query platform that exceeds the preset time. It should be noted that the larger the value of the timeliness information index is, the greater the potential risk of payment query on the payment query platform is.

[0046] In the embodiment of the present invention, the information processing coefficient represents the ratio between the total number of historical times corresponding to the mismatch between the payment information of the payment query platform and the set payment classification items and the total number of payments, the payment information includes water charges, electricity charges, property fees, etc., and the payment classification items include water charges, electricity charges, property fees, rent items, etc. It should be noted that the larger the value of the information processing coefficient, the greater the impact of the subsequent payment query matching accuracy, and the lower the query accuracy;

[0047] The query fluency analysis unit is used to perform a quantitative analysis of the query information fluency of the received query risk information to understand the risk level of the query difficulty of the payment query platform. The specific query information fluency quantitative analysis process is as follows:

[0048] Obtain the query risk information of the payment query platform within the time threshold, including the loading risk index and the query fluency index;

[0049] In the embodiment of the present invention, the loading risk index represents the product value obtained by multiplying the average page loading time of the payment query platform by the total number of loading failures after data normalization processing, and the number of loading failures represents the number of times that the query result page or the complete query result page is not loaded. It should be noted that the loading risk index is a value that reflects the degree of influence of the page display effect of the payment query platform on the query;

[0050] In the embodiment of the present invention, the query fluency index represents the product value obtained by multiplying the page freeze frequency and the total freeze duration of the payment query platform after data normalization. It should be noted that the query fluency index is an influencing parameter reflecting the page query fluency of the payment query platform. The larger the value of the query fluency index, the greater the query difficulty risk;

[0051] Compare and analyze the loading risk index and query fluency index with the preset loading risk index threshold and the preset query fluency index threshold:

[0052] If the loading risk index is less than the preset loading risk index threshold, and the query fluency index is less than the preset query fluency index threshold, the first-level fluency is determined;

[0053] If the loading risk index is greater than or equal to the preset loading risk index threshold, or the query fluency index is greater than or equal to the preset query fluency index threshold, the second level fluency is determined, wherein the page fluency performance corresponding to the first level fluency and the second level fluency is reduced in sequence, and the first level fluency and the second level fluency are set as the query fluency level CL, CL = 1, 2, that is, the query fluency level CL = 1 indicates the first level fluency, and the query fluency level CL = 2 indicates the second level fluency;

[0054] The interactive obstacle analysis unit is used to perform interactive query difficulty analysis on the query impact level CD and the query fluency level CL, so as to timely manage and adjust the payment query platform to reduce the impact of the payment query platform on subsequent payment queries, thereby helping to improve the user's payment query efficiency and reliability. The specific interactive query difficulty analysis process is as follows:

[0055] The query impact level CD and query fluency level CL of the payment query platform are obtained, and the value obtained by multiplying the query impact level CD and the query fluency level CL is set as the query barrier coefficient, and the query barrier coefficient is judged:

[0056] If the query obstruction coefficient = 1, a normal signal is generated;

[0057] If the query obstacle coefficient ≠ 1, an alarm signal is generated, and the normal signal or the alarm signal is sent to the query display unit. After receiving the normal signal or the alarm signal, the query display unit immediately performs the preset warning operation corresponding to the normal signal or the alarm signal, so as to timely manage and adjust the payment inquiry platform to reduce the impact of the payment inquiry platform on subsequent payment inquiries, thereby helping to improve the user's payment inquiry efficiency and reliability.

[0058] Embodiment 2:

[0059] When a normal signal is generated, the query form authentication unit is used to respond to the normal signal, collect the user's query method, and perform query matching quantitative feedback analysis on the query method so as to accurately query payment information and improve the user's query rate. The specific query matching quantitative feedback analysis process is as follows:

[0060] Get the query mode of users within the time threshold, including search query and non-search query, and distinguish the query mode of users:

[0061] If the user's query method is a non-search query, no signal is generated. If the user's query method is a search query, a search signal is generated. When the search signal is generated, the user's filled-in information within the time threshold is obtained, and the filled-in information includes year, month, day, etc. The filled-in information is set to g, and g is a natural number greater than zero;

[0062] In the embodiment of the present invention, when g=1, it indicates year, when g=2, it indicates month, when g=3, it indicates day, and so on;

[0063] And perform character extraction on each filled-in information, and set the character string composed of the character extraction of the user's filled-in information as the query identification string [CX1, CX2, ..., CXg];

[0064] Obtain the query identification string corresponding to the user account number of the user within the time threshold, set it as the preliminary verification identification string, and compare and analyze the preliminary verification identification string with the set query identification string list one by one. If the preliminary verification identification string belongs to the set query identification string list, generate an authorization instruction. If the preliminary verification identification string does not belong to the set query identification string list, generate a jump instruction. When the jump instruction is generated, immediately make a preset warning operation corresponding to the jump instruction so as to jump to the query page and fill in the query again;

[0065] When the authorization instruction is generated, each query identification string corresponding to the user's filled-in information within the time threshold is obtained, and characters are extracted from each query identification string, and the character string composed of the character extraction of each query identification string is set as the actual query identification string, and the actual query identification string is compared and analyzed with the set query identification string list one by one, and then the query page corresponding to the actual query identification string in the set query identification string list is obtained, and it is set as the query matching page, and the query matching page is sent to the query display unit. After receiving the query matching page, the query display unit immediately jumps to the query matching page, so as to be used for accurate query of payment history information, while improving the user's query rate;

[0066] When the query matching page is obtained, the query tracking and evaluation unit is used to respond to the query matching page, collect the display information of the query matching page, and perform query information integrity evaluation and analysis on the display information, so as to timely manage, adjust and sort the query matching page of the payment query platform to improve user query efficiency, and at the same time improve the information integrity and historical record accuracy of the payment query platform. The specific query information integrity evaluation and analysis process is as follows:

[0067] Obtain display information of query matching pages within a time threshold, the display information including a page performance index and a page matching index, compare and analyze the page performance index and the page matching index with a preset page performance index threshold and a preset page matching index threshold, obtain the number of page performance indexes and page matching indexes that are not equal to the preset page performance index threshold and the preset page matching index threshold, set it as a query display deviation index, and perform judgment processing on the query display deviation index:

[0068] If the query shows that the deviation index is equal to zero, a pass signal is generated;

[0069] If the query display deviation index is not equal to zero, an unqualified signal is generated, and the qualified signal or unqualified signal is sent to the query display unit. After receiving the qualified signal or unqualified signal, the query display unit immediately performs a preset warning operation corresponding to the qualified signal or unqualified signal, so as to timely manage, adjust and sort the query matching page of the payment query platform, so as to improve the user query efficiency, and at the same time improve the information integrity and historical record accuracy of the payment query platform;

[0070] In the embodiment of the present invention, the page performance index represents the difference between the number of payment records actually displayed on the query matching page and the number of payment records displayed by the standard. The user's historical single payment information is set as a standard display payment record. The historical single payment information includes the payment amount, payment time, etc. It should be noted that the larger the value of the page performance index, the greater the risk of missing information on the query matching page, and the greater the risk of abnormal information integrity and historical record accuracy of the payment query platform;

[0071] In the embodiment of the present invention, the page matching index indicates the number of differences between the data display sorting of the query matching page and the set sorting. It should be noted that the larger the value of the page matching index, the greater the risk of information confusion, the higher the data sorting management requirements of the payment query platform, and the greater the risk of abnormal query efficiency;

[0072] In summary, the present invention analyzes the information processing and information flow of the payment inquiry platform to understand the risk level of the inquiry difficulty of the payment inquiry platform, and interactively analyzes the query impact level CD and the query flow level CL obtained in an information interactive manner, so as to timely manage and adjust the payment inquiry platform to reduce the impact of the payment inquiry platform on subsequent payment inquiries, thereby helping to improve the payment inquiry efficiency and reliability of users;

[0073] Through the progressive use of information, we conduct in-depth quantitative feedback analysis on user query matching to accurately query payment information, improve user query speed and query security, and display and evaluate query results so that the query matching page of the payment query platform can be managed, adjusted and sorted in a timely manner to improve user query efficiency while improving the information integrity and historical record accuracy of the payment query platform.

[0074] The threshold is set to facilitate comparison. The size of the threshold depends on the amount of sample data and the number of bases set by technicians in this field for each group of sample data; as long as it does not affect the proportional relationship between the parameter and the quantized value.

[0075] The above description is only a preferred specific implementation manner of the present invention, but the protection scope of the present invention is not limited thereto. Any technician familiar with the technical field can make equivalent replacements or changes according to the technical scheme and inventive concept of the present invention within the technical scope disclosed by the present invention, which should be covered by the protection scope of the present invention.

Claims

1. A comprehensive fee payment query and management system based on data analysis, characterized in that: It includes a payment inquiry management center, a platform information database, an inquiry obstacle classification unit, an inquiry flow analysis unit, an interactive obstacle analysis unit, an inquiry form authentication unit, an inquiry tracking and evaluation unit, and an inquiry display unit; The payment inquiry management center is used to retrieve the information update data and inquiry risk information of the payment inquiry platform from the platform information database, and send the information update data and inquiry risk information to the inquiry obstacle classification unit and the inquiry smoothness analysis unit respectively; The query obstacle partitioning unit is used to perform query impact partitioning analysis on the received information update data, perform discriminant analysis on the obtained information reliability index, and obtain the query impact level CD; The query fluency analysis unit is used to perform a quantitative analysis of the query information fluency of the received query risk information to obtain a query fluency level CL; The interactive obstacle analysis unit is used to perform interactive query difficulty analysis on the query impact level CD and the query fluency level CL, and to perform discrimination processing on the obtained query obstacle coefficient to obtain a normal signal or an alarm signal; The query form authentication unit is used to respond to normal signals, collect the user's query method, perform query matching quantitative feedback analysis on the query method, and obtain a query matching page; The query tracking and evaluation unit is used to respond to the query matching page and collect the display information of the query matching page, and at the same time perform query information integrity evaluation and analysis on the display information to obtain a qualified signal or a unqualified signal.

2. According to the data analysis-based fee comprehensive payment query and management system of claim 1, it is characterized in that: The query impact partition analysis process is as follows: A monitoring period is set and set as a time threshold, and information update data of the payment inquiry platform within the time threshold is obtained, the information update data including an effectiveness information index and an information processing coefficient, and the effectiveness information index and the information processing coefficient are compared and analyzed with a preset effectiveness information index threshold and a preset information processing coefficient threshold, and the number of effectiveness information indexes and information processing coefficients that are greater than or equal to the preset effectiveness information index threshold and the preset information processing coefficient threshold is set as the information reliability index, and a discriminant analysis is performed on the information reliability index to obtain a first-level impact, a second-level impact and a third-level impact, and the first-level impact, the second-level impact and the third-level impact are set as the query impact level CD, CD=1, 2, 3.

3. According to claim 2, a comprehensive fee payment query and management system based on data analysis is characterized in that: The timeliness information index indicates the portion of the time between the most recent payment time and the time that can be queried and displayed on the payment inquiry platform that exceeds the preset time; the information processing coefficient indicates the ratio between the total number of historical times corresponding to the mismatch between the payment information of the payment inquiry platform and the set payment classification items and the total number of payments, the payment information includes water charges, electricity charges, and property fees, and the payment classification items include water charges, electricity charges, property fees, and rent items.

4. According to the data analysis-based fee comprehensive payment query and management system of claim 1, it is characterized in that: The quantitative analysis process of the query information fluency is as follows: Obtain the query risk information of the payment query platform within the time threshold, including the loading risk index and the query fluency index; The loading risk index represents the product of the average page loading time of the payment query platform and the total number of loading failures after data normalization, and the number of loading failures represents the number of times the query result page or the complete query result page is not loaded; The query fluency index represents the product of the page freeze frequency of the payment query platform and the total freeze duration after data normalization processing.

5. According to claim 4, a comprehensive fee payment query and management system based on data analysis is characterized in that: The loading risk index and the query fluency index are compared and analyzed with the preset loading risk index threshold and the preset query fluency index threshold to obtain the first level fluency and the second level fluency, and the first level fluency and the second level fluency are set as the query fluency level CL, CL=1,2.

6. According to the data analysis-based fee comprehensive payment query and management system of claim 1, it is characterized in that: The interactive query difficulty analysis process is as follows: The query impact level CD and query fluency level CL of the payment query platform are obtained, the value obtained by multiplying the query impact level CD and the query fluency level CL is set as the query barrier coefficient, and the query barrier coefficient is judged: if the query barrier coefficient = 1, a normal signal is generated; if the query barrier coefficient ≠ 1, an alarm signal is generated.

7. According to the data analysis-based fee comprehensive payment query and management system of claim 1, it is characterized in that: The query matching quantitative feedback analysis process is as follows: The query mode of the user within the time threshold is obtained, and the query mode includes search query and non-search query. The query mode of the user is judged and processed. If the query mode of the user is search query, a search signal is generated. When the search signal is generated, the filled-in information of the user within the time threshold is obtained, and the filled-in information includes year, month, and day. The filled-in information is set to g, where g is a natural number greater than zero. And perform character extraction on each filled-in information, and set the character string composed of the character extraction of the user's filled-in information as the query identification string [CX1, CX2, ..., CXg]; Obtain the query identification string corresponding to the user account number of the user within the time threshold, set it as the preliminary verification identification string, and compare and analyze the preliminary verification identification string with the set query identification string list one by one. If the preliminary verification identification string belongs to the set query identification string list, generate an authorization instruction; if the preliminary verification identification string does not belong to the set query identification string list, generate a jump instruction; When an authorization instruction is generated, each query identification string corresponding to the user's filled-in information within the time threshold is obtained, and characters are extracted from each query identification string, and the character string composed of the character extractions of each query identification string is set as the actual query identification string, and the actual query identification string is compared and analyzed with the set query identification string list one by one, and then the query page corresponding to the actual query identification string in the set query identification string list is obtained, and it is set as the query matching page.

8. According to the data analysis-based fee comprehensive payment query and management system of claim 1, it is characterized in that: The query information integrity evaluation and analysis process is as follows: Obtain display information of query matching pages within a time threshold, the display information including a page performance index and a page matching index, compare and analyze the page performance index and the page matching index with a preset page performance index threshold and a preset page matching index threshold, obtain the number of page performance indexes and page matching indexes that are not equal to the preset page performance index threshold and the preset page matching index threshold, set it as a query display deviation index, and perform discrimination processing on the query display deviation index to obtain a qualified signal or an unqualified signal.

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