A diversified data intelligent management method and system based on big data

Abstract

The present invention discloses a diversified data intelligent management method and system based on big data, which relates to the field of diversified data management technology, including: S1: obtaining business conditions in a diversified business processing platform; S2: monitoring the diversified business processing platform and obtaining user login data; and analyzing the user's business handling intention based on the current user login data; S3: analyzing the relationship between each business based on the obtained business conditions in the diversified business processing platform and the connection between the corresponding data items of each business; S4: extracting the user's relevant data in the current business based on the user's business handling selection, and managing the extracted user-related data in the current business based on the relationship between the businesses and the connection between the corresponding data items of each business obtained by S3 analysis; it can accurately understand user needs and improve business operation efficiency and user business handling experience.

Description

Technical Field

[0001] The present invention relates to the technical field of multivariate data management, and in particular to a method and system for intelligent management of diversified data based on big data. Background Art

[0002] Diversified data refers to data with diversity and richness, including data of different types, sources and forms, which can come from various business systems, sensors, social media and other channels. The mining and analysis of diversified data can bring more comprehensive, accurate and in-depth business insights. Enterprises can use diversified data to discover implicit associations, trends and patterns to support decision-making, marketing, customer relationship management and business innovation.

[0003] As the demand for diversified data changes, building a unified diversified business processing platform to achieve real-time exchange and sharing of electronic data and complete the collection of multi-dimensional data has become a popular trend. As platform data accumulates and platform business expands, the complexity of managing diversified data increases, which increases the difficulty of data quality control. At the same time, since there are many functional modules in the diversified business processing platform, when users use it, due to unfamiliar business processes or more data submission required for business processing, the user's workload is increased to a certain extent, the business processing efficiency is reduced, and the user experience is affected.

[0004] Therefore, in order to solve the above problems or part of the problems, the present invention provides a diversified data intelligent management method and system based on big data. Summary of the invention

[0005] The purpose of the present invention is to provide a diversified data intelligent management method and system based on big data to solve the problems raised in the above background technology.

[0006] In order to solve the above technical problems, the present invention provides the following technical solutions: a diversified data intelligent management method based on big data, comprising the following steps:

[0007] S1: Obtaining the business situation in the diversified business processing platform, wherein the business situation includes the number of businesses, data items corresponding to each business, and the current number of visits to the business, wherein the data items corresponding to each business are a set of corresponding data elements required for the user to handle each business when using the diversified business processing platform;

[0008] S2: Monitor the diversified business processing platform and obtain user login data, which includes user account related information, user current login location data and user historical login data; and analyze the user's business handling intention based on the current user login data;

[0009] S3: Analyze the relationship between various businesses based on the business conditions in the diversified business processing platform and the connections between the corresponding data items of various businesses;

[0010] S4: According to the user's business handling selection, the user's relevant data in the current business is extracted, and according to the relationship between the various businesses and the connection between the corresponding data items of each business obtained by S3 analysis, the extracted user-related data in the current business is managed.

[0011] Further, the S1 includes:

[0012] Step S1-1: The service set in the obtained diversified service processing platform is recorded as W, wherein W includes {W1, W2, ..., W n}, where W1, W2, ..., W n denote the 1st, 2nd, ..., nth services in the diversified service processing platform respectively; let services W1, W2, ..., W n The corresponding business visits are Q W1 , Q W2 , ..., Q Wn ;

[0013] Step S1-2: Set the i-th service W i The corresponding data item is denoted as S i , the S i Included i1 , S i2 , ..., S im}, where S i1 , S i2 ,...,S im They respectively represent the 1st, 2nd, ..., mth data elements in the data item corresponding to the i-th business.

[0014] Further, the S2 includes:

[0015] Step S2-1: Monitor the diversified business processing platform. When a user logs in, trigger the user login data detection, request data access rights from the user, and obtain the user's current login location data through IP address or GPS positioning technology;

[0016] Step S2-2: Track the user's login process, and obtain relevant information about the account in the cloud database of the diversified business processing platform according to the user's login account, wherein the account-related information includes information records when the user registers the account and historical data of the user account;

[0017] Step S2-3: Read the historical login data of the device used by the current user, wherein the historical login data includes the historical login account and the account-related information corresponding to the historical login account;

[0018] Step S2-4: Analyze the user's business handling intention according to the current user login data, including:

[0019] S2-4-1: The user's current login location data is judged. If the user's current login location belongs to a business handling point recorded in the diversified business processing platform, it is considered that the current user's first business handling intention is a business within the business scope that can be handled by the business handling point at the current location;

[0020] S2-4-2: Analyze the user's login account related information; extract the user account information record and classify it, add category tags to the user account according to the information record when the user registered, and combine the target user tags of each business preset in the platform database to determine that the current user's first business handling intention is a business whose business target user tag in the diversified business processing platform matches the current account category tag;

[0021] S2-4-3: Analyze the historical login data of the device used by the current user, extract the historical login account of the device used by the current user, if the number of historical login accounts of the device used by the current user is greater than or equal to the threshold k preset by the relevant staff, the device is considered to be a relevant business processing device, and the data storage location of the device involving the platform data is restricted through the diversified business processing platform, and a data cleaning cycle is set. The device uses the temporary data of the meta-business processing platform for cleaning, so as to protect the user's information data security and avoid user privacy leakage caused by business processing;

[0022] If the number of historical login accounts of the device used by the current user is less than the threshold k preset by the relevant staff, obtain the relevant account information corresponding to the historical login account. When the account information mapping of the historical login account overlaps, it is considered that the user uses the current device to assist in business processing, and the current device is allowed to store platform data;

[0023] Combined with the usage record of the historical login account of the current device, it is considered that the service whose frequency of services selected for handling in the historical login account of the current device exceeds the threshold value P is the first service handling intention of the current user;

[0024] The frequency of any service u = the number of times service u is handled in the historical login account / the total number of times services are handled in the historical login account.

[0025] Further, the S3 includes:

[0026] Step S3-1: Process the acquired service set, set each service in the service set W as a service node, set the access limit of each service node according to the real-time service access volume corresponding to each service, the access limit represents the upper limit of the real-time access quantity of any service node, obtain the access limit of each service node through the current service access volume and the corresponding service capacity in the test report, update the remaining access volume of each service and the connection requests initiated by other services in real time; pre-connect each service node, and build a service node relationship diagram;

[0027] Step S3-2: Analyze the pre-connection of any two task nodes in the business node relationship diagram; extract the data items corresponding to each business node, and detect the data elements in the data items corresponding to each business node; suppose the data item corresponding to the jth business node contains the data element set {S j1 , S j2 , ..., S jg}, where S j1 , S j2 ,...,S jg They represent the 1st, 2nd, ..., gth data elements in the data item corresponding to the jth business. When the jth business node completes the business processing, the data element set {H j1 , H j2 , ..., H jG}; If there are overlapping data elements between the data obtained after passing through the jth business node and the data elements in the data items of any other business node, it is determined that there is a data connection relationship between the jth business node and any other business node, and the pre-connection between the two nodes in the business node relationship diagram is confirmed. In the data connection, the jth business node is considered to be the initiator of the data connection;

[0028] According to the first service handling intention of the current user obtained by analyzing in S2, the connected services of the services included in the first service handling intention in the service node relationship diagram are obtained and set as the second service handling intention of the current user;

[0029] Since users need to input basic information or provide various materials to upload to the platform when handling business, the platform can split the user's uploaded data or adjust the data format after receiving it for data storage, so the data elements in the data items corresponding to each business are different before and after the business is handled;

[0030] Step S3-3: Analyze the hierarchical relationship between any two task nodes in the business node relationship graph; extract the connection relationship between each business node. If there are β business nodes that initiate a connection pointing to any business node R, it is considered that these β business nodes have a combination relationship, mark the business node combination, and set the business nodes in the same business node combination to the same level; set the business node pointed to by the business node combination to the upper level of the business node combination;

[0031] According to the first business handling intention of the current user obtained by analyzing in S2, when the business included in the first business handling intention has an upper level in the business node relationship diagram, the upper level business of the business included in the first business handling intention is set as the second business handling intention of the current user, and other businesses in the same combination of the businesses included in the first business handling intention are set as the third business handling intention of the current user.

[0032] Further, S4 includes:

[0033] Step S4-1: Monitor the user's business handling behavior on the diversified business processing platform, obtain the current user's business selection, and obtain relevant data of the user in the current business handling process; assume that the user's current business handling is the current user's first business handling intention, and combine the business relationships obtained by the analysis in S3 to extract the second business handling intention or the third business handling intention corresponding to the user's current business handling; obtain the real-time access volume of each business in the current diversified business processing platform, and screen the business within the second business handling intention or the third business handling intention corresponding to the user's current business handling in combination with the access limit of each business. The specific steps include:

[0034] Z1: By setting critical values, the business access volume classification standard is formulated, and the business access volume is divided into three levels: high, medium and low;

[0035] Z2: Evaluate the services within the second service handling intention or the third service handling intention corresponding to the current service handled by the user according to the grading standard, determine the level of the real-time access volume of each service by comparing the real-time access volume with the preset critical value, and add a level mark to each service according to the grading result;

[0036] Z3: According to the level identification of each service, when there is a high-visit service within the second service handling intention or the third service handling intention, reduce the recommendation weight of the high-visit service;

[0037] Among them, each business within the scope of the second business handling intention or the third business handling intention has an initial recommendation weight, which is set according to the business relationship and business level identifier; combined with real-time access volume data, the recommendation weight of each business can be dynamically adjusted;

[0038] When the same high-visited service exists within the second service handling intention or the third service handling intention range of multiple users on the platform, 50% of the users are randomly selected, and the weight of the high-visited service in the recommended services of the selected users is reduced, that is, the ranking priority of the high-visited service in the platform recommended services of the selected 50% of users is reduced;

[0039] If the number of visits to any service M in the second service handling intention or the third service handling intention reaches the critical value of the upper limit of the number of visits to the service M, the service M in the second service handling intention or the third service handling intention corresponding to the current service handled by the user will be removed and will not be recommended;

[0040] Combined with the interface visualization rules of the diversified business processing platform, the second business handling intention or the third business handling intention of the current user after screening is added to the interface recommendation position of the current user; so that the user can more easily find the corresponding pending business, provide targeted personalized recommendation services, improve the user's business handling efficiency, and enhance the user's experience and satisfaction;

[0041] Step S4-2: extract the relevant data of the user in the current business process, integrate the extracted user-related data in the current business according to the business connection relationship analyzed in S3, manage the transmission of user-related data in combination with the pointing relationship of each business, encrypt and transmit the user-related data in the current business to the next business according to the business access volume, and perform data verification on the relevant data after the data transmission is completed to ensure the integrity of the data;

[0042] Step S4-3: Record the login behavior and operation behavior of the current user on the diversified business processing platform. A database or log file may be used to store these records. The operation behavior includes the actual interaction between the user and the diversified business processing platform, so as to facilitate subsequent analysis of user behavior to optimize the user experience.

[0043] A diversified data intelligent management system based on big data, the system comprising: a data acquisition module, a data analysis module, a data monitoring module and a data intelligent management module;

[0044] The data collection module is used to collect relevant data in the diversified business processing platform to provide data sources for subsequent data analysis;

[0045] The data analysis module is used to analyze and mine relevant data collected from the diversified business processing platform; using big data analysis and mining technology, it can discover trends, associations and patterns in the data and generate insightful analysis results;

[0046] The data monitoring module is used to monitor user behavior and business status in the diversified business processing platform, which can be obtained through the front-end embedding technology;

[0047] The data intelligent management module is used to intelligently manage the relevant data of the diversified business processing platform based on the monitoring data of the data monitoring module in combination with the data analysis results of the data analysis module, so as to realize the automatic operation and intelligent decision-making of the system.

[0048] Further, the data acquisition module includes a platform business data acquisition unit, a user login data acquisition unit and a business-related data synchronization unit;

[0049] The platform service data acquisition unit is used to identify and acquire available services in the current diversified service processing platform;

[0050] The user login data acquisition unit is used to acquire user login data when a user logs into the diversified business processing platform in real time, including user account related information, user current login location data and user historical login data;

[0051] The business-related data synchronization unit is used to obtain relevant data generated in real time by each business in the diversified business processing platform, and synchronously update the corresponding data in the cloud database according to the real-time data.

[0052] Furthermore, the data analysis module includes a user login data analysis unit, a user business handling intention analysis unit and a business relationship analysis unit;

[0053] The user login data analysis unit is used to analyze the user login data and obtain the user's first service handling intention through user login data mining;

[0054] The business relationship analysis unit is used to analyze the relationship between the businesses according to the data items included in each business in the diversified business processing platform;

[0055] The user service handling intention analysis unit is used to analyze the user's next service handling intention based on the user's first service handling intention and according to the service relationship analysis result.

[0056] Furthermore, the data monitoring module includes a user login behavior monitoring unit, a user service handling behavior monitoring unit and a service access situation monitoring unit;

[0057] The user login behavior monitoring unit is used to monitor the behavior of logging into the diversified business processing platform, and process and store the monitoring data;

[0058] The user business handling behavior monitoring unit is used to monitor the user's business handling selection and business handling progress on the diversified business processing platform, and obtain the user's business handling behavior in real time;

[0059] The service access situation monitoring unit is used to monitor the real-time access volume of each service in the diversified service processing platform and obtain the access situation of each service.

[0060] Furthermore, the data intelligent management module includes a data storage management unit, a data transmission management unit and a business intelligent recommendation unit;

[0061] The data storage management unit is used to perform corresponding storage management on the current user's usage data of the diversified business processing platform according to the user login behavior analysis result;

[0062] The data transmission management unit is used to manage the transmission of the user's uploaded data according to the user's business handling behavior combined with the user's business handling intention analysis result;

[0063] The intelligent business recommendation unit is used to recommend business to the current user based on the analysis results of the user's business handling behavior and the user's business handling intention, combined with the business access situation. Through intelligent business recommendations, it can help users improve their business handling efficiency. At the same time, it can reasonably regulate the access traffic of each business in the platform and improve the data processing speed of each business.

[0064] Compared with the prior art, the beneficial effects achieved by the present invention are:

[0065] The present invention can obtain the business situation in the diversified business processing platform through S1, and the business situation includes the number of businesses, the data items corresponding to each business and the current number of visits to the business, so as to fully understand the type, quantity, growth trend and other information of the business, and provide a basis for the enterprise to formulate strategies and make decisions;

[0066] Through S2, the diversified business processing platform is monitored to obtain user login data, which includes user account related information, user current login location data and user historical login data; and the user's business handling intention is analyzed based on the current user login data; the user's login behavior and usage habits can be understood, and the user's business handling intention can also be inferred based on the current user login data, which helps to optimize the user experience, provide personalized services, and perform refined operations based on user needs.

[0067] S3 analyzes the relationship between various businesses based on the business conditions in the diversified business processing platform and the connections between the corresponding data items of each business. Combining the business conditions in the diversified business processing platform and the connections between the corresponding data items of each business, it can deeply analyze the relationship between various businesses, which helps to discover the mutual influence and dependency between businesses, and provide support for cross-business collaboration, resource allocation and business optimization.

[0068] Through S4, the user's relevant data in the current business is extracted according to the user's business processing selection, and the extracted user-related data in the current business is managed according to the relationship between each business and the connection between the corresponding data items of each business obtained by S3 analysis; this helps to centrally manage user data, improve data availability and accuracy, and protect the security and privacy of user data; it can accurately understand user needs, optimize business processes, and improve business operation efficiency and user business processing experience. BRIEF DESCRIPTION OF THE DRAWINGS

[0069] The accompanying drawings are used to provide a further understanding of the present invention and constitute a part of the specification. Together with the embodiments of the present invention, they are used to explain the present invention and do not constitute a limitation of the present invention. In the accompanying drawings:

[0070] Figure 1 It is a schematic diagram of the module structure of a diversified data intelligent management system based on big data of the present invention;

[0071] Figure 2 It is a flow chart of a diversified data intelligent management method based on big data of the present invention. DETAILED DESCRIPTION

[0072] 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.

[0073] See also Figure 1 , Figure 2 The present invention is further described with reference to the accompanying drawings and specific embodiments.

[0074] Example 1: Figure 1 As shown, this embodiment provides a diversified data intelligent management system based on big data, the system includes: a data acquisition module, a data analysis module, a data monitoring module and a data intelligent management module;

[0075] The data collection module is used to collect relevant data in the diversified business processing platform; the data collection module includes a platform business data acquisition unit, a user login data acquisition unit and a business-related data synchronization unit;

[0076] The platform business data acquisition unit is used to identify and acquire the available businesses in the current diversified business processing platform;

[0077] The user login data acquisition unit is used to acquire the user login data when the user logs into the diversified business processing platform in real time, including user account related information, user current login location data and user historical login data;

[0078] The business-related data synchronization unit is used to obtain the relevant data generated in real time by each business in the diversified business processing platform, and synchronously update the corresponding data in the cloud database according to the real-time data.

[0079] The data analysis module is used to analyze and mine the relevant data collected from the diversified business processing platform; the data analysis module includes a user login data analysis unit, a user business processing intention analysis unit, and a business relationship analysis unit;

[0080] The user login data analysis unit is used to analyze the user login data and obtain the user's first business handling intention through user login data mining;

[0081] The business relationship analysis unit is used to analyze the relationship between various businesses according to the data items included in each business in the diversified business processing platform;

[0082] The user service handling intention analysis unit is used to analyze the user's next service handling intention based on the user's first service handling intention and according to the service relationship analysis result.

[0083] The data monitoring module is used to monitor user behavior and business status in the diversified business processing platform, which can be obtained through the front-end embedding technology; the data monitoring module includes a user login behavior monitoring unit, a user business handling behavior monitoring unit and a business access status monitoring unit;

[0084] The user login behavior monitoring unit is used to monitor the behavior of logging into the diversified business processing platform and process and store the monitoring data;

[0085] The user business handling behavior monitoring unit is used to monitor the user's business handling selection and business handling progress on the diversified business processing platform, and obtain the user's business handling behavior in real time;

[0086] The service access situation monitoring unit is used to monitor the real-time access volume of each service in the diversified service processing platform and obtain the access situation of each service.

[0087] The data intelligent management module is used to intelligently manage the relevant data of the diversified business processing platform based on the monitoring data of the data monitoring module and the data analysis results of the data analysis module, so as to realize the automatic operation and intelligent decision-making of the system; the data intelligent management module includes a data storage management unit, a data transmission management unit and a business intelligent promotion unit;

[0088] The data storage management unit is used to perform corresponding storage management on the current user's usage data of the diversified business processing platform according to the user login behavior analysis results;

[0089] The data transmission management unit is used to manage the transmission of the user's uploaded data according to the user's business handling behavior and the user's business handling intention analysis result;

[0090] The intelligent business recommendation unit is used to recommend business to current users based on the analysis results of user business handling behavior and user business handling intention, combined with business access conditions. Through intelligent business recommendations, it can help users improve their business handling efficiency. At the same time, it can reasonably regulate the access traffic of each business within the platform and improve the data processing speed of each business.

[0091] Example 2: Figure 2 As shown, this embodiment provides a diversified data intelligent management method based on big data, which is implemented based on a diversified data intelligent management system based on big data in the embodiment, and specifically includes the following steps:

[0092] S1: Obtaining the business situation in the diversified business processing platform, wherein the business situation includes the number of businesses, data items corresponding to each business, and the current number of visits to the business, wherein the data items corresponding to each business are a set of corresponding data elements required for the user to handle each business when using the diversified business processing platform;

[0093] Step S1-1: The service set in the obtained diversified service processing platform is recorded as W, wherein W includes {W1, W2, ..., W n}, where W1, W2, ..., W n denote the 1st, 2nd, ..., nth services in the diversified service processing platform respectively; let services W1, W2, ..., W n The corresponding business visits are Q W1 , Q W2 , ..., Q Wn ;

[0094] Step S1-2: Set the i-th service W iThe corresponding data item is denoted as S i , the S i Included i1 , S i2 , ..., S im}, where S i1 , S i2 ,...,S im They respectively represent the 1st, 2nd, ..., mth data elements in the data item corresponding to the i-th business.

[0095] S2: Monitor the diversified business processing platform and obtain user login data, which includes user account related information, user current login location data and user historical login data; and analyze the user's business handling intention based on the current user login data;

[0096] Step S2-1: Monitor the diversified business processing platform. When a user logs in, trigger the user login data detection, request data access rights from the user, and obtain the user's current login location data through IP address or GPS positioning technology;

[0097] Step S2-2: Track the user's login process, and obtain relevant information about the account in the cloud database of the diversified business processing platform according to the user's login account, wherein the account-related information includes information records when the user registers the account and historical data of the user account;

[0098] Step S2-3: Read the historical login data of the device used by the current user, wherein the historical login data includes the historical login account and the account-related information corresponding to the historical login account;

[0099] Step S2-4: Analyze the user's business handling intention according to the current user login data, including:

[0100] S2-4-1: The user's current login location data is judged. If the user's current login location belongs to a business handling point recorded in the diversified business processing platform, it is considered that the current user's first business handling intention is a business within the business scope that can be handled by the business handling point at the current location;

[0101] S2-4-2: Analyze the user's login account related information; extract the user account information records and classify them, add category tags to the user account according to the information records when the user registered, for example, divide the user category according to the occupation, age, gender and other tags filled in by the user when registering; combine the target user tags of each business preset in the platform database, and consider that the first business processing intention of the current user is the business that matches the business target user tag in the diversified business processing platform with the current account category tag;

[0102] S2-4-3: Analyze the historical login data of the device used by the current user, extract the historical login account of the device used by the current user, if the number of historical login accounts of the device used by the current user is greater than or equal to the threshold k preset by the relevant staff, the device is considered to be a relevant business processing device, and the data storage location of the device involving the platform data is restricted through the diversified business processing platform, and a data cleaning cycle is set. The device uses the temporary data of the meta-business processing platform for cleaning, so as to protect the user's information data security and avoid user privacy leakage caused by business processing;

[0103] If the number of historical login accounts of the device used by the current user is less than the threshold k preset by the relevant staff, obtain the relevant account information corresponding to the historical login account. When the account information mapping of the historical login account overlaps, it is considered that the user uses the current device to assist in business processing, and the current device is allowed to store platform data;

[0104] Combined with the usage record of the historical login account of the current device, it is considered that the service whose frequency of services selected for handling in the historical login account of the current device exceeds the threshold value P is the first service handling intention of the current user;

[0105] The frequency of any service u = the number of times service u is handled in the historical login account / the total number of times services are handled in the historical login account.

[0106] S3: Analyze the relationship between various businesses based on the business conditions in the diversified business processing platform and the connections between the corresponding data items of various businesses;

[0107] Step S3-1: Process the acquired service set, set each service in the service set W as a service node, set the access limit of each service node according to the real-time service access volume corresponding to each service; pre-connect each service node and construct a service node relationship diagram;

[0108] Step S3-2: Analyze the pre-connection of any two task nodes in the business node relationship diagram; extract the data items corresponding to each business node, and detect the data elements in the data items corresponding to each business node; suppose the data item corresponding to the jth business node contains the data element set {S j1 , S j2 , ..., S jg}, where S j1 , S j2 ,...,S jg They represent the 1st, 2nd, ..., gth data elements in the data item corresponding to the jth business. When the jth business node completes the business processing, the data element set {H j1 , H j2, ..., H jG}; If there are overlapping data elements between the data obtained after passing through the jth business node and the data elements in the data items of any other business node, it is determined that there is a data connection relationship between the jth business node and any other business node, and the pre-connection between the two nodes in the business node relationship diagram is confirmed. In the data connection, the jth business node is considered to be the initiator of the data connection;

[0109] According to the first service handling intention of the current user obtained by analyzing in S2, the connected services of the services included in the first service handling intention in the service node relationship diagram are obtained and set as the second service handling intention of the current user;

[0110] For example, the data item S corresponding to the i-th business node i , when S i The data element set represented by {S i1 , S i2 , ..., S im} and the data element set H obtained after passing through the jth business node j ={H j1 , H j2 , ..., H jG}exist Then the i-th business node and the j-th business node have a connection relationship W i →W j ; where i, j∈[1, n], and i≠j. At the same time, business W i If the current user intends to handle the first service, then the service W j Add the current user as a candidate for the second business handling intention;

[0111] Step S3-3: Analyze the hierarchical relationship between any two task nodes in the business node relationship graph; extract the connection relationship between each business node. If there are β business nodes that initiate a connection pointing to any business node R, it is considered that these β business nodes have a combination relationship, mark the business node combination, and set the business nodes in the same business node combination to the same level; set the business node pointed to by the business node combination to the upper level of the business node combination;

[0112] According to the first service handling intention of the current user obtained by analyzing in S2, when the service included in the first service handling intention has an upper level in the service node relationship diagram, the upper level service of the service included in the first service handling intention is set as the second service handling intention of the current user, and other services in the same combination of the services included in the first service handling intention are set as the third service handling intention of the current user;

[0113] Different business data can be combined to form a larger data set or data structure. For example, customer information data items, order information data items, and product information data items can be combined into a complete sales record data set. At the same time, when managing data items at a higher level, managing the data according to the hierarchical structure can flexibly adjust and expand business data to adapt to different business needs, ensure data consistency and accuracy, and help organize and analyze data at each level.

[0114] S4: extract the user's relevant data in the current business according to the user's business selection, and manage the extracted user-related data in the current business according to the relationship between the businesses and the connection between the corresponding data items of the businesses obtained by S3 analysis;

[0115] Step S4-1: Monitor the user's business handling behavior on the diversified business processing platform, obtain the current user's business selection, and obtain relevant data of the user in the current business handling process; assume that the user's current business handling is the current user's first business handling intention, and combine the business relationships obtained by the analysis in S3 to extract the second business handling intention or the third business handling intention corresponding to the user's current business handling; obtain the real-time access volume of each business in the current diversified business processing platform, and screen the business within the second business handling intention or the third business handling intention corresponding to the user's current business handling in combination with the access limit of each business. The specific steps include:

[0116] Z1: By setting critical values, the business access volume classification standard is formulated, and the business access volume is divided into three levels: high, medium and low;

[0117] Z2: Evaluate the services within the second service handling intention or the third service handling intention corresponding to the current service handled by the user according to the grading standard, determine the level of the real-time access volume of each service by comparing the real-time access volume with the preset critical value, and add a level mark to each service according to the grading result;

[0118] Z3: According to the level identification of each service, when there is a high-visit service within the second service handling intention or the third service handling intention, reduce the recommendation weight of the high-visit service;

[0119] Among them, each business within the scope of the second business handling intention or the third business handling intention has an initial recommendation weight, which is set according to the business relationship and business level identifier; combined with real-time access volume data, the recommendation weight of each business can be dynamically adjusted;

[0120] When the same high-visited service exists within the second service handling intention or the third service handling intention range of multiple users on the platform, 50% of the users are randomly selected, and the weight of the high-visited service in the recommended services of the selected users is reduced, that is, the ranking priority of the high-visited service in the platform recommended services of the selected 50% of users is reduced;

[0121] If the number of visits to any service M in the second service handling intention or the third service handling intention reaches the critical value of the upper limit of the number of visits to the service M, the service M in the second service handling intention or the third service handling intention corresponding to the current service handled by the user will be removed and will not be recommended;

[0122] Combined with the interface visualization rules of the diversified business processing platform, the screened second business handling intention or third business handling intention of the current user is added to the interface recommendation position of the current user;

[0123] It makes it easier for users to find the corresponding pending business, provides targeted personalized recommendation services, improves the efficiency of users' business handling, and enhances users' experience and satisfaction;

[0124] Step S4-2: extract the relevant data of the user in the current business process, integrate the extracted user-related data in the current business according to the business connection relationship analyzed in S3, manage the transmission of user-related data in combination with the pointing relationship of each business, encrypt and transmit the user-related data in the current business to the next business according to the business access volume, and perform data verification on the relevant data after the data transmission is completed to ensure the integrity of the data;

[0125] Step S4-3: Record the login behavior and operation behavior of the current user on the diversified business processing platform. A database or log file may be used to store these records. The operation behavior includes the actual interaction between the user and the diversified business processing platform, so as to facilitate subsequent analysis of user behavior to optimize the user experience.

[0126] It should be noted that, in this article, relational terms such as first and second, etc. are only used to distinguish one entity or operation from another entity or operation, and do not necessarily require or imply any such actual relationship or order between these entities or operations. Moreover, the terms "include", "comprise" or any other variants thereof are intended to cover non-exclusive inclusion, so that a process, method, article or device including a series of elements includes not only those elements, but also other elements not explicitly listed, or also includes elements inherent to such process, method, article or device.

[0127] Finally, it should be noted that the above description is only a preferred embodiment of the present invention and is not intended to limit the present invention. Although the present invention has been described in detail with reference to the aforementioned embodiments, those skilled in the art can still modify the technical solutions described in the aforementioned embodiments or replace some of the technical features therein by equivalents. Any modification, equivalent replacement, improvement, etc. made within the spirit and principle of the present invention shall be included in the protection scope of the present invention.

Claims

1. A diversified data intelligent management method based on big data, characterized by: The following steps are involved: S1: Obtaining the business situation in the diversified business processing platform, wherein the business situation includes the number of businesses, data items corresponding to each business, and the current number of visits to the business, wherein the data items corresponding to each business are a set of corresponding data elements required for the user to handle each business when using the diversified business processing platform; S2: Monitor the diversified business processing platform and obtain user login data, wherein the user login data includes user account related information, user current login location data and user historical login data; And analyze the user's business handling intention based on the current user login data; S3: Analyze the relationship between various businesses based on the business conditions in the diversified business processing platform and the connections between the corresponding data items of various businesses; S4: extract the user's relevant data in the current business according to the user's business selection, and manage the extracted user-related data in the current business according to the relationship between the businesses and the connection between the corresponding data items of the businesses obtained by S3 analysis; The S2 includes: Step S2-1: Monitor the diversified business processing platform. When a user logs in, trigger the user login data detection, request data access rights from the user, and obtain the user's current login location data through IP address or GPS positioning technology; Step S2-2: Track the user's login process, and obtain relevant information about the account in the cloud database of the diversified business processing platform according to the user's login account, wherein the account-related information includes information records when the user registers the account and historical data of the user account; Step S2-3: Read the historical login data of the device used by the current user, wherein the historical login data includes the historical login account and the account-related information corresponding to the historical login account; Step S2-4: Analyze the user's business handling intention according to the current user login data, including: S2-4-1: The user's current login location data is judged. If the user's current login location belongs to a business handling point recorded in the diversified business processing platform, it is considered that the current user's first business handling intention is a business within the business scope that can be handled by the business handling point at the current location; S2-4-2: Analyze the user's login account related information; extract the user account information record and classify it, and add category tags to the user account according to the information record when the user registered; combine the target user tags of each business preset in the platform database, and consider that the current user's first business handling intention is a business whose business target user tag in the diversified business processing platform matches the current account category tag; S2-4-3: Analyze the historical login data of the device used by the current user, extract the historical login account of the device used by the current user, if the number of historical login accounts of the device used by the current user is greater than or equal to the threshold k preset by the relevant staff, then the device is considered to be a relevant business processing device, and the data storage location of the device involving the platform data is restricted through the diversified business processing platform, and a data cleaning cycle is set. The device uses the temporary data of the diversified business processing platform for cleaning; If the number of historical login accounts of the device used by the current user is less than the threshold k preset by the relevant staff, obtain the relevant account information corresponding to the historical login account. When the account information mapping of the historical login account overlaps, it is considered that the user uses the current device to assist in business processing, and the current device is allowed to store platform data; Combined with the usage record of the historical login account of the current device, it is considered that the service whose frequency of services selected for handling in the historical login account of the current device exceeds the threshold value P is the first service handling intention of the current user; The frequency of any service u = the number of times service u was handled in the historical login account / the total number of times service was handled in the historical login account; The S3 includes: Step S3-1: Process the acquired service set, set each service in the service set W as a service node, set the access limit of each service node according to the real-time service access volume corresponding to each service, pre-connect each service node, and construct a service node relationship diagram; Step S3-2: Analyze the pre-connection of any two task nodes in the business node relationship diagram; extract the data items corresponding to each business node, and detect the data elements in the data items corresponding to each business node; suppose the data item corresponding to the jth business node contains the data element set {S j1 , S j2 , ..., S jg }, where S j1 , S j2 ,...,S jg They represent the 1st, 2nd, ..., gth data elements in the data item corresponding to the jth business. When the jth business node completes the business processing, the data element set {H j1 , H j2 , ..., H jG }; If there are overlapping data elements between the data obtained after passing through the jth business node and the data elements in the data items of any other business node, it is determined that there is a data connection relationship between the jth business node and any other business node, and the pre-connection between the two nodes in the business node relationship diagram is confirmed; According to the first service handling intention of the current user obtained by analyzing in S2, the connected services of the services included in the first service handling intention in the service node relationship diagram are obtained and set as the second service handling intention of the current user; Step S3-3: Analyze the hierarchical relationship between any two task nodes in the business node relationship graph; extract the connection relationship between each business node. If there are β business nodes that initiate a connection pointing to any business node R, it is considered that these β business nodes have a combination relationship, mark the business node combination, and set the business nodes in the same business node combination to the same level; set the business node pointed to by the business node combination to the upper level of the business node combination; According to the first business handling intention of the current user obtained by analyzing in S2, when the business included in the first business handling intention has an upper level in the business node relationship diagram, the upper level business of the business included in the first business handling intention is set as the second business handling intention of the current user, and other businesses in the same combination of the businesses included in the first business handling intention are set as the third business handling intention of the current user.

2. The method for intelligent management of diversified data based on big data according to claim 1, characterized in that: The S1 includes: Step S1-1: The service set in the obtained diversified service processing platform is recorded as W, wherein W includes {W1, W2, ..., W n }, where W1, W2, ..., W n denote the 1st, 2nd, ..., nth services in the diversified service processing platform respectively; let services W1, W2, ..., W n The corresponding business visits are Q W1 , Q W2 , ..., Q Wn ; Step S1-2: Set the i-th service W i The corresponding data item is denoted as S i , the S i Included i1 , S i2 , ..., S im }, where S i1 , S i2 ,...,S im They respectively represent the 1st, 2nd, ..., mth data elements in the data item corresponding to the i-th business.

3. The method for intelligent management of diversified data based on big data according to claim 1, characterized in that: The S4 includes: Step S4-1: Monitor the user's business handling behavior on the diversified business processing platform, obtain the current user's business selection, and obtain relevant data of the user in the current business handling process; assume that the user's current business handling is the current user's first business handling intention, and combine the business relationships obtained by the analysis in S3 to extract the second business handling intention or the third business handling intention corresponding to the user's current business handling; obtain the real-time access volume of each business in the current diversified business processing platform, and screen the business within the second business handling intention or the third business handling intention corresponding to the user's current business handling in combination with the access limit of each business. The specific steps include: Z1: By setting critical values, the business access volume classification standard is formulated, and the business access volume is divided into three levels: high, medium and low; Z2: Evaluate the services within the second service handling intention or the third service handling intention corresponding to the current service handled by the user according to the grading standard, determine the level of the real-time access volume of each service by comparing the real-time access volume with the preset critical value, and add a level mark to each service according to the grading result; Z3: According to the level identification of each service, when there is a high-visit service within the second service handling intention or the third service handling intention, reduce the recommendation weight of the high-visit service; If the number of visits to any service M in the second service handling intention or the third service handling intention reaches the critical value of the upper limit of the number of visits to the service M, the service M in the second service handling intention or the third service handling intention corresponding to the current service handled by the user will be removed and will not be recommended; Combined with the interface visualization rules of the diversified business processing platform, the screened second business handling intention or third business handling intention of the current user is added to the interface recommendation position of the current user; Step S4-2: extract the user's relevant data in the current business process, integrate the extracted user-related data in the current business according to the business connection relationship analyzed in S3, manage the transmission of user-related data in combination with the pointing relationship of each business, and encrypt and transmit the user-related data in the current business to the next business; Step S4-3: Record the login behavior and operation behavior of the current user on the diversified business processing platform, where the operation behavior includes the actual interaction between the user and the diversified business processing platform.

4. A diversified data intelligent management system based on big data, used to execute a diversified data intelligent management method based on big data as claimed in any one of claims 1 to 3, characterized in that: The system includes: a data acquisition module, a data analysis module, a data monitoring module and a data intelligent management module; The data collection module is used to collect relevant data in the diversified business processing platform; The data analysis module is used to analyze and mine relevant data collected from the diversified business processing platform; The data monitoring module is used to monitor user behavior and business status in the diversified business processing platform; The data intelligent management module is used to intelligently manage the relevant data of the diversified business processing platform based on the monitoring data of the data monitoring module in combination with the data analysis results of the data analysis module.

5. According to claim 4, a diversified data intelligent management system based on big data is characterized in that: The data acquisition module includes a platform business data acquisition unit, a user login data acquisition unit and a business-related data synchronization unit; The platform service data acquisition unit is used to identify and acquire available services in the current diversified service processing platform; The user login data acquisition unit is used to acquire user login data when a user logs into the diversified business processing platform in real time, including user account related information, user current login location data and user historical login data; The business-related data synchronization unit is used to obtain relevant data generated in real time by each business in the diversified business processing platform, and synchronously update the corresponding data in the cloud database according to the real-time data.

6. The diversified data intelligent management system based on big data according to claim 4 is characterized by: The data analysis module includes a user login data analysis unit, a user business handling intention analysis unit and a business relationship analysis unit; The user login data analysis unit is used to analyze the user login data and obtain the user's first service handling intention through user login data mining; The business relationship analysis unit is used to analyze the relationship between the businesses according to the data items included in each business in the diversified business processing platform; The user service handling intention analysis unit is used to analyze the user's next service handling intention based on the user's first service handling intention and according to the service relationship analysis result.

7. The diversified data intelligent management system based on big data according to claim 4 is characterized by: The data monitoring module includes a user login behavior monitoring unit, a user service handling behavior monitoring unit and a service access situation monitoring unit; The user login behavior monitoring unit is used to monitor the behavior of logging into the diversified business processing platform, and process and store the monitoring data; The user business handling behavior monitoring unit is used to monitor the user's business handling selection and business handling progress on the diversified business processing platform, and obtain the user's business handling behavior in real time; The service access situation monitoring unit is used to monitor the real-time access volume of each service in the diversified service processing platform and obtain the access situation of each service.

8. The diversified data intelligent management system based on big data according to claim 4 is characterized by: The data intelligent management module includes a data storage management unit, a data transmission management unit and a business intelligent recommendation unit; The data storage management unit is used to perform corresponding storage management on the current user's usage data of the diversified business processing platform according to the user login behavior analysis result; The data transmission management unit is used to manage the transmission of the user's uploaded data according to the user's business handling behavior combined with the user's business handling intention analysis result; The intelligent service recommendation unit is used to recommend services to the current user based on the analysis results of the user's service handling behavior and the user's service handling intention, combined with the service access situation.

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