Data reporting method, device, system and medium based on complex network

Abstract

The present disclosure provides a data reporting method based on a complex network, which belongs to the field of big data. The method includes: constructing a complex network for reporting data, wherein the nodes in the complex network include data tables and business fields involved in the data reporting process, and the association relationship between the nodes in the complex network includes the blood relationship between the data tables, and the attribution relationship between the data tables and the business fields; wherein each of the blood relationship exists between two data tables with a data processing relationship, and each of the attribution relationship exists between the data table covering the corresponding business field and the business field; and when reporting data, data is screened from the complex network based on the reporting subject of the data report. The present disclosure also provides a data reporting device, system and medium based on a complex network.

Description

Technical Field

[0001] The present disclosure belongs to the field of big data technology, and more specifically, relates to a data reporting method, device, system and medium based on a complex network. Background Art

[0002] With the continuous development of the digital age, the requirements for data supervision quality are also constantly increasing. For example, the horizontal scope of regulatory data has been greatly expanded, and the vertical granularity has been continuously refined. Different regulatory norms and systems may also overlap, and the content of supervision can cover almost all business scopes of the organization. Traditional reporting data integration mainly uses manual methods to screen and process data, which has the disadvantages of large workload, low efficiency, unclear relationship between data, and differences in statistical caliber. Summary of the invention

[0003] In view of this, the embodiments of the present disclosure provide a data reporting method, device, system and medium based on a complex network. Based on the knowledge and statistical characteristics of the complex network, it can provide logical relationships between the data involved in the data reporting process and between the data and the business domain, thereby improving the efficiency of data reporting.

[0004] One aspect of the embodiments of the present disclosure provides a data reporting method based on a complex network. The method includes: constructing a complex network for reporting data, wherein the nodes in the complex network include data tables and business fields involved in the data reporting process, and the association relationship between the nodes in the complex network includes the blood relationship between the data tables and the attribution relationship between the data tables and the business fields; wherein each of the blood relationship exists between two data tables with a data processing relationship, and each of the attribution relationship exists between a data table covering a corresponding business field and the business field; and when reporting data, data is screened from the complex network based on the reporting subject of the data reporting.

[0005] According to an embodiment of the present disclosure, the construction of a complex network for reporting data includes: treating each data table involved in the data reporting process as a node in the complex network; treating each business field involved in the data reporting process as a node in the complex network; establishing the blood relationship between two data tables with a data processing relationship through a processing field, wherein the processing field is a field based on which data is extracted during the data processing process; wherein each of the blood relationships contains at least one of the processed data; and establishing the attribution relationship between the two data tables with the blood relationship and the business field based on the business field covered by the processing field contained in the blood relationship.

[0006] According to an embodiment of the present disclosure, establishing the blood relationship between two data tables having a data processing relationship through processing fields also includes: determining the weight relationship between the two data tables having the blood relationship based on the number of processed fields and / or field attributes contained in the blood relationship.

[0007] According to an embodiment of the present disclosure, establishing the attribution relationship between the two data tables with the blood relationship and the business fields based on the business fields covered by the processing fields included in the blood relationship also includes: determining the weight relationship between the two data tables with the blood relationship and each business field based on the number of fields of each business field covered in the processing fields included in the blood relationship.

[0008] According to an embodiment of the present disclosure, the method further includes visually displaying a network topology diagram of the complex network. When reporting data, filtering data from the complex network based on the reporting subject of the data report includes: matching information of nodes in the complex network based on the reporting subject; and distinguishing and displaying the matched nodes in the network topology diagram to filter the data.

[0009] According to an embodiment of the present disclosure, the data tables involved in the data reporting process are classified into multi-level data according to the processing level, wherein the multi-level data includes two or more of detailed data, aggregated data, indicator data, or report data. The data tables in the aggregated data are obtained by preliminary processing the data tables in the detailed data. The data tables in the indicator data are obtained by processing the data tables in the aggregated data according to business demand indicators. The data tables in the report data are obtained by processing the data tables in the indicator data according to regulatory reporting requirements.

[0010] According to an embodiment of the present disclosure, in the network topology diagram, nodes representing data tables at different levels in the multi-level data are represented using different symbols and / or colors, and nodes representing business areas are represented using different symbols and / or colors from nodes representing data tables.

[0011] In another aspect of the disclosed embodiment, a data reporting device based on a complex network is provided. The device includes a complex network construction module and a data screening module. The complex network construction module is used to construct a complex network for reporting data. The nodes in the complex network include data tables and business fields involved in the data reporting process, and the association relationship between the nodes in the complex network includes the blood relationship between the data tables and the attribution relationship between the data tables and the business fields. Each of the blood relationship exists between two data tables with a data processing relationship, and each of the attribution relationship exists between a data table covering a corresponding business field and the business field. The data screening module is used to screen data from the complex network based on the reporting subject of the data report when reporting data.

[0012] According to an embodiment of the present disclosure, the complex network construction module includes a node setting submodule and a relationship establishment submodule. The node setting submodule is used to treat each data table involved in the data reporting process as a node in the complex network, and treat each business field involved in the data reporting process as a node in the complex network. The relationship establishment submodule is used to: establish the blood relationship between two data tables with a data processing relationship through a processing field, wherein the processing field is the field based on which data is extracted during the data processing process, wherein each of the blood relationships contains at least one of the processed data; and establish the attribution relationship between the two data tables with the blood relationship and the business field according to the business field covered by the processing field contained in the blood relationship.

[0013] According to an embodiment of the present disclosure, the device further includes a visualization module. The visualization module is used to visualize the network topology diagram of the complex network. The data screening module is used to match the information of the nodes in the complex network based on the reported subject, and to distinguish and display the matched nodes in the network topology diagram to screen the data.

[0014] Another aspect of the embodiment of the present disclosure provides a data reporting system based on a complex network. The data reporting system includes one or more memories and one or more processors. The memories store executable instructions. The processors execute the executable instructions to implement the above method.

[0015] Another aspect of an embodiment of the present disclosure provides a computer-readable storage medium storing computer-executable instructions, which are used to implement the method described above when executed.

[0016] Another aspect of an embodiment of the present disclosure provides a computer program, wherein the computer program includes computer executable instructions, and the instructions are used to implement the method described above when executed.

[0017] One or more of the above-mentioned embodiments have the following advantages or beneficial effects: they can at least partially overcome the defects of the prior art in that the processing efficiency is low when manually screening data, and the data type cannot be judged in a timely and accurate manner. Therefore, complex network theory can be used to realize automatic classification and screening of data and automatic integration of data from multiple sources, which effectively promotes the improvement of the efficiency and quality of regulatory reporting data. BRIEF DESCRIPTION OF THE DRAWINGS

[0018] The above and other objects, features and advantages of the present disclosure will become more apparent through the following description of the embodiments of the present disclosure with reference to the accompanying drawings, in which:

[0019] Figure 1 The system architecture of the complex network-based data reporting method and device according to an embodiment of the present disclosure is schematically shown;

[0020] Figure 2 A flowchart of a complex network-based data reporting method according to an embodiment of the present disclosure is schematically shown;

[0021] Figure 3 A simple complex network structure diagram is schematically shown;

[0022] Figure 4 A schematic diagram schematically shows a data reporting process of a bank;

[0023] Figure 5 A schematic diagram schematically shows the data processing levels in the data reporting process;

[0024] Figure 6 A data architecture diagram for reporting data according to an embodiment of the present disclosure is schematically shown;

[0025] Figure 7 A flowchart of a data reporting method based on a complex network according to another embodiment of the present disclosure is schematically shown;

[0026] Figure 8 A flowchart of a data reporting method based on a complex network according to another embodiment of the present disclosure is schematically shown;

[0027] Fig. 9 A block diagram schematically shows a complex network-based data reporting device according to an embodiment of the present disclosure; and

[0028] Fig.10A block diagram of a computer system suitable for implementing complex network-based data reporting according to an embodiment of the present disclosure is schematically shown. DETAILED DESCRIPTION

[0029] Hereinafter, embodiments of the present disclosure will be described with reference to the accompanying drawings. However, it should be understood that these descriptions are exemplary only and are not intended to limit the scope of the present disclosure. In the following detailed description, for ease of explanation, many specific details are set forth to provide a comprehensive understanding of the embodiments of the present disclosure. However, it is apparent that one or more embodiments may also be implemented without these specific details. In addition, in the following description, descriptions of known structures and technologies are omitted to avoid unnecessary confusion of the concepts of the present disclosure.

[0030] The various embodiments of the present disclosure aim to provide a data reporting method, device, system and medium based on a complex network, using complex network theory and model methods to analyze the connections between various layers of data in regulatory reporting and between data and the covered business areas.

[0031] The method according to an embodiment of the present disclosure may include first constructing a complex network for reporting data, and then filtering data from the complex network based on the reporting subject of the data when reporting data. The nodes in the complex network include data tables and business fields involved in the data reporting process, and the association relationship between the nodes in the complex network includes the blood relationship between the data tables and the attribution relationship between the data tables and the business fields. Each blood relationship exists between two data tables with a data processing relationship, and each attribution relationship exists between a data table covering a corresponding business field and the business field.

[0032] According to the embodiments of the present disclosure, it is possible to utilize complex network theoretical knowledge, as well as technologies such as basic models and statistical characteristics of network topology, to overcome the defects of the prior art of manually screening data, which has low processing efficiency and cannot timely and accurately determine the data type when faced with high-quality, high-demand massive reported data. Therefore, it is possible to achieve automatic classification and screening of data and automatic integration of data from multiple sources, which effectively promotes sufficient cross-validation of data, regular data quality monitoring, and improvement of the efficiency and quality of regulatory reporting data.

[0033] It should be noted that the complex network data reporting method, device, system and medium determined in the embodiments of the present disclosure can be used in the financial field, and can also be used in any field other than the financial field. The present disclosure does not limit the application field.

[0034] Figure 1 The system architecture 100 of the complex network-based data reporting method and device according to an embodiment of the present disclosure is schematically shown. It should be noted that: Figure 1What is shown is merely an example of a system architecture to which the embodiments of the present disclosure can be applied, in order to help those skilled in the art understand the technical content of the present disclosure, but it does not mean that the embodiments of the present disclosure cannot be used in other devices, systems, environments or scenarios.

[0035] like Figure 1 As shown, the system architecture 100 according to this embodiment may include a terminal device 101, a network 102 and a server 103. The network 102 is used to provide a communication link between the terminal device 101 and the server 103. The network 102 may include various connection types, such as wired, wireless communication links or optical fiber cables, etc.

[0036] The user can use the terminal device 101 to interact with the server 103 through the network 102 to receive or send messages, etc. Various communication client applications can be installed on the terminal device 101, such as bank management systems, government applications, monitoring applications, web browser applications, search applications, office applications, instant messaging tools, email clients, social platform software and other applications (only as examples).

[0037] The server 103 may be a server that provides various services. For example, the server 103 may construct a complex network for reporting data, using the data tables and business fields involved in the data reporting process of an organization as nodes, and the logical relationships between the data tables, and the logical relationships between the data tables and the business fields as edges, to construct the complex network, so that the data tables and business fields involved in the data reporting process can be associated with each other, breaking down data barriers. Furthermore, the server 103 may also perform data screening according to the reporting subject of the data report input by the user from the terminal device 101.

[0038] Research on complex network theory has been widely applied in various fields, and the scientific understanding of the quantitative and qualitative characteristics of complex networks has become an extremely important and challenging topic in scientific research in the network era. The network topology characteristics and models provided by this theory take different individuals in real life as nodes, connect two individuals with a certain connection into edges, and present them with weights based on the closeness of the relationship. Complex network research mainly focuses on the following three aspects: empirical research on a large number of real networks, analysis of the statistical characteristics of real networks, and construction of evolutionary models that conform to the statistical characteristics of real networks.

[0039] One definition of a complex network is: a network that has some or all of the properties of self-organization, self-similarity, attractor, small world, and scale-free. In short, a complex network is a network that is highly complex. Its main network models include: regular networks, random networks, small world networks, scale-free networks, self-similar networks, etc., and the network has the following statistical characteristics:

[0040] 1) Average path length L

[0041] The average path length of a network refers to the average distance between all pairs of nodes in the network. It indicates the degree of separation between nodes in the network and reflects the globality of the network.

[0042] 2) Clustering coefficient C

[0043] The clustering coefficient of a node refers to the ratio of the number of edges between all nodes adjacent to the node to the maximum possible number of edges between these adjacent nodes. The clustering coefficient of a network refers to the average value of the clustering coefficients of all nodes in the network, which reflects the local characteristics of the network. Assume that node i has k i adjacent nodes, and have E(i) edges with these adjacent nodes, then the clustering coefficient of node i can be obtained as:

[0044] C(i)=2E(i) / k i (k i -1)

[0045] 3) Degree Distribution

[0046] The degree of a node refers to the number of nodes adjacent to the node, that is, the number of edges connecting the node. <k>Refers to the average degree of all nodes in the network. The degree distribution P(k) refers to the probability that a randomly selected node in the network has a degree of exactly k.

[0047]

[0048] 4) Betweenness

[0049] It includes node betweenness and edge betweenness. Node betweenness refers to the proportion of all shortest paths in the network that pass through the node, while edge betweenness refers to the proportion of all shortest paths in the network that pass through the edge. Betweenness reflects the role and influence of the corresponding node or edge in the entire network. The node betweenness B(i) of node i is:

[0050]

[0051] The edge betweenness of node i is B(e ij )for:

[0052]

[0053] 5) Small World Effect

[0054] The small-world effect of complex networks means that although the scale of the network is large (the number of network nodes N is large), the distance between two nodes is much smaller than we imagine. In other words, the average path length L of the network grows logarithmically with the scale of the network, that is, L ~ In N. A large number of empirical studies have shown that almost all real networks have the small-world effect.

[0055] 6) Scale-free characteristics

[0056] For random networks and regular networks, the degree distribution interval is very narrow, and most nodes are concentrated around the node mean degree. <k>, indicating that the nodes are homogeneous, so <k>It is regarded as a characteristic scale of node degree. However, most networks in the real world are not random networks. Most nodes have very small degrees, while a few have very large degrees, indicating that the nodes are heterogeneous. This power-law distribution of node degrees is the scale-free characteristic of the network.

[0057] It should be noted that the data reporting method based on a complex network provided in the embodiment of the present disclosure can generally be executed by the server 103. Accordingly, the data reporting device, system and medium based on a complex network provided in the embodiment of the present disclosure can generally be arranged in the server 103. The data reporting method based on a complex network provided in the embodiment of the present disclosure can also be executed by a server or server cluster that is different from the server 103 and can communicate with the terminal device 101 and / or the server 103. Accordingly, the data reporting device, system and medium based on a complex network provided in the embodiment of the present disclosure can also be arranged in a server or server cluster that is different from the server 103 and can communicate with the terminal device 101 and / or the server 103.

[0058] It should be understood that Figure 1 The number of terminal devices, networks and servers in the embodiment is only for illustration. Any number of terminal devices, networks and servers may be provided according to implementation requirements.

[0059] Figure 2 The flowchart of the complex network-based data reporting method according to an embodiment of the present disclosure is schematically shown.

[0060] like Figure 2 As shown, the complex network-based data reporting method according to this embodiment may include operations S210 to S220.

[0061] First, in operation S210, a complex network for reporting data is constructed. The nodes in the complex network include data tables and business fields involved in the data reporting process, and the association relationship between the nodes in the complex network includes the blood relationship between the data tables and the attribution relationship between the data tables and the business fields. Each blood relationship exists between two data tables with a data processing relationship, and each attribution relationship exists between a data table covering a corresponding business field and the business field.

[0062] Figure 3 A simple complex network structure diagram is schematically shown. It should be noted that: Figure 3 It is only a schematic and figurative representation of the structure of a complex network to help those skilled in the art understand the present solution, but it is not the actual structure of the complex network for reporting data in the embodiment of the present disclosure and does not constitute any limitation to the present disclosure.

[0063] Combination Figure 3 , a complex network can use individuals with real physical meanings as nodes, connect two individuals with a certain specific connection into edges and display them with weights based on the closeness of the relationship.

[0064] Specifically in the data reporting scenario of the embodiment of the present disclosure, when constructing a complex network for reporting data, each data table involved in the data reporting process can be regarded as a node in the complex network, and each business field involved in the data reporting process can be regarded as a node in the complex network. Figure 3 A solid dot or solid hexagon in represents a node. In some embodiments, different types of data may be represented by different symbols or colors to distinguish nodes, for example, data tables and business domain data may be represented by different symbols, so that node type information may be visually displayed.

[0065] Then, a blood relationship is established between two data tables with a data processing relationship through the processing field. The processing field is the field based on which data is extracted during the data processing process, and each blood relationship contains at least one processed data. The data in an organization can include source data generated by the front line of business, and can also include data obtained by further processing (for example, data cleaning, format processing, statistical indicators, etc.) on the basis of the source data. The process of data processing is the process of extracting data from one or more data tables and then processing it into corresponding data in another data table. The field (or the extracted field) based on which data is extracted in this process is the above-mentioned processing field.

[0066] According to an embodiment of the present disclosure, a blood relationship can be used as an edge between two data tables. For example, assuming Figure 3 The solid dots in the middle represent the nodes corresponding to the data tables, and the edges between the solid dots reflect the blood relationship between the two data tables.

[0067] In addition, in some embodiments, the weight relationship between two data tables with a blood relationship can also be determined based on the number of processed fields and / or field attributes contained in the blood relationship. Field attributes may, for example, refer to information such as whether the processed field is the data primary key or key field of the data table from which the data is extracted. For example, the data of the aggregate data table A comes from the detail tables a and b, where, in the process of processing the aggregate data table A, 10 fields are taken from table a, including the primary key field; and 2 fields are taken from table b, but the primary key field is not included. Then in the complex network, the weight of the edge Aa is greater than the weight of Ab.

[0068] Furthermore, according to the embodiments of the present disclosure, an attribution relationship between two data tables with a blood relationship and a business field can be established according to the business field covered by the processing field included in the blood relationship. That is, in two data tables with a blood relationship, to which business field the processing field included in the blood relationship belongs, the two data tables can establish an attribution relationship with these business fields.

[0069] According to an embodiment of the present disclosure, the attribution relationship may be used as an edge between the two data tables and the corresponding business domains. Figure 3 The solid hexagon in the middle represents the business field, and the edges between the solid dots and the solid hexagon in the figure reflect the relationship between a data table and the business field.

[0070] In addition, according to the embodiments of the present disclosure, the weight relationship between two data tables with a blood relationship and each business field can be determined according to the number of fields in each business field covered by the processed fields included in the blood relationship. For example, if a complete description of a business field requires information of x fields, the weight of the data table and the business field can be established according to the number of fields in the processed fields in the blood relationship associated with a data table that belong to the business field.

[0071] Then in operation S220, when data is submitted, data is screened from the constructed complex network based on the reporting subject of the data submission. After the complex network is constructed, when the data table information associated with the reporting subject is matched from the complex network, the business fields involved in these data tables, as well as other data tables related thereto and their degree of association can be displayed through the association relationship in the complex network, which can save a lot of time and reduce human resource investment compared to manual data screening, and is more efficient and intelligent.

[0072] Figure 4 A schematic diagram schematically shows a data reporting process of a bank.

[0073] like Figure 4 As shown, taking banks as an example, the data scope in the data reporting process includes business scopes such as deposits, loans, accounting, credit cards, customer information, credit information, foreign exchange, bonds, etc., and the regulatory agencies that need to be reported include multiple domestic / foreign regulatory agencies (for example, regulatory agency 1, regulatory agency 12, ..., regulatory agency Y, etc.). Different regulatory agencies may need to report different reporting topics, reporting time intervals or cycles, and report formats each time. In the related art, independent construction of systems for different reporting topics will inevitably lead to differences in statistical calibers, lack of clear data connections, and difficulty in efficiently meeting the timeliness and accuracy of data reporting. The method of the disclosed embodiment can use complex network theory to analyze the correlation between the data involved in the reporting process, break down the barriers between data and business areas, and support the processing and analysis of massive data, which is more suitable for scenarios where the sources of regulatory reporting data are complex and involve a wide range of businesses.

[0074] Figure 5 The figure schematically shows the data processing levels in the data reporting process.

[0075] like Figure 5 As shown, according to an embodiment of the present disclosure, the data tables involved in the data reporting process are classified into multi-level data according to the processing level, wherein the multi-level data includes two or more of detailed data, aggregated data, indicator data, or report data.

[0076] Detailed data can be incorporated into upstream source data, including data directly transmitted from upstream or obtained from a data lake.

[0077] The data table in the aggregate data is obtained by preliminary processing of the data table in the detailed data, such as associating the data according to the business field to generate lightly summarized data that the business can understand. For example, all the detailed data in a certain business field within a certain time period are counted together to obtain an aggregate table. In the process of processing detailed data to aggregate data, the processing fields used are the fields for data screening in the detailed data.

[0078] The data tables in the indicator data are obtained by processing the data tables in the aggregate data according to the business demand indicators, and are used to support the flexible customization of business indicators. For example, the aggregate data can be processed into statistical indicators of the organization, subject, and product dimensions. The indicator data has business logic, and the indicators that business personnel can understand are various indicators with business meanings obtained by logically processing one or more aggregate tables according to business analysis requirements. In the process of processing the indicator data from the aggregate data, the processing fields include the fields for data filtering from one or more aggregate data tables. In the process of processing the indicator table, data can be taken from the aggregate data table according to these fields, and then substituted into the specified formula or algorithm to obtain the corresponding indicator data.

[0079] The data tables in the report data are obtained by processing the data tables in the indicator data according to the regulatory reporting requirements. For example, based on the indicator data, the business can be supported to generate report data by customization, so as to respond quickly to regulatory changes. For example, the corresponding format report data can be pre-set for different regulatory agencies. In the process of processing indicator data to report data, the processing fields are the condition fields when each report screens data from each indicator table.

[0080] The multi-level data in the embodiment of the present disclosure can establish blood relationships with each other based on processing fields, supporting upward and downward drilling of data.

[0081] Figure 6 A data architecture diagram for reporting data according to an embodiment of the present disclosure is schematically shown.

[0082] like Figure 6 As shown, according to the embodiments of the present disclosure, the data tables in each level of the multi-level data can be simulated as nodes in a complex network. For example, each detailed data table stored in the database can be simulated as a node; or each aggregate table obtained by aggregating the detailed data can be simulated as a node; or each indicator table obtained by deep processing of the aggregate table can be simulated as a node; or each report pre-set for different regulatory agencies can be regarded as a node.

[0083] At the same time, when constructing a complex network, the embodiments of the present disclosure will also simulate the business domain as a node. Figure 6 The information of the business fields shown is represented by labels or classification information of each business field. For example, the business fields of banking business may include corporate loans, personal loans, corporate customers, bonds, bill business, entrusted loans, etc. The classification information or business label of each business field may be simulated as a node.

[0084] In this way, based on Figure 6 The complex network built by the data architecture can break down the barriers between data and business domains, and give business meanings to technical proprietary names such as detailed data, aggregated data, indicator data, and / or report data, making them clear and understandable.

[0085] Figure 7 The flowchart of a data reporting method based on a complex network according to another embodiment of the present disclosure is schematically shown.

[0086] like Figure 7 As shown, the complex network-based data reporting method according to this embodiment may include operation S210, operation S710, and operations S721 to S722. Operation S721 to S722 are a specific embodiment of operation S220.

[0087] First, in operation S210, a complex network for reporting data is constructed, wherein the nodes in the complex network include data tables and business fields involved in the data reporting process, and the association relationship between the nodes in the complex network includes the blood relationship between the data tables, and the attribution relationship between the data tables and the business fields. The specific introduction of operation S210 is referred to the above content, and will not be repeated here.

[0088] Then, in operation S710, a network topology diagram of the complex network is visualized and displayed. A complex network visualization tool (eg, Pajek tool, Gephi software, etc.) is used to simulate the network topology diagram.

[0089] Next, in operation S721, when data is reported, information of nodes in the complex network is matched based on the reported subject.

[0090] And in operation S722, the matched nodes are displayed distinctively (for example, highlighted) in the network topology diagram to perform data screening.

[0091] According to the embodiments of the present disclosure, a visual and interactive network topology diagram can be formed, which can reflect the relationship between the data involved in the reporting process. The complex network formed in this way can show the relationship between the data tables, which is convenient for tracing the required data tables when reporting data.

[0092] In one embodiment, in the network topology diagram, nodes representing data tables of different levels in the multi-level data can be represented by different symbols and / or colors, and nodes representing business areas can be represented by symbols and / or colors different from those representing data tables. Therefore, when data is screened in operation S722, the level to which the data to be screened belongs can be quickly determined based on the symbols and / or colors of the matched nodes, and the business area of ​​the data to be screened can be quickly located, which greatly guides the business personnel who process the reported data to find data and improves the efficiency of data reporting.

[0093] Figure 8 The flowchart of a complex network-based data reporting method according to another embodiment of the present disclosure is schematically shown.

[0094] like Figure 8 As shown, the data reporting method may include steps S801 to S804.

[0095] Step S801: Network node selection. For example, Figure 6 The data architecture shown simulates the various parameters (detailed data, aggregated data, indicator data, report data and the business areas covered) into nodes in a complex network.

[0096] Step S802: Establish the association relationship of each node. The detailed data, aggregated data, indicator data, and report data are established in a blood relationship through the processing fields. These processing fields belong to different business areas (such as personal loans, legal loans, credit cards, etc.). Therefore, based on the processing fields, the attribution relationship between each layer of data and the business area can also be created.

[0097] Step S803: Calculate the weight relationship between nodes. Take the nodes in step S801 and the association relationships (including blood relationship and belonging relationship) in step S802 as edges, refer to various typical models of complex networks, substitute the statistical characteristic parameters of the network, and calculate the weight relationship between each node based on the number, meaning and field attributes of the processed fields in each blood relationship.

[0098] Step S804: Simulate the network model of the submitted data. According to the weight relationship in step S803, use complex network visualization tools such as Pajek and Gephi to simulate the network topology diagram. Select different nodes to display which processing fields and their weights are specifically associated between each node. Thus, the network topology diagram of the complex network formed can intuitively display the connection between different data and between data and business fields, and the associated relationship is displayed by weight, which is convenient for distinguishing the closeness of the connection and laying the foundation for further screening and analysis of data.

[0099] When data needs to be submitted, you can first check whether there is report data that meets the conditions and can be directly submitted according to the reporting subject. If there is, you can use it directly. If not, you can check whether the format of existing report data can be reused. If so, you can filter indicator data based on the existing report data according to the report conditions, and you can drill or trace layer by layer.

[0100] Complex network theory and models support the processing and analysis of massive data, and have a higher prediction accuracy than other models. They are more suitable for the complex sources of regulatory reporting data and a wide range of business involved. As the amount of sample data increases, the accuracy of data screening can be further improved.

[0101] Fig. 9 A block diagram of a complex network-based data reporting device 900 according to an embodiment of the present disclosure is schematically shown.

[0102] like Fig. 9 As shown, the complex network-based data reporting device 900 according to an embodiment of the present disclosure may include a complex network construction module 910 and a data screening module 920. According to other embodiments of the present disclosure, the device 900 may further include a visualization module 930. The device 900 may be used to implement reference Figure 2 to Figure 8 The method according to the embodiment of the present disclosure is described.

[0103] The complex network construction module 910 can, for example, perform operation S210 to construct a complex network for reporting data. The nodes in the complex network include data tables and business fields involved in the data reporting process, and the association relationship between the nodes in the complex network includes the blood relationship between the data tables and the attribution relationship between the data tables and the business fields. Each blood relationship exists between two data tables with a data processing relationship, and each attribution relationship exists between a data table covering a corresponding business field and the business field.

[0104] The data screening module 920 may, for example, perform operation S220 to screen data from a complex network based on a reporting subject of the data reporting when reporting data.

[0105] The visualization module 930 can, for example, perform operation S710 to visualize the network topology diagram of the complex network. Accordingly, the data screening module 920 is used to match the information of nodes in the complex network based on the reported subject, and to distinguish and display the matched nodes in the network topology diagram to screen the data.

[0106] According to some embodiments of the present disclosure, the complex network construction module 910 may further include a node setting submodule 911 and a relationship establishment submodule 912 .

[0107] The node setting submodule 911 is used to treat each data table involved in the data reporting process as a node in the complex network, and treat each business field involved in the data reporting process as a node in the complex network.

[0108] The relationship establishment submodule 912 is used to: establish a blood relationship between two data tables with a data processing relationship through a processing field, wherein the processing field is a field based on which data is extracted during the data processing process, and each blood relationship contains at least one processed data; and establish an affiliation relationship between two data tables with a blood relationship and a business field based on the business field covered by the processing field contained in the blood relationship.

[0109] Furthermore, the relationship establishment submodule 912 is also used to determine the weight relationship between the two data tables with a blood relationship based on the number of processed fields and / or field attributes included in the blood relationship. Optionally, the relationship establishment submodule 912 is also used to determine the weight relationship between the two data tables with a blood relationship and each business field based on the number of fields in the processed fields included in the blood relationship that cover each business field.

[0110] According to the complex network-based data reporting device 900 of the embodiment of the present disclosure, the organization's reporting data architecture system can be upgraded to optimize the relationship between regulatory data and business areas. On the basis of ensuring the rapid supply of regulatory data, it can more effectively ensure that the data is reliable, accurate and complete, which is conducive to improving the quality of data regulatory reporting.

[0111] According to the embodiments of the present invention, any one or more of the modules, submodules, units, and subunits, or at least part of the functions of any one of them can be implemented in one module. According to the embodiments of the present invention, any one or more of the modules, submodules, units, and subunits can be split into multiple modules for implementation. According to the embodiments of the present invention, any one or more of the modules, submodules, units, and subunits can be at least partially implemented as hardware circuits, such as field programmable gate arrays (FPGAs), programmable logic arrays (PLAs), systems on chips, systems on substrates, systems on packages, application specific integrated circuits (ASICs), or can be implemented by hardware or firmware in any other reasonable way of integrating or packaging the circuit, or implemented in any one of the three implementation methods of software, hardware, and firmware, or in any appropriate combination of any of them. Alternatively, according to the embodiments of the present invention, one or more of the modules, submodules, units, and subunits can be at least partially implemented as computer program modules, and when the computer program modules are run, the corresponding functions can be performed.

[0112] For example, any of the complex network construction module 910, the data screening module 920, and the visualization module 930 can be combined in one module, or any of the modules can be split into multiple modules. Alternatively, at least part of the functions of one or more of these modules can be combined with at least part of the functions of other modules and implemented in one module. According to an embodiment of the present disclosure, at least one of the complex network construction module 910, the data screening module 920, and the visualization module 930 can be at least partially implemented as a hardware circuit, such as a field programmable gate array (FPGA), a programmable logic array (PLA), a system on a chip, a system on a substrate, a system on a package, an application-specific integrated circuit (ASIC), or can be implemented by hardware or firmware such as any other reasonable way of integrating or packaging the circuit, or implemented in any one of the three implementation methods of software, hardware and firmware or in an appropriate combination of any of them. Alternatively, at least one of the complex network construction module 910, the data screening module 920, and the visualization module 930 can be at least partially implemented as a computer program module, and when the computer program module is run, the corresponding function can be performed.

[0113] Fig.10 A block diagram of a computer system 1000 suitable for implementing complex network-based data reporting according to an embodiment of the present disclosure is schematically shown. Fig.10 The computer system 1000 shown is only an example and should not bring any limitation to the functions and scope of use of the embodiments of the present disclosure.

[0114] like Fig.10 As shown, the computer system 1000 according to the embodiment of the present disclosure includes a processor 1001, which can perform various appropriate actions and processes according to the program stored in the read-only memory (ROM) 1002 or the program loaded from the storage part 1008 to the random access memory (RAM) 1003. The processor 1001 may include, for example, a general-purpose microprocessor (such as a CPU), an instruction set processor and / or a related chipset and / or a special-purpose microprocessor (for example, an application-specific integrated circuit (ASIC)), etc. The processor 1001 may also include an onboard memory for caching purposes. The processor 1001 may include a single processing unit or multiple processing units for performing different actions of the method flow according to the embodiment of the present disclosure.

[0115] In RAM 1003, various programs and data required for the operation of computer system 1000 are stored. Processor 1001, ROM 1002 and RAM 1003 are connected to each other via bus 1004. Processor 1001 performs various operations of the method flow according to the embodiment of the present disclosure by executing the program in ROM 1002 and / or RAM 1003. It should be noted that the program can also be stored in one or more memories other than ROM 1002 and RAM 1003. Processor 1001 can also perform various operations of the method flow according to the embodiment of the present disclosure by executing the program stored in the one or more memories.

[0116] According to an embodiment of the present disclosure, the computer system 1000 may further include an input / output (I / O) interface 1005, which is also connected to the bus 1004. The computer system 1000 may further include one or more of the following components connected to the I / O interface 1005: an input section 1006 including a keyboard, a mouse, etc.; an output section 1007 including a cathode ray tube (CRT), a liquid crystal display (LCD), etc., and a speaker, etc.; a storage section 1008 including a hard disk, etc.; and a communication section 1009 including a network interface card such as a LAN card, a modem, etc. The communication section 1009 performs communication processing via a network such as the Internet. A drive 1010 is also connected to the I / O interface 1005 as needed. A removable medium 1011, such as a magnetic disk, an optical disk, a magneto-optical disk, a semiconductor memory, etc., is installed on the drive 1010 as needed, so that a computer program read therefrom is installed into the storage section 1008 as needed.

[0117] According to an embodiment of the present disclosure, the method flow according to an embodiment of the present disclosure can be implemented as a computer software program. For example, an embodiment of the present disclosure includes a computer program product, which includes a computer program carried on a computer-readable storage medium, and the computer program contains a program code for executing the method shown in the flowchart. In such an embodiment, the computer program can be downloaded and installed from the network through the communication part 1009, and / or installed from the removable medium 1011. When the computer program is executed by the processor 1001, the above-mentioned functions defined in the system of the embodiment of the present disclosure are executed. According to an embodiment of the present disclosure, the system, equipment, device, module, unit, etc. described above can be implemented by a computer program module.

[0118] The present disclosure also provides a computer-readable storage medium, which may be included in the device / apparatus / system described in the above embodiments; or may exist independently without being assembled into the device / apparatus / system. The above computer-readable storage medium carries one or more programs, and when the above one or more programs are executed, the method according to the embodiment of the present disclosure is implemented.

[0119] According to an embodiment of the present disclosure, a computer-readable storage medium may be a non-volatile computer-readable storage medium, for example, may include but is not limited to: a portable computer disk, a hard disk, a random access memory (RAM), a read-only memory (ROM), an erasable programmable read-only memory (EPROM or flash memory), a portable compact disk read-only memory (CD-ROM), an optical storage device, a magnetic storage device, or any suitable combination thereof. In the present disclosure, a computer-readable storage medium may be any tangible medium containing or storing a program, which may be used by or in combination with an instruction execution system, an apparatus or a device. For example, according to an embodiment of the present disclosure, a computer-readable storage medium may include the ROM 1002 and / or RAM 1003 described above and / or one or more memories other than ROM 1002 and RAM 1003.

[0120] The embodiments of the present disclosure also include a computer program product, which includes a computer program, and the computer program contains program code for executing the method provided by the embodiments of the present disclosure. When the computer program product runs on an electronic device, the program code is used to enable the electronic device to implement the method provided by the embodiments of the present disclosure.

[0121] When the computer program is executed by the processor 1001, the above functions defined in the system / device of the embodiment of the present disclosure are executed. According to the embodiment of the present disclosure, the system, device, module, unit, etc. described above can be implemented by a computer program module.

[0122] In one embodiment, the computer program may rely on tangible storage media such as optical storage devices, magnetic storage devices, etc. In another embodiment, the computer program may also be transmitted and distributed in the form of signals on a network medium, and downloaded and installed through the communication part 1009, and / or installed from the removable medium 1011. The program code contained in the computer program may be transmitted using any appropriate network medium, including but not limited to: wireless, wired, etc., or any suitable combination of the above.

[0123] According to an embodiment of the present disclosure, the program code for executing the computer program provided by the embodiment of the present disclosure can be written in any combination of one or more programming languages. Specifically, these computing programs can be implemented using high-level process and / or object-oriented programming languages, and / or assembly / machine languages. Programming languages ​​include, but are not limited to, Java, C++, python, "C" language or similar programming languages. The program code can be executed entirely on the user computing device, partially on the user device, partially on the remote computing device, or entirely on the remote computing device or server. In the case of a remote computing device, the remote computing device can be connected to the user computing device through any type of network, including a local area network (LAN) or a wide area network (WAN), or can be connected to an external computing device (e.g., using an Internet service provider to connect through the Internet).

[0124] The flow charts and block diagrams in the accompanying drawings illustrate the possible architecture, functions and operations of the systems, methods and computer program products according to various embodiments of the present disclosure. In this regard, each box in the flow chart or block diagram can represent a module, a program segment, or a part of a code, and the above-mentioned module, program segment, or a part of a code contains one or more executable instructions for realizing the specified logical function. It should also be noted that in some alternative implementations, the functions marked in the box can also occur in a different order from the order marked in the accompanying drawings. For example, two boxes represented in succession can actually be executed substantially in parallel, and they can sometimes be executed in the opposite order, depending on the functions involved. It should also be noted that each box in the block diagram or flow chart, and the combination of the boxes in the block diagram or flow chart can be implemented with a dedicated hardware-based system that performs a specified function or operation, or can be implemented with a combination of dedicated hardware and computer instructions.

[0125] The embodiments of the present disclosure are described above. However, these embodiments are only for illustrative purposes and are not intended to limit the scope of the present disclosure. Without departing from the scope of the present disclosure, those skilled in the art may make various substitutions and modifications, which should all fall within the scope of the present disclosure.< / k> < / k> < / k>

Claims

1. A data reporting method based on a complex network, comprising: Constructing a complex network for reporting data, wherein the nodes in the complex network include data tables and business fields involved in the data reporting process, and the association relationships between the nodes in the complex network include blood relationships between data tables and attribution relationships between data tables and business fields; wherein each of the blood relationships exists between two data tables having a data processing relationship, and each of the attribution relationships exists between a data table covering a corresponding business field and the business field; and When submitting data, data is screened from the complex network based on the reporting subject of the data report, including: matching the information of the data table associated with the reporting subject from the complex network; and displaying the business field involved in the matched data table, and other data tables related thereto and their degree of association through the blood relationship and the belonging relationship in the complex network; Wherein, the construction of a complex network for reporting data also includes: The blood relationship is established between two data tables having a data processing relationship through a processing field; wherein the processing field is a field based on which data is extracted during data processing; wherein each of the blood relationships contains at least one processing field; Determine a weight relationship between two data tables having the blood relationship based on the number of the processed fields and / or field attributes contained in each of the blood relationships; According to the business field to which the processing fields included in each of the blood relations belong, establishing the attribution relationship between the two data tables having the blood relation and the business field; and According to the number of fields belonging to each business field in the processed fields included in each of the blood relations, the weight relationship between the two data tables having the blood relation and each business field is determined.

2. The method according to claim 1, wherein: The complex network constructed for reporting data includes: Each data table involved in the data reporting process is regarded as a node in the complex network; Each business area involved in the data reporting process is regarded as a node in the complex network.

3. The method according to claim 1, wherein: The method further comprises: visually displaying a network topology diagram of the complex network; When submitting data, screening data from the complex network based on the reporting subject of the data submission includes: Matching information of nodes in the complex network based on the reporting topic; and In the network topology diagram, the matched nodes are displayed distinctively to perform data screening.

4. The method according to any one of claims 1 to 3, wherein: The data tables involved in the data reporting process are classified into multi-level data according to the processing level, wherein the multi-level data includes two or more of detailed data, aggregated data, indicator data, or report data; in, The data table in the aggregated data is obtained by preliminary processing of the data table in the detailed data; The data table in the indicator data is obtained by processing the data table in the aggregate data according to the business demand indicator; and The data tables in the report data are obtained by processing the data tables in the indicator data in accordance with regulatory reporting requirements.

5. The method according to claim 4, wherein: In the network topology diagram: Nodes representing data tables at different levels in the multi-level data are represented by different symbols and / or colors; as well as Nodes representing business areas are represented using different symbols and / or colors than nodes representing data tables.

6. A data reporting device based on a complex network, comprising: A complex network construction module, used to construct a complex network for reporting data, wherein the nodes in the complex network include data tables and business fields involved in the data reporting process, and the association relationship between the nodes in the complex network includes the blood relationship between the data tables and the attribution relationship between the data tables and the business fields; wherein each of the blood relationship exists between two data tables with a data processing relationship, and each of the attribution relationship exists between a data table covering a corresponding business field and the business field; and A data screening module, used for screening data from the complex network based on the reporting subject of the data report when submitting data, including: matching the information of the data table associated with the reporting subject from the complex network; and displaying the business field involved in the matched data table, and other data tables related thereto and their degree of association through the blood relationship and the belonging relationship in the complex network; The complex network construction module further includes a relationship establishment submodule, and the relationship establishment submodule is further used for: The blood relationship is established between two data tables with a data processing relationship through processing fields, and based on the number and / or field attributes of the processing fields contained in each of the blood relationship, a weight relationship between the two data tables with the blood relationship is determined; wherein the processing field is a field based on which data is extracted during data processing; wherein each of the blood relationship contains at least one processing field; and According to the business field to which the processed fields contained in each of the blood relationships belong, the attribution relationship between the two data tables with the blood relationship and the business field is established; and according to the number of fields belonging to each business field in the processed fields contained in each of the blood relationships, the weight relationship between the two data tables with the blood relationship and each business field is determined.

7. A data reporting system based on a complex network, comprising: One or more memories storing executable instructions; as well as One or more processors execute the executable instructions to implement the method according to any one of claims 1 to 5.

8. A computer-readable storage medium having executable instructions stored thereon, which, when executed by a processor, causes the processor to execute the method according to any one of claims 1 to 5.

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