CN114398864A

CN114398864A - Report display method, device, equipment and storage medium

Info

Publication number: CN114398864A
Application number: CN202210037519.1A
Authority: CN
Inventors: 刘新磊
Original assignee: Ping An Puhui Enterprise Management Co Ltd
Current assignee: Ping An Puhui Enterprise Management Co Ltd
Priority date: 2022-01-13
Filing date: 2022-01-13
Publication date: 2022-04-26

Abstract

The embodiment of the application provides a report display method, a report display device, report display equipment and a storage medium. Relates to the technical field of artificial intelligence, and the method comprises the following steps: determining at least one target index from all indexes included in the report according to the target role, and determining a logical parent-child relationship between all target indexes based on a business association relationship between indexes in a business knowledge graph to obtain a target index logical tree; and sequentially acquiring node index data and node index attributes corresponding to each node of the target index logic tree based on a depth-first traversal algorithm, and displaying each node index data according to the node index attribute corresponding to each node. The display rate of the report can be improved. The present application may relate to a blockchain technique, such as node pointer data and node pointer attributes corresponding to each node may be written into a blockchain. The application also relates to the technical field of digital medical treatment, for example, the node index data comprises data in the technical field of digital medical treatment.

Description

Report display method, device, equipment and storage medium

Technical Field

The present application relates to the field of data processing technologies, and in particular, to a method, an apparatus, a device, and a storage medium for displaying a report.

Background

Currently, many enterprises adopt a reporting software system to perform inductive analysis on enterprise business data to generate a data report for enterprise decision or reference, for example, a Cognos reporting software system is used to generate a Cognos report, and the Cognos report is displayed to a client in a webpage report form. However, as the enterprises expand, the number of index items in the data report increases, and the association relationship between the index items is complex and unclear.

Disclosure of Invention

The embodiment of the application provides a report display method, a report display device, a report display equipment and a report display storage medium, wherein a target index logic tree is quickly constructed through a business knowledge graph, the target index logic tree can indicate the incidence relation among all target indexes, and the report display speed can be improved.

In a first aspect, an embodiment of the present application provides a report display method, where the report display method includes:

acquiring each index included in the report;

determining at least one target index from each index according to the target role, and determining a parent-child relationship between each target index based on a service incidence relationship between indexes in a service knowledge graph to obtain a target index logic tree; the nodes in the target index logic tree correspond to each target index one by one;

and sequentially acquiring node index data and node index attributes corresponding to each node of the target index logic tree based on a depth-first traversal algorithm, and displaying each node index data according to the node index attribute corresponding to each node.

In a second aspect, an embodiment of the present application provides a report display apparatus, including:

the acquisition unit is used for acquiring each index included in the report;

the determining unit is used for determining at least one target index from all the indexes according to the target role, determining the parent-child relationship among all the target indexes based on the service incidence relationship among the indexes in the service knowledge graph, and obtaining a target index logic tree; the nodes in the target index logic tree correspond to each target index one by one;

and the display unit is used for sequentially acquiring node index data and node index attributes corresponding to each node of the target index logic tree based on a depth-first traversal algorithm and displaying each node index data according to the node index attributes corresponding to each node.

In a third aspect, an embodiment of the present application provides a report display device, where the report display device includes an input interface and an output interface, and the report display device further includes:

a processor adapted to implement one or more instructions; and the number of the first and second groups,

a computer storage medium having stored thereon one or more instructions adapted to be loaded by a processor and to perform the method of the first aspect.

In a fourth aspect, the present application further provides a computer-readable storage medium, which stores computer program instructions, and when the computer program instructions are executed by a processor, the computer program instructions are configured to perform the method of the first aspect.

In the embodiment of the application, the report display device can determine at least one target index from all indexes included in the report according to the target role, can display different indexes aiming at different roles, displays the indexes in a targeted manner, and can meet the requirement that different roles view different visual data. And moreover, a tree structure is introduced, a target index logic tree is constructed based on the logic relation among target indexes, and nodes in the target index logic tree correspond to the target indexes one to one. The incidence relation among the target indexes is described by using a target index logic tree, the incidence relation among the target indexes is clearer, and the display rate of the report can be improved through the target index logic tree. In addition, the target index logic tree can be constructed based on the knowledge graph, and the construction speed of the target index logic tree can be improved.

Drawings

In order to more clearly illustrate the embodiments of the present application or the technical solutions in the prior art, the drawings used in the description of the embodiments or the prior art will be briefly described below, it is obvious that the drawings in the following description are only some embodiments of the present application, and for those skilled in the art, other drawings can be obtained according to the drawings without creative efforts.

Fig. 1 is a schematic diagram of an architecture of a report display system according to an embodiment of the present application;

fig. 2 is a schematic flowchart of a report displaying method according to an embodiment of the present application;

FIG. 3 is a schematic diagram of a business knowledge graph structure provided by an embodiment of the present application;

FIG. 4 is a schematic structural diagram of a pointer logic tree provided in an embodiment of the present application;

FIG. 5 is a flowchart illustrating another report displaying method according to an embodiment of the present disclosure;

fig. 6 is a schematic structural diagram of a report display apparatus according to an embodiment of the present application;

fig. 7 is a schematic structural diagram of a report display device according to an embodiment of the present application.

Detailed Description

The technical solutions in the embodiments of the present application will be clearly and completely described below with reference to the drawings in the embodiments of the present application, and it is obvious that the described embodiments are only a part of the embodiments of the present application, and not all of the embodiments. All other embodiments, which can be derived by a person skilled in the art from the embodiments given herein without making any creative effort, shall fall within the protection scope of the present application.

With the continuous improvement of the social informatization degree, the report tool is an essential informatization tool in the production, operation, investment and management processes of various enterprises. Currently, many enterprises employ reporting software systems to perform inductive analysis on enterprise business data to generate data reports for enterprise decision-making or reference. However, as business of enterprises increases, the index items in the report are increasing. Because the index items in the report are too many, the incidence relation among all indexes in the report is not clear, and the rate of displaying the report is low.

Based on this, the embodiment of the present application provides a report display scheme, and the principle of the scheme is as follows: responding to a triggering operation of report display, acquiring each index included by the report, determining at least one target index from each index according to a target role, determining a parent-child relationship between each target index based on a service incidence relationship between indexes in a service knowledge graph, obtaining a target index logic tree, wherein nodes in the target index logic tree correspond to each target index one by one, sequentially acquiring node index data and node index attributes corresponding to each node of the target index logic tree based on a depth-first traversal algorithm, and displaying each node index data according to the node index attributes corresponding to each node. The index logic tree can be quickly constructed based on the service knowledge graph, the target index logic tree indicates the incidence relation between target indexes, and the display rate of the report can be improved.

The report display scheme mentioned in the embodiment of the present application may be applied to a report display system as shown in fig. 1, and as shown in fig. 1, the report display system may at least include a report display device 11 and a data storage device 12. The report display scheme may be applied to the report display device 11, as shown in fig. 1, the report display device 11 may be a terminal device, and the terminal device may include but is not limited to: smart phones, tablets, laptops, wearable devices, desktop computers, and the like. The data storage device 12 may be any device having a data storage function, for example, the data storage device 12 is a server or the like. The server may be an independent physical server, a server cluster or a distributed system formed by a plurality of physical servers, a cloud server providing basic cloud computing services such as cloud service, a cloud database, cloud computing, a cloud function, cloud storage, Network service, cloud communication, a Content Delivery Network (CDN), middleware service, domain name service, security service, big data and an artificial intelligence platform, and the like. The embodiment of the present application does not limit this.

Based on the above description, the report display method according to the embodiment of the present application is explained in detail below. Referring to fig. 2, fig. 2 illustrates a report display method. As shown in fig. 2, the report display method includes S201 to S203:

s201: and acquiring each index included in the report.

The report form can comprise one or more indexes, and each index corresponds to index data. The service condition can be indicated through the index data corresponding to each index included in the report. For example, in a performance assessment business scenario, the report is a performance report, which may include performance indicators (e.g., one or more of over-budget credit, production efficiency, predicted deviation rate, cost optimization), and may indicate business conditions of the performance assessment business via indicator data corresponding to the performance indicators. For another example, in the scenario of the fee counting service, the report is a fee counting report, and the fee counting report may include a fee index, and the service condition of the fee counting service may be indicated by index data corresponding to the fee index. The report forms can have different types and can have different styles. For example, the report may be a line graph report, a table report, a histogram report, or any combination thereof.

S202: determining at least one target index from each index according to the target role, and determining a parent-child relationship between each target index based on a service incidence relationship between indexes in a service knowledge graph to obtain a target index logic tree; the nodes in the target index logic tree correspond to each target index one to one.

Wherein, the index logic tree can be used for reflecting the incidence relation between indexes. The metric logic tree may include, but is not limited to, the following elements: nodes, parent-child relationships between nodes, and hierarchy of the index logical tree. Wherein, the node is a component element in the index logic tree. Wherein, the parent-child relationship between the nodes is the dependency relationship between the nodes at the upper and lower layers in the index logic tree. The hierarchy of the metric logical tree means that each node is located at the hierarchy of the metric logical tree.

Wherein each node has corresponding node metric data and node metric attributes. The node index data may be any form of data, and may include but is not limited to: value type data (e.g., percentage type, value type, bit type, etc.), text type data, image type data (e.g., picture type, short video type, chart type, etc.). The node index data may be data in any business field, for example, data in a financial field (such as car insurance data), and for example, data in a digital medical technology field (such as personal health record, prescription, examination report, etc.).

The node index attribute is used for describing a display mode of index data. The node metric attributes may include, but are not limited to: font, color, size, absolute positional relationship, and relative positional relationship between node index data. Optionally, the relative position relationship between the node index data may be obtained by: and configuring alignment attributes between the node index data, and determining the relative position relationship between the node index data based on the alignment attributes. In one embodiment, the alignment property between node pointer data may be implemented by a flexible layout (FlexibleBoxflex) method. Wherein the alignment attribute comprises: the node index data alignment method comprises the following steps of flex-direction, flex-wrap, flex-flow, just-content, align-items and align-content, wherein the flex-direction attribute determines the direction of a main shaft (namely the arrangement direction of the node index data), the flex-wrap attribute is used for defining how to exchange lines under the condition that the node index data is not arranged on one axis (also called the axis), the flex-flow attribute is the shorthand form of the flex-direction attribute and the flex-wrap attribute, the just-content attribute defines the alignment mode of the node index data on the main shaft, the align-items attribute defines how to align the node index data on the cross shaft, and the align-content attribute defines the alignment mode of a plurality of axes.

In an embodiment, target role information is required to be acquired through target user login information of a target user, the target role information includes at least one target role, so that a target index is determined from indexes included in a report according to the target role, and a target index logic tree corresponding to the target role can be built based on the target index. Different index logic trees can be set for different roles, corresponding visual data can be displayed according to the index logic trees, the visual data can be displayed in a targeted mode, and the requirement that different visual data can be viewed by different roles is met.

Specifically, target user login information can be acquired, the target user login information is verified, and if the target user login information is verified, target role information is determined based on the target user login information.

Optionally, the report display system may display a login page, obtain login information of the target user in response to an input operation of the target user on the login page, verify the login information of the target user, obtain the user role association table if the login information of the target user passes the verification, and search target role information corresponding to the login information of the target user from the user role association table. The user role association table is used for indicating the corresponding relation between the user login information and the role information.

The user login information may include user identification information and a combined password, where the combined password includes a user login password and a user authentication password. The step of checking the user login information comprises the following steps: and verifying the user login password in the combined password according to the preset login password corresponding to the user identification information, verifying the user authentication password in the combined password according to the preset authentication password corresponding to the user identification information, and determining that the user login information is verified if the user login password and the user authentication password are both verified. And if the user login password and/or the user authentication password are not verified, determining that the user login information verification fails, and outputting prompt information. Meanwhile, the user login password and the user authentication password in the combined password are verified, so that the safety can be improved. The user identification information may uniquely identify the user, for example, the user identification information may include, but is not limited to, a mobile phone number of the user, an identification number of the user, a mailbox address of the user, or a user ID.

Wherein the role information may include at least one role, which may include, but is not limited to, headquarter financial officer, department leader, general user, and the like. For example, the role information may be used to indicate a role of headquarter financial officer. As another example, role information may be used to indicate that the headquarters financial officer and department are in charge of both roles.

In one embodiment, the correspondence between the user login information and the role information may be described by using a key value pair. Specifically, the user login information may be used as a key of a key-value pair, and the role information may be used as a value of the key-value pair, so that when the target user login information passes the verification, the target role information corresponding to the target user login information may be obtained based on the key-value pair.

In one embodiment, for a target role included in the target role information, a target index may be determined according to target historical behavior data corresponding to the target role. The method comprises the steps of obtaining target historical behavior data of a target role, carrying out feature extraction on the target historical behavior data to obtain a target feature vector, calling a classification model to classify the target feature vector to obtain at least one target index.

In the embodiment of the application, after at least one target is determined from each index according to a target role, a parent-child relationship between each target index can be determined based on a service association relationship between indexes in a service knowledge graph, so as to obtain a target index logic tree.

The knowledge graph is a graph organization form which associates various entities or concepts existing in the real world, and a graph structure is mainly formed by nodes, edges and node attributes. The service knowledge graph may be a service knowledge graph, nodes in the service knowledge graph are used for indicating service items (i.e., indexes), and node attributes of the service knowledge graph are used for indicating service attributes of the service items (i.e., indexes). Edges in the business knowledge graph are used to characterize business association relationships between business items (i.e., indexes). The business association relation among all indexes in the report is described in the business knowledge map.

In one embodiment, the report display device may search a common upper node of nodes corresponding to each target index in the service knowledge graph, use the searched common upper node as a root node, and construct a target index logical tree using the nodes corresponding to each target index as leaf nodes according to a service association relationship of each target index in the service knowledge graph.

Optionally, the step of searching for a common superior node of the nodes corresponding to each target index in the service knowledge graph by the report display device includes: and acquiring the coding sequence of the corresponding node of each target index in the service incidence relation of the service knowledge graph, comparing the coding sequences of the corresponding nodes of each target index to obtain the intersection of the coding sequences, and taking the corresponding node of the intersection of the coding sequences as the common superior node of each target index. For example, as shown in FIG. 3, when the nodes corresponding to the target indexes include a node A corresponding to the financial management part, a node B corresponding to the business expense/net profit, a node C corresponding to the sales expense/new sales expense, a node D corresponding to the business expense, a node E corresponding to the net profit, a node F corresponding to the sales expense, and a node G corresponding to the new sales expense, the coding sequence of the node corresponding to each target index can be obtained, as shown in the service knowledge graph of fig. 3, the coding sequence of the node a is a, the coding sequence of the node B is a-B, the coding sequence of the node C is a-C, the coding sequence of the node D is a-B-D, the coding sequence of the node E is a-B-E, the coding sequence of the node F is a-C-F, and the coding sequence of the node G is a-C-G. Therefore, the coded sequence of the node corresponding to each target index can know the information such as the number of superior nodes of the node. The node A can be known as a common superior node of the nodes corresponding to the target indexes through the coding sequence of each node. The expression form of the coding sequence of the node can be adjusted according to the needs, and the present application does not limit this.

Further, the report display device uses the searched common superior node as a root node, and constructs a target index logic tree using the node corresponding to each target index as a leaf node according to the service association relation of each target index in the service knowledge graph, including: and judging whether father nodes of all nodes in nodes corresponding to other target indexes except the target indexes corresponding to the root node are root nodes or not, and if so, taking the corresponding nodes as child nodes of the root node. In the example shown in fig. 3, with node a as the root node, it can be determined whether the parent nodes of node B, node C, node D, node E, node F, and node G are node a, and if the parent nodes of node B and node C are node a, the parent nodes of node B and node C can be obtained through the service knowledge graph, so that node B and node C can be child nodes of node a. Next, the child nodes of node B and node C may be sequentially obtained, and a target index logical tree as shown in the left diagram of fig. 4 is constructed. The node A corresponding to the financial management part is a first level node of the target index logic tree, the node B corresponding to the operational expense/net profit and the node C corresponding to the sales expense/new sales expense are second level nodes of the target index logic tree, the node D corresponding to the operational expense, the node E corresponding to the net profit, the node F corresponding to the sales expense and the node G corresponding to the new sales expense are third level nodes of the target index logic tree, and the node B corresponding to the operational expense/net profit and the node C corresponding to the sales expense/new sales expense are child nodes of the node A corresponding to the financial management part; the node D corresponding to the business expense and the node E corresponding to the net profit are child nodes of the node B corresponding to the business expense/the net profit, and the node F corresponding to the sales expense and the node G corresponding to the new sales expense are child nodes of the node C corresponding to the sales expense/the new sales expense.

In the embodiment of the application, the target index logic tree can be constructed based on the knowledge graph, the knowledge graph covers the business incidence relation among all indexes in the report, different index logic trees can be rapidly constructed aiming at different roles through the business incidence relation among all the indexes, and the construction speed of the target index logic tree is improved.

Optionally, the index logic tree building page may be displayed, the user operation information in the index logic tree building page is monitored, the target user instruction is generated according to the user operation information, and the parent-child relationship between the target indexes is determined based on the target user instruction, so as to obtain the target index logic tree. The user operation information may include, but is not limited to, one or more items of addition information, deletion information, and movement information. A user can construct a parent-child relationship between page configuration target indexes through the index logic tree, and the target index logic tree can be generated more flexibly.

S203: and sequentially acquiring node index data and node index attributes corresponding to each node of the target index logic tree based on a depth-first traversal algorithm, and displaying each node index data according to the node index attribute corresponding to each node.

In one embodiment, the node index data corresponding to each node and the node index attribute corresponding to each node may be obtained from a preset database directly through a database query statement (e.g., a select statement). The node index data and the node index attributes corresponding to each node may be located in one preset database or may be located in different preset databases. The preset database may be a node index database obtained through data statistical analysis, and is used to store node index data and/or node index attributes of nodes, so as to facilitate subsequent display and analysis, such as a Kylin and Hbase database.

Optionally, node index data corresponding to some nodes may be directly obtained from a preset database, and then node index data corresponding to the node may be directly obtained from the preset database. Optionally, the node index data corresponding to some nodes may not be directly obtained from the preset database, and the node index data corresponding to the node may be determined according to the node index data of the child node corresponding to the node. Specifically, for any node in the target index logic tree, index data of a child node of any node is obtained and used as child node index data, and data processing is performed on the child node index data according to a data processing rule corresponding to any node to obtain node index data corresponding to any node. The data processing rules may include mathematical operation rules (e.g., one or more of addition rules, subtraction rules, multiplication rules, division rules, derivation rules, and integration rules), among others.

For example, in the target index logic tree of the left graph example in fig. 4, the node index data of the node B corresponding to the business expense/net profit may not be directly obtained from the preset database, and needs to be determined by the node index data of the node D corresponding to the business expense and the node index data of the node E corresponding to the net profit. The node index data of the node D corresponding to the business expense and the node index data of the node E corresponding to the net profit can be obtained, and division operation is performed on the node index data of the node D corresponding to the business expense and the node index data of the node E corresponding to the net profit according to the data processing rule of the node B corresponding to the business expense/net profit, so that the node index data of the node B corresponding to the business expense/net profit is obtained.

Further, after the report display device obtains the node index data and the node index attributes corresponding to the nodes of the target index logic tree, the report display device can also store the node index data and the node index attributes corresponding to the nodes of the target index logic tree, and can reuse the node index data and the node index attributes corresponding to the nodes of the target index logic tree.

In an embodiment, the node index data and the node index attribute corresponding to each node of the target index logical tree may be written into a Block Chain (Block Chain), so that the node index data and the node index attribute corresponding to each node of the target index logical tree may be directly obtained subsequently. Specifically, the node index data and the node index attribute corresponding to each node of the target index logic tree can be verified, and if the verification is passed, the node index data and the node index attribute corresponding to each node of the target index logic tree are subjected to consensus verification through a consensus node in the block chain network; and if the consensus verification is passed, packaging the node index data and the node index attributes corresponding to each node of the target index logic tree into a block, and writing the block into a block chain.

The block chain is a chain data structure formed by combining data blocks in a sequential connection mode according to a time sequence, and a distributed account book which can not be tampered and forged of data is guaranteed in a cryptographic mode. Multiple independent distributed nodes maintain the same record. The blockchain technology realizes decentralization and becomes a foundation for credible digital asset storage, transfer and transaction.

In one embodiment, a reference index logic tree is constructed, distinguishing nodes are obtained from the reference index logic tree, the distinguishing nodes are nodes except for nodes of a target index logic tree in the nodes of the reference index logic tree, node index data and node index attributes of the distinguishing nodes are obtained, the node index data of the distinguishing nodes are combined with the node index data corresponding to each node of the target index logic tree, node index data corresponding to each node in the reference index logic tree are determined, and the node index attributes of the distinguishing nodes are combined with the node index attributes corresponding to each node of the target index logic tree to obtain the node index attributes corresponding to each node in the reference index logic tree.

The reference index logical tree may be an updated target index logical tree. The distinguishing nodes are nodes except the nodes of the target index logical tree in the nodes of the reference index logical tree.

For example, as shown in the left diagram of fig. 4, the target metric logical tree includes at least one node: the financial management part comprises a node A corresponding to the financial management part, a node B corresponding to the operational expense/net profit, a node C corresponding to the sales expense/new sales expense, a node D corresponding to the operational expense, a node E corresponding to the net profit, a node F corresponding to the sales expense and a node G corresponding to the new sales expense. As shown in the right diagram of fig. 4, the reference metric logical tree may be obtained by updating the target metric logical tree, where the reference metric logical tree includes at least one node: a node I corresponding to the financial sum part, a node B corresponding to the operational cost/net profit, a node D corresponding to the operational cost, a node E corresponding to the net profit, and a node J corresponding to the budget cost. The determination of the distinct nodes according to the nodes of the reference index logical tree and the nodes of the target index logical tree may include a node I corresponding to the financial sum portion and a node J corresponding to the budget system cost. The node B corresponding to the business expense/net profit, the node D corresponding to the business expense, and the node index data and the node index attribute corresponding to the node E corresponding to the net profit may be multiplexed. That is, the report display device may obtain the node index data of the node I corresponding to the financial sum portion and the node J corresponding to the budget system cost, and determine the node index data of each node in the reference index logical tree based on the node index data of the node I corresponding to the financial sum portion and the node J corresponding to the budget system cost, and the node index data of the node B corresponding to the business cost/net profit in the target index logical tree, the node D corresponding to the business cost, and the node E corresponding to the net profit. That is, the report display device may obtain the node index attributes of the node I corresponding to the financial sum portion and the node J corresponding to the budget system cost, and determine the node index attributes of each node in the reference index logical tree based on the node index attributes of the node I corresponding to the financial sum portion and the node J corresponding to the budget system cost, and the node index attributes of the node B corresponding to the business cost/net profit in the target index logical tree, the node D corresponding to the business cost, and the node E corresponding to the net profit.

When the report display device displays the node index data corresponding to each node in the reference index logic tree, the report display device can multiplex the node index data and the node index attribute corresponding to each node in the target index logic tree. Only the node index data and the node index attribute corresponding to the different nodes can be obtained, the node index data and the node index attribute corresponding to each node in the reference index logic tree do not need to be obtained, and computing resources can be saved.

In the embodiment of the application, the report display device can determine at least one target index from all indexes included in the report according to the target role, can display different indexes aiming at different roles, displays the indexes in a targeted manner, and can meet the requirement that different roles view different visual data. And moreover, a tree structure is introduced, a target index logic tree is constructed based on the logic relation among target indexes, and nodes in the target index logic tree correspond to the target indexes one to one. The incidence relation among the target indexes is described by using a target index logic tree, the incidence relation among the target indexes is clearer, and the display rate of the report can be improved based on the target index logic tree. In addition, the target index logic tree can be constructed based on the knowledge graph, and the construction speed of the target index logic tree can be improved.

As can be seen from the above description of the embodiment of the method shown in fig. 2, the report displaying method shown in fig. 2 can determine the target index according to the target historical behavior data corresponding to the target role. Based on this, the embodiment of the present application provides a flow diagram of another report display method. As shown in FIG. 5, the flow diagram of the report display method includes S501-S503:

s501: and acquiring target historical behavior data corresponding to the target role.

The historical behavior data may include behavior characteristics of the character on the indexes, and the historical behavior data may include, but is not limited to, browsing times of users of the character on the indexes, browsing time duration on the indexes, and the like. For example, the report includes an index a, an index B, an index C, and an index D. The target historical behavior data may be that the browsing times of the target role corresponding to the user in the index a are 10 times, and the browsing time duration is 100 seconds. The browsing times of the index B are 100 times, and the browsing time duration is 100 seconds. The browsing times in the index C are 3 times, and the browsing duration is 35 seconds. And so on. For another example, the report includes an index a, an index B, an index C, and an index D. The target historical behavior data may be that the browsing times of the target role corresponding to the user in the index a are 10 times, and the browsing time duration is 100 seconds. The browsing times of the index B are 100 times, and the browsing time duration is 100 seconds. The browsing times in the index C are 3 times, and the browsing duration is 35 seconds. The browsing times in the index D are 1 time, and the browsing duration is 10 seconds. And so on.

Further, in order to enable the target historical behavior data to more comprehensively characterize the behavior characteristics of the character on each index, the target historical behavior data can be determined based on the long-term first historical behavior data and the short-term second historical behavior data. In one embodiment, first historical behavior data of a user corresponding to a target role in a first time period can be obtained, and second historical behavior data of the user corresponding to the target role in a second time period can be obtained; the duration of the first time period is greater than the duration of the second time period. For example, the first time period may be the week closest to the current time, and the second time period may be the day closest to the current time. The duration of the first time period is long, and long-term behavior characteristics can be acquired in the first time period. That is, the first historical behavior data may include, but is not limited to, the number of times each index is browsed in the first time period, and the browsing duration of each index. The time of the second time period is short, and the short-term behavior characteristics can be acquired in the second time period. That is, the second historical behavior data may include, but is not limited to, the number of times each index is browsed, and the browsing duration of each index in the second time period.

The target historical behavior data of the target role determined according to the first historical behavior data and the second historical behavior data can comprise various forms. Alternatively, the target historical behavior data may be obtained by directly performing addition processing on the first historical behavior data and the second historical behavior data. Optionally, the first historical behavior data and the second historical behavior data may be processed based on an attention mechanism, so as to obtain target historical behavior data corresponding to the target role. Specifically, the attention weight corresponding to the first historical behavior data and the attention weight corresponding to the second historical behavior data may be obtained, and the first historical behavior data and the second historical behavior data are processed based on the attention weight corresponding to the first historical behavior data and the attention weight corresponding to the second historical behavior data, so as to obtain the target historical behavior data corresponding to the target role. Wherein attention mechanism means that attention can be focused on the actually important feature by attention weight. For example, when the long-term behavior feature is more focused, the attention weight of the first historical behavior data may be set to be greater than the attention weight of the second historical behavior data. For another example, when the short-term behavior feature is more focused, the attention weight of the second historical behavior data may be set to be greater than the attention weight of the first historical behavior data.

S502: and performing feature extraction on the historical behavior data of the target to obtain a target feature vector.

Specifically, the target historical behavior data may be encoded to obtain an encoded vector, and then the encoded vector may be feature-extracted by using a feature extraction layer to obtain a target feature vector. The target historical behavior data can be encoded by an encoding method to obtain an encoding vector. The encoding method may be One-Hot encoding (One-Hot encoding) or the like. The feature extraction layer may be a convolutional neural network, and the feature extraction may be performed on the coding vector by using the convolutional neural network to obtain a feature vector. Specifically, the encoding vector may be divided into two-dimensional matrices of the same shape, and the two-dimensional matrices may be input to a convolutional neural network, and the convolutional neural network may perform sliding convolution on a plurality of two-dimensional matrices to obtain the target feature vector. Therein, the convolutional neural network may comprise a plurality of convolutional layers, for example, the convolutional neural network comprises four convolutional layers of 1 x 3, 1 x 4, 1 x 5 and 1 x 6.

S503: and calling a classification model to classify the target feature vectors to obtain target indexes.

In one embodiment, a classification task may be included in the classification model. Calling a classification model to classify the target feature vectors to obtain target indexes, wherein the classification model comprises the following steps: and calling a classification model to determine the confidence coefficient of each index according to the target feature vector and the feature vector corresponding to each index in the report, acquiring a preset threshold, and determining the index with the confidence coefficient greater than the preset threshold in each index as the target index.

In another embodiment, the classification model may include a plurality of classification tasks, and one classification task may be used to determine whether an index in the report is a target index. Calling a classification model to classify the target feature vectors to obtain target indexes, wherein the classification model comprises the following steps: and respectively calling each classification task to determine the confidence of each index in the report, and determining the index with the confidence greater than the reference threshold as a target index.

Aiming at any index in the report, the classification task corresponding to the any index can be called to determine the confidence coefficient of the any index according to the target feature vector and the feature vector of the any index, the confidence coefficient is used for indicating the probability that the target feature vector belongs to the feature vector of the any index, and when the confidence coefficient of the any index is larger than a reference threshold value, the any index is determined to be the target index. When the confidence of the arbitrary index is less than or equal to a reference threshold, it is determined that the arbitrary index is not the target index. For example, for an index a and an index b in a report, a classification task corresponding to the index a may be called to classify a target feature vector, so as to determine a confidence of any index according to the target feature vector and the feature vector of the index a, that is, to determine a probability that the target feature vector belongs to the feature vector of the index a, compare the confidence of the index a with a reference threshold, and determine that the index a is a target index when the confidence of the index a is greater than the reference threshold. The classification task corresponding to the index b can be called to classify the target feature vector, so as to determine the confidence of any index according to the target feature vector and the feature vector of the index b, namely to determine the probability that the target feature vector belongs to the feature vector of the index b, compare the confidence of the index b with a reference threshold, and when the confidence of the index b is smaller than or equal to the reference threshold, determine that the index b is not the target index. Wherein the reference threshold may be set according to the traffic demand or experience, for example, the reference threshold may be set to 0.5.

Wherein, the classification task may be trained by Machine Learning (ML) algorithm based on artificial intelligence technology, and the Machine Learning algorithm may include, but is not limited to, one or more of the following: decision Tree (DT) algorithm, Rocchio algorithm, extreme Gradient Boosting (xgboost) algorithm, Naive Bayes (Naive Bayes, NB) algorithm, Linear Discriminant Analysis (LDA), Support Vector Machine (SVM) algorithm, Random Forest (RF) algorithm, Logistic Regression (LR) algorithm, and deep neural network, etc.

In the embodiment of the application, the report display device can determine the target historical behavior data based on the long-term first historical behavior data and the short-term second historical behavior data, and then determine the target index according to the target historical behavior data. The target historical behavior data is determined based on the first historical behavior data and the second historical behavior data, long-term characteristics and short-term characteristics are comprehensively considered, behavior characteristics of the role in each index can be more comprehensively represented, and therefore the determined target index is more accurate.

The embodiment of the application also discloses a report display device, which can be a computer program (including program codes) running in the above mentioned report display equipment. The report display apparatus may perform the method shown in fig. 2 or fig. 5. Referring to fig. 6, the report display apparatus may operate as follows:

an obtaining unit 601, configured to obtain each index included in the report;

a determining unit 602, configured to determine at least one target indicator from the indicators according to a target role, and determine a parent-child relationship between the target indicators based on a service association relationship between the indicators in the service knowledge graph, to obtain a target indicator logic tree; each node in the target index logic tree corresponds to each index in the target index one by one;

the display unit 603 is configured to sequentially obtain node index data and node index attributes corresponding to each node in the target index logic tree based on a depth-first traversal algorithm, and display each node index data according to the node index attribute corresponding to each node.

In a possible implementation manner, the determining unit 602 is configured to determine a parent-child relationship between each target indicator based on a service association relationship between indicators in a service knowledge graph, and obtain a target indicator logical tree, including:

searching a common superior node of nodes corresponding to each target index in a service knowledge graph;

and constructing a target index logic tree which takes the nodes corresponding to the target indexes as leaf nodes according to the service association relation of the target indexes in the service knowledge graph.

In a possible embodiment, after the determining unit 602 is configured to determine at least one target index from the indexes according to the target role, the determining unit 602 is further configured to:

displaying an index logic tree construction page;

monitoring user operation information in the index logic tree construction page, and generating a target user instruction according to the user operation information;

and determining the parent-child relationship among all target indexes based on the target user instruction to obtain a target index logic tree.

In a possible implementation manner, the display unit 603 is configured to sequentially obtain node index data corresponding to each node of the target index logical tree based on a depth-first traversal algorithm, and includes:

the index data of a child node of any node in the target index logic tree is used as child node index data;

and performing data processing on the sub-node index data according to the data processing rule corresponding to any one node to obtain the node index data corresponding to any one node.

In a possible implementation manner, after the display unit 603 is configured to sequentially obtain node index data and node index attributes corresponding to each node of the target index logical tree based on a depth-first traversal algorithm, the display unit 603 is further configured to:

constructing a reference index logic tree;

acquiring a difference node from the reference index logic tree, wherein the difference node is a node in the reference index logic tree except for the node of the target index logic tree;

the node index data and the node index attributes of the distinguishing nodes are obtained, the node index data of the distinguishing nodes are combined with the node index data corresponding to each node of the target index logic tree, the node index data corresponding to each node in the reference index logic tree are determined, and the node index attributes of the distinguishing nodes are combined with the node index attributes corresponding to each node of the target index logic tree to obtain the node index attributes corresponding to each node in the reference index logic tree.

In a possible implementation, the determining unit 602 is configured to determine at least one target index from the indexes according to the target role, and includes:

acquiring target historical behavior data of a target role, and performing feature extraction on the target historical behavior data to obtain a target feature vector;

and calling a classification model to classify the target feature vectors to obtain at least one target index.

In a possible implementation manner, the determining unit 602 is configured to invoke a classification model to perform classification processing on the target feature vector, so as to obtain at least one target indicator, where the method includes:

calling a classification model to determine the confidence of each index according to the target feature vector and the feature vector corresponding to each index in the report;

and acquiring a preset threshold, and determining indexes with the confidence degrees larger than the preset threshold in all indexes as at least one target index.

According to another embodiment of the present application, the units in the report display apparatus shown in fig. 6 may be respectively or entirely combined into one or several other units to form the report, or some of the units may be further split into multiple units with smaller functions to form the report, which may implement the same operation without affecting implementation of technical effects of the embodiment of the present application. The units are divided based on logic functions, and in practical applications, the functions of one unit may be implemented by a plurality of units, or the functions of a plurality of units may be implemented by one unit. In other embodiments of the present application, the report-based display device may also include other units, and in practical applications, these functions may also be implemented by being assisted by other units, and may be implemented by cooperation of multiple units.

According to another embodiment of the present application, the Processing element and the memory element may include a Central Processing Unit (CPU), a random access memory medium (RAM), a read only memory medium (ROM), and the like. A general purpose computing device, such as a computer, runs a computer program (including program code) capable of executing the steps involved in the corresponding method shown in fig. 2 or fig. 5, to construct a report display apparatus shown in fig. 6, and to implement the report display method of the embodiment of the present application. The computer program may be recorded on a computer-readable recording medium, for example, and loaded and executed in the report display apparatus through the computer-readable recording medium.

Based on the description of the report display method embodiment, the embodiment of the application also discloses a report display device. Referring to fig. 7, the report display apparatus at least includes a processor 701, an input interface 702, an output interface 703 and a computer storage medium 704, which can be connected by a bus or other means.

The computer storage medium 704 is a memory device in the report display device for storing programs and data. It is understood that the computer storage medium 704 herein may include both the built-in storage medium of the report display device and, of course, the extended storage medium supported by the report display device. The computer storage medium 704 provides storage space that stores the operating system of the report display device. Also stored in this memory space are one or more instructions, which may be one or more computer programs (including program code), suitable for loading and execution by processor 701. Note that the computer storage media herein can be high-speed RAM memory; optionally, the report display device may further include at least one computer storage medium remote from the processor, where the processor may be referred to as a Central Processing Unit (CPU), and is a core and a control center of the report display device, and the processor is adapted to be implemented with one or more instructions, and specifically load and execute the one or more instructions to implement the corresponding method flow or function.

In one embodiment, one or more instructions stored in the computer storage medium 704 may be loaded and executed by the processor 701 to implement the steps involved in performing the corresponding method as shown in fig. 2 or fig. 5, and in particular, one or more instructions stored in the computer storage medium 704 may be loaded and executed by the processor 701 to implement the steps of:

acquiring each index included in the report;

determining target indexes from all indexes according to target roles, and determining parent-child relations among all the target indexes based on service incidence relations among the indexes in the service knowledge graph to obtain a target index logic tree; each node in the target index logic tree corresponds to each index in the target index one by one;

and sequentially acquiring node index data and node index attributes corresponding to each node in the target index logic tree based on a depth-first traversal algorithm, and displaying each node index data according to the node index attributes corresponding to each node.

In a possible embodiment, the processor 701 is configured to determine a parent-child relationship between each target indicator based on a service association relationship between indicators in a service knowledge graph, and obtain a target indicator logic tree, including:

In a possible embodiment, after the processor 701 is configured to determine at least one target index from the indexes according to the target role, the processor 701 is further configured to:

displaying an index logic tree construction page;

In a possible implementation manner, the processor 701 is configured to sequentially obtain node index data corresponding to each node of the target index logical tree based on a depth-first traversal algorithm, and includes:

In a possible implementation manner, after the processor 701 is configured to sequentially obtain node index data and node index attributes corresponding to each node of the target index logical tree based on a depth-first traversal algorithm, the processor 701 is further configured to:

constructing a reference index logic tree;

acquiring node index data and node index attributes of the distinct nodes, combining the node index data of the distinct nodes with the node index data corresponding to each node of the target index logic tree, determining the node index data corresponding to each node in the reference index logic tree, and combining the node index attributes of the distinct nodes with the node index attributes corresponding to each node of the target index logic tree to obtain the node index attributes corresponding to each node in the reference index logic tree.

In one possible embodiment, the processor 701 is configured to determine at least one target index from the indexes according to the target role, and includes:

In a possible embodiment, the processor 701 is configured to invoke a classification model to perform classification processing on the target feature vector, so as to obtain at least one target indicator, where the method includes:

It should be noted that the present application also provides a computer program product or a computer program, where the computer program product or the computer program includes computer instructions, and the computer instructions are stored in a computer-readable storage medium. The processor of the report display device reads the computer instruction from the computer readable storage medium, and the processor executes the computer instruction, so that the report display device executes the steps executed in the embodiment of the report display method shown in fig. 2 or fig. 5.

While the foregoing is directed to embodiments of the present invention, other and further embodiments of the invention may be devised without departing from the basic scope thereof, and the scope thereof is determined by the claims that follow.

Claims

1. A report display method is characterized by comprising the following steps:

acquiring each index included in the report;

determining at least one target index from the indexes according to a target role, and determining a parent-child relationship among the target indexes based on a service incidence relationship among the indexes in a service knowledge graph to obtain a target index logic tree; nodes in the target index logic tree correspond to the target indexes one by one;

2. The method of claim 1, wherein determining parent-child relationships between the target metrics based on business associations between metrics in a business knowledge graph to obtain a logical tree of target metrics comprises:

searching a common superior node of the nodes corresponding to the target indexes in the service knowledge graph;

and taking the searched common superior node as a root node, and constructing a target index logic tree taking the node corresponding to each target index as a leaf node according to the service incidence relation of each target index in the service knowledge graph.

3. The method of claim 1, wherein after determining at least one target metric from the metrics based on target role, the method further comprises:

displaying an index logic tree construction page;

and determining a parent-child relationship among the target indexes based on the target user instruction to obtain the target index logic tree.

4. The method of claim 1, wherein the sequentially obtaining node index data corresponding to each node of the target index logical tree based on a depth-first traversal algorithm comprises:

acquiring index data of a child node of any node in the target index logic tree as child node index data;

and performing data processing on the sub-node index data according to a data processing rule corresponding to any one of the nodes to obtain node index data corresponding to any one of the nodes.

5. The method of claim 1, wherein after the depth-first traversal-based algorithm sequentially obtains the node index data and the node index attributes corresponding to the nodes of the target index logical tree, the method further comprises:

constructing a reference index logic tree;

6. The method according to any of claims 1-5, wherein said determining at least one target metric from said respective metrics based on target role comprises:

acquiring target historical behavior data of the target role, and performing feature extraction on the target historical behavior data to obtain a target feature vector;

and calling a classification model to classify the target feature vector to obtain at least one target index.

7. The method of claim 6, wherein said invoking a classification model to classify said target feature vector to obtain at least one of said target metrics comprises:

calling the classification model to determine the confidence of each index according to the target feature vector and the feature vector corresponding to each index in the report;

and acquiring a preset threshold, and determining the index with the confidence level greater than the preset threshold in each index as at least one target index.

8. A report display apparatus, comprising:

the acquisition unit is used for acquiring each index included in the report;

the determining unit is used for determining at least one target index from the indexes according to a target role, and determining a parent-child relationship among the target indexes based on a service incidence relationship among the indexes in a service knowledge graph to obtain a target index logic tree; each node in the target index logic tree corresponds to each index in the target indexes one to one;

and the display unit is used for sequentially acquiring the node index data and the node index attributes corresponding to the nodes in the target index logic tree based on a depth-first traversal algorithm, and displaying the node index data according to the node index attributes corresponding to the nodes.

9. A report display device comprises an input interface and an output interface, and is characterized by further comprising:

a computer storage medium having stored thereon one or more instructions adapted to be loaded by the processor to perform the report display method of any of claims 1-7.

10. A computer-readable storage medium, characterized in that the computer-readable storage medium stores a computer program comprising program instructions that, when executed by a processor, cause the processor to perform the report display method according to any one of claims 1-7.