CN110347752B

CN110347752B - Data processing method, device, computer readable storage medium and computer equipment

Info

Publication number: CN110347752B
Application number: CN201810321933.9A
Authority: CN
Inventors: 黄贤贤; 段文超
Original assignee: Tencent Technology Shenzhen Co Ltd
Current assignee: Tencent Technology Shenzhen Co Ltd
Priority date: 2018-04-11
Filing date: 2018-04-11
Publication date: 2023-07-11
Anticipated expiration: 2038-04-11
Also published as: CN110347752A

Abstract

The application relates to a data processing method, a device, a computer readable storage medium and a computer apparatus, the method comprising: responding to a data request of a terminal, and inquiring a first topological graph obtained based on the association relation between the entities; sending a first topological graph to a terminal; inquiring graph data obtained by analyzing the data based on the entity corresponding to the node when the graph data request sent by the terminal in response to the operation of the node of the first topological graph is obtained; and sending the chart data to the terminal. The method uses topology diagram to represent the association relation between the entities, so that the association between the entities can be intuitively known, and the single entities are not isolated but connected. Through binding of the nodes and the chart data of the entity, when the nodes are triggered on the topological graph, the chart data of the entity can be obtained, so that the analysis of the data becomes comprehensive and visual.

Description

Data processing method, device, computer readable storage medium and computer equipment

Technical Field

The present invention relates to the field of data analysis technologies, and in particular, to a data processing method, apparatus, computer readable storage medium, and computer device.

Background

Along with the development of internet technology, how to grasp key data from a large amount of information, improve information processing efficiency, help people to make decisions is a problem to be solved urgently.

To solve this problem, a data analysis tool having a graph analysis function, such as microsoft office software Excel, is provided. The chart analysis can present key data and provide charts in various forms such as line drawings, bar charts, and gravity charts, which can be analyzed. And displaying the development trend of the event, key influencing factors and the like according to the analysis result, and helping people to quickly know key information.

However, conventional data analysis tools typically analyze only critical data from one dimension, and the analysis results are not comprehensive.

Disclosure of Invention

Based on this, it is necessary to provide a data processing method, apparatus, computer-readable storage medium and computer device for solving the technical problem of incomplete analysis.

A data processing method, comprising:

responding to a data request of a terminal, and inquiring a first topological graph obtained based on the association relation between the entities;

sending the first topological graph to the terminal;

Inquiring graph data obtained by analyzing the data based on the entity corresponding to the node when a graph data request sent by the terminal in response to the operation of the node of the first topological graph is obtained;

and sending the chart data to the terminal.

A data processing method, comprising:

responding to the data request operation, and acquiring a first topological graph obtained based on the association relationship between the entities from a server;

displaying the first topological graph;

when the operation of the nodes of the first topological graph is obtained, obtaining the nodes;

requesting graph data corresponding to the nodes from a server, wherein the graph data is obtained by analyzing the data of the entities corresponding to the nodes;

the chart data is received and presented.

A data processing apparatus comprising:

the query module is used for responding to the data request of the terminal and querying a first topological graph obtained based on the association relation between the entities;

a sending module, configured to send the first topology map to the terminal;

the query module is further configured to query graph data obtained by analyzing data based on an entity corresponding to a node when a graph data request sent by a terminal in response to an operation on the node of the first topological graph is obtained;

The sending module is further configured to send the chart data to the terminal.

A data processing apparatus comprising:

the topology map acquisition module is used for responding to the data request operation and acquiring a first topology map obtained based on the association relationship between the entities from the server;

the display module is used for displaying the first topological graph;

the node acquisition module is used for acquiring the nodes when acquiring the operation on the nodes of the first topological graph;

the chart request module is used for requesting chart data corresponding to the nodes from a server, wherein the chart data is obtained by analyzing the data of the entities corresponding to the nodes;

the display module is also used for receiving and displaying the chart data.

A computer readable storage medium storing a computer program which, when executed by a processor, causes the processor to perform the steps of any one of the methods described above.

A computer device comprising a memory and a processor, the memory storing a computer program that, when executed by the processor, causes the processor to perform the steps of any of the methods described above.

According to the data processing method, the topological graph is obtained according to the association relation between the entities, and each node of the topological graph is bound with the chart data. The association relation between the entities is represented by a topological graph, so that the association between the entities can be intuitively known, and the single entities are not isolated but connected. Through binding of the nodes and the chart data of the entity, when the nodes are triggered on the topological graph, the chart data obtained for the entity can be obtained, so that the analysis of the data becomes comprehensive and visual.

Drawings

FIG. 1 is a diagram of an application environment for a data processing method in one embodiment;

FIG. 2 is a flow diagram of a data processing method in one embodiment;

FIG. 3 is a flow chart illustrating steps for processing to obtain a first topology in one embodiment;

FIG. 4 is a flow chart illustrating steps for processing to obtain a second topology in one embodiment;

FIG. 5 is a flowchart illustrating steps for processing to obtain a first topology according to another embodiment;

FIG. 6 is a flowchart illustrating steps for processing to obtain a second topology according to another embodiment;

FIG. 7 is a schematic diagram of a server processing data in one embodiment;

FIG. 8 is a flow chart illustrating steps for processing diagram data in one embodiment;

FIG. 9 is a flow diagram of a method of data processing in one embodiment;

FIG. 10 is a schematic diagram of a first topology in one embodiment;

FIG. 11 is a schematic diagram of chart data in one embodiment;

FIG. 12 is a schematic diagram of a second topology in one embodiment;

FIG. 13 is a timing diagram of a data processing method in one embodiment;

FIG. 14 is a block diagram of a data processing apparatus in one embodiment;

FIG. 15 is a block diagram showing the structure of a data processing apparatus in another embodiment;

FIG. 16 is a block diagram of a computer device in one embodiment.

Detailed Description

In order to make the objects, technical solutions and advantages of the present application more apparent, the present application will be further described in detail with reference to the accompanying drawings and examples. It should be understood that the specific embodiments described herein are for purposes of illustration only and are not intended to limit the present application.

FIG. 1 is a diagram of an application environment for a data processing method in one embodiment. Referring to fig. 1, the data processing method is applied to a data processing system. The data processing system comprises a reporting terminal 110, a querying terminal 120 and a server 130. The reporting terminal 110 and the query terminal 120 are respectively connected to the server 130, and the server 130 may include a data reporting server 1301 for receiving the reporting data of the reporting terminal 110, a mining server 1302 for mining the reporting data to obtain data including a topology map and a chart, a data storage server 1303 for storing the mining result, and a web page display server 1304 for reading the data from the data storage server and displaying the data on a web page. The reporting terminal 110 and the querying terminal 120 may be specifically desktop terminals or mobile terminals, and the mobile terminals may be specifically at least one of mobile phones, tablet computers, notebook computers, and the like. The server 120 may be implemented as a stand-alone server or as a server cluster composed of a plurality of servers.

As shown in fig. 2, in one embodiment, a data processing method is provided. The present embodiment is mainly exemplified by the method applied to the server 130 in fig. 1. Referring to fig. 2, the data processing method specifically includes the steps of:

s202, responding to a data request of a terminal, and inquiring a first topological graph obtained based on the association relation between the entities.

The terminal of this embodiment is referred to as the inquiry terminal 120 in fig. 1. The data request is a request sent by the inquiring terminal 120 in response to the inquiring operation of the terminal.

The inquiring terminal obtains the inquiring authority after the authentication of the server 130 is passed. Specifically, the server 130 performs authority authentication on the user account logged in by the query terminal 120, and after the authority authentication is passed, responds to the data request of the terminal. The data analysis tool provided by the server analyzes the data of a plurality of entities with association relations provided by the user, and a topological graph capable of intuitively knowing the association relations among the entities is formed according to the association relations. The data request of the terminal is used for requesting the server to acquire the topological graph.

Specifically, the data request includes a user account and query content. The server 130 verifies the query authority of the user according to the user account number, and feeds back the topology map corresponding to the query content after the verification is passed.

In one embodiment, a user analyzes, for example, user behavior data by purchasing a data analysis service at server 130. The user purchases the corresponding service to obtain the inquiry authority, and can inquire the corresponding result through logging in the user account to obtain the topological graph representing the time sequence relation of the operation behavior. In another embodiment, the administrator may also perform authority configuration on the user account with the management authority, where the user account with the management authority may be an administrator who manages the network device of the machine room. The manager has the authority to inquire the analysis result of the network equipment. And inquiring a corresponding result through logging in the user account number to obtain a topological graph representing the connection relation of the network equipment.

An entity is a transaction or event that is independent and of practical significance. The entities corresponding to different analysis requirements are different. The entity in this embodiment is an analysis target of a data analysis tool, and the data analysis tool analyzes the entity and links the entities based on the association relationship between the entities to obtain a first topological graph. The topological graph is a network structure diagram formed by nodes and connecting lines between the nodes, and can clearly and intuitively represent the association relation between the entities through the topological graph. Wherein each node of the first topology is an entity.

The association relationship refers to a relationship between entities. Such a link may be intuitive, such as a connection relationship, or may be latent, as obtained by analysis of entity-related data, such as a timing relationship of operational behavior. The entities corresponding to different analysis requirements are different. The data source to be analyzed comprises a plurality of entities, and the aim of the embodiment is to display the association relation among the entities and display the data of each entity in a chart form.

Taking the requirement as an example of analyzing the operation behaviors of users on advertisements in an application program, in the application program, advertisements are put in different positions of a page, and a user who wants to know the operation behaviors of users in each advertisement position. In this embodiment, the entity is an operation event of the user for each advertisement. The operation event may be clicking on the advertisement a, closing a certain advertisement B, etc., and the association relationship between the entities is the time sequence relationship of each operation behavior. By analyzing the operation event, the operation time sequence of the clicking action of the user on the advertisement can be known, for example, after the user clicks the advertisement A position, the user closes or views the advertisement A position, and after the user clicks the advertisement A position, whether the advertisement B position is clicked or not, and the like.

S204, the first topological graph is sent to the terminal.

The query terminal receives the first topological graph sent by the server and displays the first topological graph on a display interface of the query terminal. Through the first topological graph, a user can intuitively know the association relationship among the entities.

S206, inquiring the graph data obtained by analyzing the data based on the entity corresponding to the node when the graph data sent by the terminal in response to the operation of the node of the first topological graph is obtained.

The topology graph is composed of nodes and links between nodes. The topology graph of the present embodiment represents the association relationship between entities, and therefore, the nodes of the topology graph are entities.

And in order to distinguish each node, a unique identification mark is allocated for each node of the first topological graph, and a corresponding relation among the node identification mark, the entity and the chart data is established. For example, the node numbered 001 corresponds to operation behavior 1, and operation behavior 1 corresponds to graph data obtained by analyzing the related data of operation behavior 1.

When a user operates the node at the terminal through the query terminal, the terminal responds to the operation of the node, acquires the identification of the node and sends a chart data request to the server. The server queries and obtains the graph data of the entity of the node based on the identification mark of the node and according to the identification mark of the node and the corresponding relation between the entity and the graph data. In this embodiment, the interaction mode of the user and the terminal interaction node is not limited, and can be implemented through multiple interaction modes such as clicking by an input tool, clicking by a touch screen, sliding operation, somatosensory control and the like.

The related data of the entity can be analyzed from multiple dimensions to obtain chart data so as to comprehensively analyze the entity. Taking an entity as an example of advertisement clicking, the method can analyze the daily click quantity, the duty ratio of the daily click quantity, the trend of the monthly click quantity and other multidimensional of the advertisement and display the multidimensional in the form of a corresponding chart.

The chart data is the relevant analysis result intuitively displayed by a visual method such as a chart or a table. The chart data includes a line graph, a bar graph, a specific gravity graph, and the like. In particular embodiments, data may be analyzed from a plurality of different angles or dimensions, resulting in a multi-dimensional data graph of the data. Typically, a multi-dimensional data graph comprises a series of data graphs, with different data graphs representing data from different angles of analysis. For example, the click rate of multiple advertisements at the same time is compared, the click rate trend of the same advertisement in one day is analyzed, the click rate of one advertisement accounts for the click rate of all advertisements, and the like. In this embodiment, the server performs multidimensional analysis on related data of the entity in advance, generates corresponding chart data by using a chart generation tool provided by the server, and binds the chart data with the entity. And when the chart data request sent by the terminal responding to the trigger operation of the user on the node is obtained, sending the chart data corresponding to the node to the terminal.

And S208, sending the chart data to the terminal.

The query terminal receives the chart data sent by the server and displays the chart data on a display interface of the query terminal. The user can intuitively understand the multidimensional analysis data of the entity through the chart data.

According to the data processing method, the topological graph is obtained according to the association relation between the entities, and each node of the topological graph is bound with the chart data. The association relation between the entities is represented by a topological graph, so that the association between the entities can be intuitively known, and the single entities are not isolated but connected. Through binding of the nodes and the chart data of the entities, when the nodes are triggered on the topological graph, the chart data obtained by analyzing the data of the entities can be obtained, so that the analysis of the data becomes comprehensive and visual.

In another embodiment, the data processing method further comprises: and inquiring a second topological graph associated with the path when a path inquiring request sent by the terminal in response to the operation of the path of the first topological graph is acquired, and sending the second topological graph to the terminal. The second topological graph is obtained through a first type entity corresponding to the path and an associated second type entity, the first type entity is an entity corresponding to a head node or a tail node of the path, and in the association relationship between the entities, the first type entity corresponding to the head node is associated to the first type entity corresponding to the tail node through each second type entity.

The first kind of entity refers to an entity whose key index meets the setting requirement. The second type of entity is an entity whose key index does not meet certain requirements. Taking the key index as an example, the CPU utilization rate is taken as the first type entity, which is the network equipment with the CPU utilization rate larger than the threshold value, and the second type entity, which is the network equipment with the CPU utilization rate smaller than the threshold value.

The path refers to a road in the topology map that points to a specific target, which in this embodiment may be a first type entity. The topological graph is formed by nodes and connecting lines between the nodes, and the paths are one or more connecting lines which are connected in sequence and point to the first kind of entities in the topological graph. In a path of the topological graph, an entity corresponding to a head node or a tail node of the path is a first-class entity.

Each link of the first topology graph has a unique link identification identifier, each path pointing to a specific target also has a unique path identification identifier, the link identification identifier is associated with an entity to which the link is connected, the link identification junction identifier is associated with the path identification identifier, and one path identification may correspond to a plurality of links. The path identification is associated with a specific target (first class entity) and a second topology map.

When the first topological graph is displayed on the display interface of the query terminal, the association relationship among the entities can be intuitively known according to the first topological graph, and chart data obtained by analyzing the entities can be obtained through triggering nodes. When a user operates a certain connecting line through the query terminal, searching a corresponding path identifier according to the connecting line identifier, and acquiring a corresponding second topological graph based on the path identifier.

The second topological graph is obtained through the first type entity corresponding to the path and the associated second type entity.

In a path of the topological graph, an entity corresponding to a head node or a tail node of the path is a first-class entity. In the association relation between the entities, a first type entity corresponding to the first node is associated to a first type entity corresponding to the second node through each second type entity. The second topological graph can be aggregation of multiple paths in the first topological graph, or refinement of one path in the first topological graph.

In this embodiment, by associating the second topology map with the path, the path of the first topology can be further aggregated or refined on the basis of the displayed first topology map, so that it is convenient to deeply analyze the entity details and increase the information amount of path analysis.

In one embodiment, a server acquires entity data and an association relationship between entities in advance, and processes the acquired topology map and chart data. Specifically, as shown in fig. 3, the determining manner of the first topology map includes:

s302, acquiring the entity and the association relation between the entities.

Specifically, the association relationship between the entities can be obtained through the entity data. Entity data is entity-related data capable of characterizing various items of information of an entity, including, but not limited to, entity names and entity association information. It will be appreciated that the entity data corresponding to different analysis objects is different. For the user behavior analysis platform, the entity is an operation event, that is, the user operates on the application platform, and the entity data includes, but is not limited to, operation event content, operation time, operation position and the like. Taking an operational event entity as an example of an advertisement click, entity data includes, but is not limited to, a click event, a clicked advertisement spot, an advertisement dispenser, advertisement content, click time and viewing time, and the like.

The association relationship refers to a relationship between entities. Such a link may be intuitive, such as a connection relationship, or may be latent, as obtained by processing entity-related data, such as a timing relationship of operational behavior. The entities corresponding to different analysis requirements are different.

S304, extracting a first entity of which the key index meets the setting requirement.

The key index is an entity evaluation index concerned by the demand analysis. Generally, the key index is related to the evaluation of the entity. For example, the operation event entity refers to an event triggered by a related operation performed by a user on an application program, such as a click event triggered by a click operation of an advertisement on a display page of the application program by the user, a close event triggered by closing the advertisement operation, and the like. Each operational event entity has a timing relationship based on an operational time. For an operational event entity, the key index may be an operational rate of the operational event. The operation rate refers to the proportion of the triggers of the operation event entities to the triggers of all operation event entities of interest for the demand analysis. For example, the operation rate for advertisement A is the click-through rate for advertisement A.

The key index may be known to be, for example, included in entity data, such as CPU utilization of a certain network device. The key index may also be calculated from entity data, e.g., the operation rate is calculated from all operation event entity data.

It will be appreciated that for a demand analysis, the entities of interest are typically of the same category. For example, demand analysis of ad spots, the entity of interest is related to the operation of application advertising content. As another example, the demand analysis of a video application, the entity of interest is related to the operation of the video in the application.

In this embodiment, the setting requirements are used to divide the entities into key entities and common entities. A threshold value is set that distinguishes between key entities, for example 5%. Taking an operation event entity as an example, when the operation rate of one operation event entity is greater than the threshold, the operation event entity can be considered as a key operation event, i.e. a first type operation event entity. The threshold may be adjusted empirically.

It will be appreciated that in practical applications, different thresholds may also be set to correspond to different entity levels. The topology map corresponding to the entity level shown by each entity level.

S306, obtaining a first topological graph based on the association relation between the first kind of entities.

Specifically, according to the association relation between the first type of entities, each associated entity is searched in turn to form a first topological graph. Through the first topological graph, the association relationship between the entities can be intuitively known. Taking an operation event entity as an example, according to the sequence of the operation corresponding to the first type of operation event entity, sequentially searching the operation event entity to form a first topological graph.

As shown in fig. 4, further, the determining manner of the second topology includes:

s308, determining paths pointing to nodes corresponding to the entities of the first type in the first topological graph.

The first kind of entity refers to an entity whose key index meets the setting requirement. Taking the user operation event entity as an example, the key index may be an entity whose operation rate (e.g., click rate) is greater than a threshold.

A path is a road in the topology graph that points to an entity of the first type. The topological graph is formed by nodes and connecting lines between the nodes, and the paths are one or more connecting lines which are connected in sequence and point to the first kind of entities in the topological graph. In a path of the topological graph, an entity corresponding to a head node or a tail node of the path is a first-class entity. Specifically, after determining a path, the path may be associated with a connection line that constitutes the path, and when an operation on the connection line is acquired, a corresponding path may be determined according to the association relationship.

And S310, obtaining a second topological graph according to the first type entity corresponding to the head node of the path, the first type entity corresponding to the tail node and the second type entity of the first type entity corresponding to the tail node in the association relation between the entities.

The first topological graph shows the association relation between the entities with the key indexes larger than the threshold value, and the first node and the tail node are two nodes connected by one path. In the association relationship, the head node and the tail node can be associated by a second type entity, and the second type entity can be an entity with a key index smaller than a threshold value. But the second class of entities associated with the first class of entities are not embodied in the first topology. I.e. the first topology shows some associations between entities of the first type with higher key indexes. For example, in a user behavior analysis, the second type of entity is an advertisement with a click rate smaller than a threshold, and in this application scenario, the first topological graph is used to show the operation time sequence of the user on the advertisement with the click rate exceeding the threshold. Between the timing of the operation of the advertisement whose click-through rate exceeds the threshold, the user also operates on the advertisement whose click-through rate is less than the threshold. The time sequence relationship cannot be displayed through the first topological graph, namely the association relationship among the entities cannot be displayed globally.

In this embodiment, the second topology map is obtained according to the first type entity and the associated second type entity corresponding to the path, and the second topology map is bound with the path. When the path is triggered by the querying terminal, the second topology map is requested to the server. The second topological graph can show the time sequence flow direction of the operation behaviors with the click rate smaller than the threshold value from the operation behaviors with the click rate larger than the threshold value corresponding to the head node to the operation behaviors with the click rate larger than the threshold value corresponding to the tail node. The first topological graph is an abstract aggregated association relationship graph, and by clicking a certain path of the first topological graph, sub-path association relationships comprising second class entity details on the association relationship represented by the path can be obtained. Such sub-path association relationship may be a plurality of sub-paths.

And S312, storing the paths and the second topological graph correspondingly.

By the method, the association relation between the entities with the key indexes larger than the threshold value is displayed first, so that the demander is helped to know the data flow direction between the key high-frequency entities, and the readability of the key information is ensured. By providing the second topological graph, all sub-paths between two entity paths can be unfolded, and the demander is helped to analyze the association relation of any sub-path.

In another embodiment, the server acquires the association relationship between the entity data and the entity in advance, and processes the association relationship to obtain each topological graph and chart data. Specifically, as shown in fig. 5, the determination manner of the first topology map includes:

s502, acquiring the entity and the association relation between the entities.

S504, obtaining a first topological graph based on the association relation between the entities.

Specifically, according to the association relation among all the entities, each associated entity is searched in turn to form a first topological graph. Through the first topological graph, the association relationship between the entities can be intuitively known. Taking an operation event entity as an example, sequentially searching the operation event entities according to the sequence of the operation corresponding to all the entities to form a first topological graph. The first topological diagram in this embodiment shows a global relationship, that is, an association relationship between each entity.

As shown in fig. 6, the determination method of the second topology map includes:

s506, extracting a first type entity of which the key index meets the setting requirement and a second type entity of which the key index does not meet the setting requirement.

The key index is an entity evaluation index concerned by the demand analysis. Generally, the key index is related to the evaluation of the entity. The key index may be known to be, for example, included in entity data, such as CPU utilization of a certain network device. The key index may also be calculated from entity data, e.g., the operation rate is calculated from all operation event entity data.

In this embodiment, the setting requirements are for the entities to be classified as critical or normal entities. The first kind of entity refers to an entity whose key index meets the setting requirement, and the second kind of entity refers to an entity whose key index does not meet the setting requirement. Taking the user operation event entity as an example, the key index may be an entity whose operation rate (e.g., click rate) is greater than a threshold.

By setting a threshold of key entities, for example 5%. When the key index of an entity is greater than the threshold, then the entity may be considered a key entity, i.e., an entity of the first type. When the key index of an entity is less than this threshold, then the entity may be considered a normal entity, i.e., a second class of entities. The threshold may be adjusted empirically.

S508, determining paths pointing to nodes corresponding to the entities of the first type in the first topological graph.

S510, according to the first type entity corresponding to the head node and the second type entity corresponding to the tail node of each path and the association relation between the entities, associating the first type entity corresponding to the head node and the second type entity corresponding to the tail node, and obtaining the association relation between the first type entities.

The first topological graph shows the association relation among all the entities, including the association relation between the first type of entities and the second type of entities. In such a relationship, since there are many entities, the relationship is clear, but there is no hierarchy, and the emphasis is not highlighted. In this embodiment, a part of the second topology map is abstracted on the basis of the first topology map.

Specifically, on the basis of the first topological graph, a first type of entity with a key index larger than a threshold value and a second type of entity with a key index smaller than the threshold value and relatively unimportant are determined. According to the first class of entities, a path is determined. And removing the second type entity on each path to obtain the association relation between the first type entities on the path.

S512, obtaining a second topological graph according to the association relation among the first type entities.

And if the first type entity corresponding to the head node and the second type entity corresponding to the tail combination of the path connection are the same after the second type entity is removed from the plurality of paths, aggregating the plurality of paths into a topological graph.

And S514, storing the paths and the second topological graph correspondingly.

By means of the method, the global outline can be intuitively understood by showing the association relationship among the global entities through the first topological graph, the paths are aggregated through the second topological graph on the basis of the first topological graph, the association relationship among the entities with the key indexes larger than the threshold value is shown, the data flow direction among the key high-frequency entities is known by a demander, and the readability of the key information is ensured.

For example, in one user behavior analysis, a first topology graph shows the timing of operations for all advertisements. Among these operational behaviors are operations for advertisements whose click-through rates exceed a threshold and for advertisements whose click-through rates are less than a threshold. By presenting the association between the individual operational events through a first topology.

In the first topological graph, a second type of entity with the click rate smaller than a threshold value and a first type of entity with the click rate larger than the threshold value are included. And eliminating each second type entity in the path by marking the first type entity and the path pointing to the first type entity to obtain a second topological graph. In the case where the head-to-tail nodes of multiple paths are the same first class entity, multiple paths can be aggregated into one path.

In this way, all the association relations among all the entities are displayed first, so as to help the demander to know the global situation. By providing the second topological graph, a plurality of sub-paths can be aggregated into one path, so that a demander is helped to know the data flow direction between key high-frequency entities, and the readability of key information is ensured.

In one embodiment, the data processing method can be applied to any other network with a topological structure, such as a device network, and the nodes in the topological network structure can be bound with other data information, so that the data structuring and multidimensional analysis can be realized. For example, a network of devices in a machine room may be represented by a flow chart, each path being a connection between devices, and each node being a machine room device. In this process, each node is bound to the data information corresponding to the device, such as a CPU usage trend chart.

In one embodiment, the data processing method may be used for user behavior analysis products. The user behavior analysis product refers to a data mining and visual analysis product, in which the relationship between user operation behaviors needs to be displayed, and analysis of different dimensions is performed for any one operation behavior.

Specifically, obtaining the entity and the association relationship between the entities includes: acquiring a time sequence of operation event entity data; and determining the time sequence relation of each operation event entity according to the time sequence.

The operation event entity refers to an event triggered by a user performing related operations on an application program. For example, a click event triggered by a click operation of an advertisement of a display page of an application by a user, a close event triggered by a close operation of an advertisement, and the like. Each operational event entity has a timing relationship based on an operational time.

The operation event entity data, namely data generated by relevant operation of a user on an application program, comprises operation event content, operation time, operation position and the like. Taking an operation event entity as an advertisement click as an example, the operation event entity data includes a click event, a clicked advertisement position, an advertisement dispenser, advertisement content, a click time, a viewing time, and the like.

The time sequence is obtained by arranging the data according to the sequence of the occurrence time. The time sequence of the operation event entity data is obtained through the sequence of the operation time of the operation event entity data. The time sequence of the operation event entity data can be obtained by smoothly sorting and finishing the operation event entity data according to the operation time. When the terminal performs data reporting, the last operation event entity data and the current operation event entity data can be combined into a sequence for reporting. And obtaining a time sequence according to the precedence relationship of the two operation events in the sequence. The time sequence can record the time sequence relation of the operation event entities, namely the occurrence sequence of the operation, and the time sequence relation of each operation event entity is determined according to the time sequence.

Specifically, acquiring a time sequence of operational event entity data includes: acquiring a time sequence of user operation behavior data reported by a terminal; preprocessing user operation behavior data; and extracting the operation behavior of setting the operation content to obtain the time sequence of the operation event entity data.

The terminal in this embodiment is the reporting terminal of fig. 1, specifically, a terminal with an application program for analyzing the requirements installed. And the reporting terminal reports the user operation behavior data to the server after detecting the operation of the user on the application program. When reporting data, the reporting terminal combines the last operation event entity data and the current operation event entity data into a sequence for reporting. And obtaining a time sequence according to the precedence relationship of the two operation events in the sequence. In this embodiment, receiving the report data may be performed by the data report server 1301 shown in fig. 1.

In this embodiment, the mining server 1302 shown in fig. 1 may perform mining processing on user operation behavior data. Specifically, as shown in fig. 7, the mining process includes preprocessing.

Preprocessing of user operational behavior data includes data cleansing. The data cleaning method comprises the following steps: missing value processing, outlier processing, deduplication processing, noise data processing, and the like. The method of data cleaning may be implemented by a conventional method, which is not limited herein.

Preprocessing the user operation behavior data also comprises data parsing. Specifically, after the data is cleaned to remove dirty data such as repeated data, noise data, true data, abnormal value data, and the like, the structure of the user operation behavior data is analyzed, and data required to be analyzed including operation contents, operation time, operation positions, and the like is extracted therefrom.

Preprocessing of user operational behavior data also includes data format conversion. Specifically, the extracted data is converted in a format required for server processing.

The mining process also includes extracting operation behaviors of setting operation contents to obtain operation event entity data. The setting operation content can be set according to analysis requirements. Setting operation content as content related to advertisement operation, and eliminating content related to other page operation.

The mining process also includes clustering behavior patterns to obtain behavior patterns of different categories. The data processing mode of the method can analyze the behavior data of a certain user, and can analyze the behavior data of a class of users.

Specifically, due to the diversity of user operation behaviors, the user behavior data reported by the terminal is messy, and is directly used for the user behavior analysis, so that the readability is not high. Therefore, in specific application, the user operation behavior data can be clustered by adopting a clustering model, a neural network algorithm and the like, so that the user behavior data of various users under the same behavior mode can be obtained. By adopting the data processing method, the topological graph corresponding to the user row analysis result of each type of user is displayed in a classified manner.

The mining process also includes chart data processing. And processing the entity data in advance to obtain chart data. Specifically, as shown in fig. 8, the data processing method further includes:

s802: entity data is acquired.

Entity data is entity-related data capable of characterizing various items of information of an entity, including, but not limited to, entity names and entity association information. It will be appreciated that the entity data corresponding to different analysis objects is different. For the user behavior analysis platform, the entity is an operation event, that is, the user operates on the application platform, and the entity data includes, but is not limited to, operation event content, operation time, operation position and the like. Taking an operational event entity as an example of an advertisement click, entity data includes, but is not limited to, a click event, a clicked advertisement spot, an advertisement dispenser, advertisement content, click time and viewing time, and the like.

S804, according to the entity data, calculating analysis data corresponding to the set analysis dimension of each entity.

The analysis data corresponding to the analysis dimension is set for analyzing the entity from a plurality of dimensions, and may be, for example, a duty ratio of the click amount, the click amount in each time period, or the like. The result of analysis data is the source of chart data, and the analysis dimension and the calculation method of the corresponding analysis can be set according to the result required by the chart data to be displayed.

S806, according to the analysis data, chart data corresponding to each analysis dimension are obtained.

The chart data is the relevant analysis result intuitively displayed by a visual method such as a chart or a table. The chart data includes a line graph, a bar graph, a specific gravity graph, and the like. In particular embodiments, data may be analyzed from a plurality of different angles or dimensions, resulting in a multi-dimensional data graph of the data. Typically, a multi-dimensional data graph comprises a series of data graphs, with different data graphs representing data from different angles of analysis. For example, the click rate of multiple advertisements at the same time is compared, the click rate trend of the same advertisement in one day is analyzed, the click rate of one advertisement accounts for the click rate of all advertisements, and the like. In this embodiment, the server performs multidimensional analysis on related data of the entity in advance, and generates corresponding chart data by using a chart generation tool provided by the server.

S808, storing each graph data in association with the node corresponding to the entity.

The chart data is bound to the entity. When a chart data request sent by a terminal in response to the triggering operation of a user on a node is obtained, chart data corresponding to the node is sent to the terminal, and the chart of the associated data is ensured to be a multidimensional analysis result aiming at an operation event entity corresponding to the node.

As shown in fig. 9, in one embodiment, a data processing method is provided. The present embodiment is mainly exemplified by the application of the method to the query terminal 120 in fig. 1. Referring to fig. 9, the data processing method specifically includes the steps of:

s902, responding to a data request operation, and acquiring a first topological graph obtained based on the association relation between the entities from a server.

And the user performs data request operation on the query terminal to acquire a corresponding analysis result. The terminal responds to the data request operation and sends a data request to the server.

The data request is a request sent by the inquiring terminal 120 in response to the inquiring operation of the terminal.

The server processes entity data in advance, and a first topological graph is obtained based on the association relation between the entities. When the data request of the terminal is acquired, after verification is passed, the topological graph corresponding to the query content is fed back.

Specifically, the data request includes a user account and query content. The server 130 verifies the user's query authority according to the user account.

In one embodiment, a user analyzes, for example, user behavior data by purchasing a data analysis service at server 130. The user purchases the corresponding service to obtain the inquiry authority, and can inquire the corresponding result through logging in the user account to obtain the topological graph representing the time sequence relation of the operation behavior. In another embodiment, the administrator may also perform authority configuration on the user account with the management authority, where the user account with the management authority may be an administrator who manages the network device of the machine room. The manager has the authority to inquire the analysis result of the network equipment. And inquiring a corresponding result through logging in the user account number to obtain a topological graph representing the connection relation of the network equipment. An entity is a transaction or event that is independent and of practical significance. The entities corresponding to different analysis requirements are different. The entity in this embodiment is an analysis target of the data analysis tool, and the data analysis tool analyzes the entity and links the entities based on the association relationship between the entities to obtain the first topological graph. The topological graph is a network structure diagram formed by nodes and connecting lines between the nodes, and can clearly and intuitively represent the association relation between the entities through the topological graph. Wherein each node of the first topology is an entity.

S904, a first topology is shown.

A schematic of the first topology is shown in fig. 10.

S906, when the operation on the node of the first topological graph is acquired, acquiring the node.

S908, requesting graph data corresponding to the nodes from a server, wherein the graph data is obtained by analyzing the data of the entities corresponding to the nodes.

The server processes the data of the entity in advance to obtain corresponding chart data, and binds the chart data with the nodes corresponding to the entity.

The chart data is the relevant analysis result intuitively displayed by a visual method such as a chart or a table. The chart data includes a line graph, a bar graph, a specific gravity graph, and the like. In particular embodiments, data may be analyzed from a plurality of different angles or dimensions, resulting in a multi-dimensional data graph of the data. Typically, a multi-dimensional data graph comprises a series of data graphs, with different data graphs representing data from different angles of analysis. For example, the click rate of multiple advertisements at the same time is compared, the click rate trend of the same advertisement in one day is analyzed, the click rate of one advertisement accounts for the click rate of all advertisements, and the like. In this embodiment, the server performs multidimensional analysis on related data of the entity in advance, generates corresponding chart data by using a chart generation tool provided by the server, and binds the chart data with the entity. And when the chart data request sent by the terminal in response to the trigger operation of the user on the node is obtained, the corresponding chart data is sent to the terminal.

S910, receiving and displaying chart data.

The query terminal receives the chart data sent by the server and displays the chart data on a display interface of the query terminal. The user can intuitively understand the multidimensional analysis data of the entity through the chart data. When the node corresponding to the user operation A is clicked, the displayed chart data is shown in FIG. 11.

According to the data processing method, the topological graph is obtained according to the association relation between the entities, and each node of the topological graph is bound with the chart data. The association relation between the entities is represented by a topological graph, so that the association between the entities can be intuitively known, and the single entities are not isolated but connected. Through binding of the nodes and the chart data of the entity, when the nodes are triggered on the topological graph, the chart data obtained by analyzing the entity can be obtained, so that the analysis of the data becomes comprehensive and visual.

In another embodiment, the data processing method further comprises: when the operation of the path of the first topological graph is acquired, acquiring the path; and requesting a second topological graph corresponding to the path from the server, and receiving and displaying the second topological graph. The second topological graph is obtained through a first type entity corresponding to the path and an associated second type entity, the first type entity is an entity corresponding to a head node or a tail node of the path, and in the association relationship between the entities, the first type entity corresponding to the head node is associated to the first type entity corresponding to the tail node through each second type entity.

In a path of the topological graph, an entity corresponding to a head node or a tail node of the path is a first-class entity. In the association relation between the entities, a first type entity corresponding to the first node is associated to a first type entity corresponding to the second node through each second type entity. The second topological graph can be aggregation of multiple paths in the first topological graph, or refinement of one path in the first topological graph. In one embodiment, clicking on the link between user operation A and user operation B results in a second topology as shown in FIG. 12.

In one embodiment, the data processing method is applied to a user behavior analysis platform as an example. The user behavior analysis platform analyzes the user behavior data by collecting the user behavior data of the user in the application program and helps an operator of the application program to know the user behavior and the attribute. For the user behavior analysis platform, the entity is an operation event entity, namely, the operation of the user on the application program platform. As shown in fig. 13, the data processing method includes:

And the reporting terminal reports the user operation behavior data in time sequence. Specifically, after detecting the operation of the user on the application program, the reporting terminal reports the user operation behavior data to the server. When reporting data, the reporting terminal combines the last operation event entity data and the current operation event entity data into a sequence for reporting. And obtaining a time sequence according to the precedence relationship of the two operation events in the sequence.

The server preprocesses the user operation behavior data, extracts the operation behavior of the preprocessed set operation content, and obtains operation event entity data. Specifically, preprocessing includes data cleansing, data parsing, and data format conversion.

And the server determines the time sequence relation of each operation event entity according to the time sequence of the operation event entity data. Specifically, the setting operation content can be set according to the analysis requirements. Setting operation content as advertisement analysis by taking demand analysis as an example, setting operation content as content related to advertisement operation, eliminating content related to other page operation, and ensuring data accuracy.

The server processes the operation event entities, extracts first-class operation event entities with the operation rate meeting the setting requirement from the operation event entities, and obtains a first topological graph based on the association relation of the first-class operation event entities. Specifically, the operation rate refers to the proportion of triggers of the operation event entities to triggers of all operation event entities of interest for the demand analysis. For example, the operation rate for advertisement A is the click-through rate for advertisement A. A threshold value is set that distinguishes between key entities, for example 5%. When the operation rate of an operation event entity is greater than the threshold, the operation event entity may be considered a key operation event, i.e., a first type of operation event entity. And sequentially searching the operation event entities according to the sequence of the operation corresponding to the first type of operation event entities to form a first topological graph.

The server determines paths pointing to nodes corresponding to all first-class operation event entities in the first topological graph and connecting lines forming the paths, and according to the first-class operation event entities corresponding to the first nodes of the paths, the first operation event entities corresponding to the tail nodes and the second-class entities of the first operation event entities corresponding to the first nodes and the second operation event entities corresponding to the tail nodes in the association relation among the entities, a second topological graph is obtained, and the connecting lines, the paths and the second topological graph are correspondingly stored.

Specifically, a second topological graph is obtained according to the first type entity corresponding to the path and the associated second type entity, and the second topological graph is bound with the path. When the path is triggered by the querying terminal, the second topology map is requested to the server. The second topological graph can show the time sequence flow direction of the operation behaviors with the click rate smaller than the threshold value from the operation behaviors with the click rate larger than the threshold value corresponding to the head node to the operation behaviors with the click rate larger than the threshold value corresponding to the tail node. The first topological graph is an abstract aggregated association relationship graph, and by clicking a certain path of the first topological graph, sub-path association relationships comprising second class entity details on the association relationship represented by the path can be obtained.

The server calculates set analysis data of each operation entity data according to the operation entity data, obtains corresponding chart data according to the analysis data, and stores the chart data corresponding to nodes corresponding to the operation event entities. Specifically, chart data is bound to an entity. When a chart data request sent by a terminal in response to the triggering operation of a user on a node is obtained, chart data corresponding to the node is sent to the terminal, and the chart of the associated data is ensured to be a multidimensional analysis result aiming at an operation event entity corresponding to the node.

And the query terminal responds to the data request operation and sends a data request to the server. Specifically, the user performs a data request operation on the query terminal to obtain a corresponding analysis result. The terminal responds to the data request operation and sends a data request to the server.

The server responds to the data request of the inquiring terminal, inquires a first topological graph obtained based on the time sequence relation between the operation entities, and sends the first topological graph to the inquiring terminal.

The query terminal receives and displays the first topological graph. The query terminal receives the first topological graph sent by the server and displays the first topological graph on a display interface of the query terminal, as shown in fig. 10. Through the first topological graph, a user can intuitively know the association relationship among the entities.

The query terminal responds to the operation of the nodes of the first topological graph, acquires the nodes, and requests graph data corresponding to the nodes from the server.

And the server inquires the chart data obtained by analyzing the data based on the entity corresponding to the node according to the node, and sends the chart data to the inquiring terminal. In this embodiment, the server performs multidimensional analysis on related data of the entity in advance, generates corresponding chart data by using a chart generation tool provided by the server, and binds the chart data with the entity. And when the chart data request sent by the terminal in response to the trigger operation of the user on the node is obtained, the corresponding chart data is sent to the terminal.

The query terminal receives and displays the chart data. Specifically, the query terminal receives the chart data sent by the server and displays the chart data on a display interface of the query terminal. That is, when a user clicks on any node in the flow chart, since the node is already bound to the user's behavior event, when the user clicks on the node, a multi-dimensional analysis data graph for the corresponding user behavior event will be displayed, as shown in fig. 11. By the method, a user can clearly know the corresponding relation between the data chart and the user behavior event, and the data analysis charts with different dimensions corresponding to the same event are ensured to be in a reading space, so that confusion and conflict between charts are avoided.

And responding to the operation of the path of the first topological graph by the query terminal, acquiring the path, and requesting a second topological graph corresponding to the topological graph from the server.

And the server inquires a second topological graph associated with the path according to the path and sends the second topological graph to the terminal. The server processes the data related to the entity in advance, binds the path and refines the second topological graph of the display of the path. And when the query request is obtained when the terminal responds to the path generated by the triggering operation of the user on the path, the corresponding second topological graph is sent to the terminal.

The query terminal receives and displays the second topological graph. In this embodiment, by associating the second topology map with the path, the path of the first topology can be further aggregated or refined on the basis of the displayed first topology map, so that it is convenient to deeply analyze the entity details and increase the information amount of path analysis. When a user clicks a certain sub-stream in the flow chart, the stream is automatically unfolded to generate a more detailed flow chart, so that the user can search the details of the sub-stream more deeply.

The user may click on any sub-path in the flow chart. For example, when the user clicks on the sub-path between "user operation a" and "user operation B", the sub-path will be expanded, and the expanded detailed stream data thereof will be displayed as shown in fig. 13.

Of course, when the user clicks on any other sub-path, the expanded flow data will be displayed, and the user is provided with the capability of deep mining and analyzing the flow direction of any sub-path. According to the data processing method, a standard for binding an operation event entity and a multidimensional visual chart based on a topological graph is established, and through connecting incidence relations among the event, the behavior flow and the multidimensional visual chart by using the topological graph, deep analysis and multidimensional analysis of data by a user are supported.

As shown in fig. 14, a data processing apparatus includes:

and a query module 1402, configured to query a first topology map obtained based on an association relationship between entities in response to a data request of the terminal.

A sending module 1404, configured to send the first topology map to a terminal.

The query module 1402 is further configured to query graph data obtained by analyzing data based on an entity corresponding to the node when a graph data request sent by the terminal in response to an operation of the node of the first topology graph is obtained.

The sending module 1404 is further configured to send the chart data to the terminal.

In another embodiment, the query module 1402 is further configured to query, when a path query request sent by the terminal in response to an operation of a path of the first topology map is obtained, a second topology map associated with the path, where the second topology map is obtained by a first type entity corresponding to the path and an associated second type entity, the first type entity is an entity corresponding to a head node or a tail node of the path, and in an association relationship between the entities, the first type entity corresponding to the head node is associated to the first type entity corresponding to the tail node through each second type entity.

And the sending module is also used for sending the second topological graph to the terminal.

In another embodiment, the data processing apparatus further comprises:

the relationship acquisition module is used for acquiring the entity and the association relationship between the entities.

The extraction module is used for extracting first-class entities of which the key indexes meet the set requirements.

The topological graph processing module is used for obtaining a first topological graph based on the association relation between the first type of entities.

In another embodiment, the data processing apparatus further comprises:

a path determining module for determining paths pointing to nodes corresponding to the first type entities in the first topological graph

The topology graph processing module is further configured to obtain a second topology graph according to the first type entity corresponding to the first node of the path, the first type entity corresponding to the tail node, and the second type entity associating the first type entity corresponding to the first node with the first type entity corresponding to the tail node in the association relationship between the entities.

And the storage module is used for correspondingly storing the path and the second topological graph.

In another embodiment, the data processing apparatus further comprises:

the entity acquisition module is used for acquiring the entity and the association relation between the entities.

The topology processing module is used for obtaining a first topology graph based on the association relation between the entities.

In another embodiment, the data processing module further comprises:

the entity processing module is used for extracting a first entity with the key index meeting the setting requirement and a second entity without meeting the setting requirement.

And the path module is used for determining paths pointing to nodes corresponding to the first type entities in the first topological graph.

The topology processing module is further configured to obtain an association relationship between the first type entities according to the first type entities corresponding to the head node and the tail node of each path, and in the association relationship between the entities, associate the first type entities corresponding to the head node with the second type entities corresponding to the tail node, and obtain a second topology according to the association relationship between the first type entities.

Specifically, the relationship acquiring module or the entity acquiring module is configured to acquire a time sequence of the operation event entity data, and determine a time sequence relationship of each operation event entity according to the time sequence.

Specifically, a time sequence of user operation behavior data reported by a terminal is obtained, the user operation behavior data is preprocessed, operation behaviors of set operation content are extracted, and a time sequence of operation event entity data is obtained.

In another embodiment, the system further comprises a chart data acquisition module, which is used for acquiring entity data and calculating analysis data corresponding to the set analysis dimension of each entity according to the entity data; and obtaining chart data corresponding to each analysis dimension according to the analysis data. And the storage module is also used for correspondingly storing the chart data and the nodes corresponding to the entities.

As shown in fig. 15, a data processing apparatus includes:

the topology map acquisition module 1502 is configured to acquire, from a server, a first topology map obtained based on an association relationship between entities in response to a data request operation.

A display module 1504 is configured to display the first topology map.

The node obtaining module 1506 is configured to obtain the node when obtaining the operation on the node of the first topology map.

The graph request module 1508 is configured to request graph data corresponding to the node from the server, where the graph data is obtained by analyzing the data of the entity corresponding to the node.

The display module 1504 is further configured to receive and display chart data.

In yet another embodiment, the data processing apparatus further comprises a path acquisition module for acquiring a path when an operation on the path of the first topology is acquired.

The topology map obtaining module 1502 requests, from the server, a second topology map corresponding to the path, where the second topology map is obtained by a first type entity corresponding to the path and an associated second type entity, the first type entity is an entity corresponding to a first node or a tail node of the path, and in an association relationship between the entities, the first type entity corresponding to the first node is associated to the first type entity corresponding to the tail node through each second type entity.

The display module 1504 is further configured to receive and display the second topology map.

It should be understood that each step in the above-described flowcharts is shown in order as indicated by the arrow, but the steps are not necessarily performed in order as indicated by the arrow. The steps are not strictly limited to the order of execution unless explicitly recited herein, and the steps may be executed in other orders. Moreover, at least some of the steps in the flowcharts described above may include a plurality of sub-steps or a plurality of stages, which are not necessarily performed at the same time, but may be performed at different times, and the order of execution of the sub-steps or stages is not necessarily sequential, but may be performed alternately or alternately with at least a part of the sub-steps or stages of other steps or other steps.

FIG. 16 illustrates an internal block diagram of a computer device in one embodiment. The computer device may be in particular the terminal 120 (or the server 130) in fig. 1. As shown in fig. 16, the computer device includes a processor, a memory, a network interface, an input device, and a display screen connected by a system bus. The memory includes a nonvolatile storage medium and an internal memory. The non-volatile storage medium of the computer device stores an operating system, and may also store a computer program which, when executed by a processor, causes the processor to implement a data processing method. The internal memory may also store a computer program which, when executed by the processor, causes the processor to perform the data processing method. The display screen of the computer equipment can be a liquid crystal display screen or an electronic ink display screen, the input device of the computer equipment can be a touch layer covered on the display screen, can also be keys, a track ball or a touch pad arranged on the shell of the computer equipment, and can also be an external keyboard, a touch pad or a mouse and the like.

It will be appreciated by those skilled in the art that the structure shown in fig. 16 is merely a block diagram of a portion of the structure associated with the present application and is not limiting of the computer device to which the present application is applied, and that a particular computer device may include more or fewer components than shown, or may combine certain components, or have a different arrangement of components.

In one embodiment, the data processing apparatus provided herein may be implemented in the form of a computer program that is executable on a computer device as shown in fig. 16. The memory of the computer device may store various program modules constituting the data processing apparatus, such as the query module and the transmission module shown in fig. 14. The computer program constituted by the respective program modules causes the processor to execute the steps in the data processing method of the respective embodiments of the present application described in the present specification.

For example, the computer device shown in fig. 16 may execute the step of querying the first topology map obtained based on the association relationship between the entities by the query module in the data processing apparatus shown in fig. 14, in response to the data request of the terminal. The computer device may perform the step of transmitting the first topology map to the terminal through the transmission module.

A computer readable storage medium storing a computer program which, when executed by a processor, causes the processor to perform:

sending a first topological graph to a terminal;

inquiring graph data obtained by analyzing the data based on the entity corresponding to the node when the graph data request sent by the terminal in response to the operation of the node of the first topological graph is obtained;

And sending the chart data to the terminal.

In another embodiment, a computer program, when executed by a processor, causes the processor to perform:

when a path query request sent by a terminal in response to the operation of the path of the first topological graph is obtained, querying a second topological graph associated with the path, wherein the second topological graph is obtained through a first type entity corresponding to the path and an associated second type entity, the first type entity is an entity corresponding to a head node or a tail node of the path, and in the association relationship among the entities, the first type entity corresponding to the head node is associated to the first type entity corresponding to the tail node through each second type entity;

and sending the second topological graph to the terminal.

In another embodiment, the determining of the first topology map includes:

acquiring an association relation between entities;

extracting a first entity of which the key index meets the set requirement;

and obtaining a first topological graph based on the association relation between the first type of entities.

In another embodiment, the determining of the second topology comprises:

determining paths pointing to nodes corresponding to the first type entities in the first topological graph;

according to the first type entity corresponding to the head node of the path, the first type entity corresponding to the tail node of the path and the second type entity of the first type entity corresponding to the head node and the second type entity of the first type entity corresponding to the tail node in the association relation between the entities, a second topological graph is obtained;

And correspondingly storing the paths and the second topological graph.

In another embodiment, the determining of the first topology map includes:

acquiring an association relation between entities;

and obtaining a first topological graph based on the association relation between the entities.

In another embodiment, the determining of the second topology comprises:

extracting a first type entity of which the key index meets the setting requirement and a second type entity of which the key index does not meet the setting requirement;

according to the first type entity corresponding to the head node and the first type entity corresponding to the tail node of each path and the association relation between the entities, associating the first type entity corresponding to the head node and the second type entity corresponding to the tail node to obtain the association relation between the first type entities;

obtaining a second topological graph according to the association relation among the first type entities;

and correspondingly storing the paths and the second topological graph.

In another embodiment, obtaining the entity and the association relationship between the entities includes:

acquiring a time sequence of operation event entity data;

and determining the time sequence relation of each operation event entity according to the time sequence.

In another embodiment, obtaining a time sequence of operational event entity data includes:

acquiring a time sequence of user operation behavior data reported by a terminal;

preprocessing user operation behavior data;

and extracting the operation behavior of setting the operation content to obtain the time sequence of the operation event entity data.

In another embodiment, the determining of the chart data includes:

acquiring entity data;

according to the entity data, calculating analysis data corresponding to the set analysis dimension of each entity;

obtaining chart data corresponding to each analysis dimension according to the analysis data;

and storing the chart data corresponding to the nodes corresponding to the entities.

showing a first topology;

when the operation of the nodes of the first topological graph is obtained, the nodes are obtained;

Chart data is received and presented.

when the operation of the path of the first topological graph is acquired, acquiring the path;

requesting a second topological graph corresponding to the path from a server, wherein the second topological graph is obtained through a first type entity corresponding to the path and an associated second type entity, the first type entity is an entity corresponding to a head node or a tail node of the path, and in the association relationship between the entities, the first type entity corresponding to the head node is associated to the first type entity corresponding to the tail node through each second type entity;

a second topology map is received and shown.

A computer device comprising a memory and a processor, the memory storing a computer program which, when executed by the processor, causes the processor to perform:

sending a first topological graph to a terminal;

And sending the chart data to the terminal.

and sending the second topological graph to the terminal.

In another embodiment, the determining of the first topology map includes:

acquiring an association relation between entities;

extracting a first entity of which the key index meets the set requirement;

In another embodiment, the determining of the second topology comprises:

And correspondingly storing the paths and the second topological graph.

In another embodiment, the determining of the first topology map includes:

acquiring an association relation between entities;

In another embodiment, the determining of the second topology comprises:

and correspondingly storing the paths and the second topological graph.

acquiring a time sequence of operation event entity data;

preprocessing user operation behavior data;

In another embodiment, the determining of the chart data includes:

acquiring entity data;

and storing each chart data corresponding to the node corresponding to the entity.

A computer device comprising a memory and a processor, the memory storing a computer program which, when executed by the processor, causes the processor to perform

showing a first topology;

Chart data is received and presented.

a second topology map is received and shown.

Those skilled in the art will appreciate that all or part of the processes in the methods of the above embodiments may be implemented by a computer program for instructing relevant hardware, where the program may be stored in a non-volatile computer readable storage medium, and where the program, when executed, may include processes in the embodiments of the methods described above. Any reference to memory, storage, database, or other medium used in the various embodiments provided herein may include non-volatile and/or volatile memory. The nonvolatile memory can include Read Only Memory (ROM), programmable ROM (PROM), electrically Programmable ROM (EPROM), electrically Erasable Programmable ROM (EEPROM), or flash memory. Volatile memory can include Random Access Memory (RAM) or external cache memory. By way of illustration and not limitation, RAM is available in a variety of forms such as Static RAM (SRAM), dynamic RAM (DRAM), synchronous DRAM (SDRAM), double Data Rate SDRAM (DDRSDRAM), enhanced SDRAM (ESDRAM), synchronous Link DRAM (SLDRAM), memory bus direct RAM (RDRAM), direct memory bus dynamic RAM (DRDRAM), and memory bus dynamic RAM (RDRAM), among others.

The technical features of the above embodiments may be arbitrarily combined, and all possible combinations of the technical features in the above embodiments are not described for brevity of description, however, as long as there is no contradiction between the combinations of the technical features, they should be considered as the scope of the description.

The above examples only represent a few embodiments of the present application, which are described in more detail and are not to be construed as limiting the scope of the present application. It should be noted that it would be apparent to those skilled in the art that various modifications and improvements could be made without departing from the spirit of the present application, which would be within the scope of the present application. Accordingly, the scope of protection of the present application is to be determined by the claims appended hereto.

Claims

1. A data processing method, comprising:

sending the first topological graph to the terminal;

Sending the chart data to the terminal;

when a path query request sent by a terminal in response to a path operation of the first topological graph is obtained, querying a second topological graph associated with the path, wherein the second topological graph is obtained through a first type entity corresponding to the path and an associated second type entity, the first type entity is an entity corresponding to a head node or a tail node of the path, and in an association relationship between the entities, the first type entity corresponding to the head node is associated to the first type entity corresponding to the tail node through each second type entity;

and sending the second topological graph to the terminal.

2. The method of claim 1, wherein the determining of the first topology comprises:

acquiring an association relation between entities;

extracting a first type entity of which the key index meets the set requirement from the entities;

3. The method of claim 2, wherein the determining of the second topology map includes the method further comprising:

According to a first type entity corresponding to a head node of the path, a first type entity corresponding to a tail node of the path and a second type entity of the first type entity corresponding to the head node and the second type entity of the first type entity corresponding to the tail node in the association relation between the entities, a second topological graph is obtained;

and correspondingly storing the path and the second topological graph.

4. The method of claim 1, wherein the determining of the first topology comprises:

acquiring an association relation between entities;

5. The method of claim 4, wherein the determining of the second topology comprises:

extracting a first type entity of which the key index meets the set requirement from the entities; and a second class of entities that do not meet the set requirements;

Obtaining a second topological graph according to the association relation between the first type entities;

and correspondingly storing the path and the second topological graph.

6. The method according to claim 2 or 4, wherein the acquiring the association between the entity and the entity includes:

acquiring a time sequence of operation event entity data;

7. The method of claim 6, wherein the obtaining a time series of operational event entity data comprises:

preprocessing the user operation behavior data;

8. The method according to any one of claims 2 to 5, wherein the determining means of the chart data includes:

acquiring entity data;

9. A data processing method, comprising:

displaying the first topological graph;

receiving and displaying the chart data;

requesting a second topological graph corresponding to the path from a server, wherein the second topological graph is obtained through a first type entity corresponding to the path and an associated second type entity, the first type entity is an entity corresponding to a first node or a tail node of the path, and in the association relationship between the entities, the first type entity corresponding to the first node is associated to the first type entity corresponding to the tail node through each second type entity;

the second topology map is received and shown.

10. A data processing apparatus comprising:

A sending module, configured to send the first topology map to the terminal;

the sending module is further used for sending the chart data to the terminal;

the query module is further configured to query a second topology graph associated with the path when a path query request sent by the terminal in response to the operation on the path of the first topology graph is obtained, where the second topology graph is obtained through a first type entity corresponding to the path and an associated second type entity, the first type entity is an entity corresponding to a first node or a tail node of the path, and in an association relationship between the entities, the first type entity corresponding to the first node is associated to the first type entity corresponding to the tail node through each second type entity;

the sending module is further configured to send the second topology map to the terminal.

11. The apparatus of claim 10, wherein the data processing apparatus further comprises:

The relationship acquisition module is used for acquiring the entity and the association relationship between the entities;

the extraction module is used for extracting a first type entity of which the key index meets the set requirement;

12. The apparatus of claim 11, wherein the data processing apparatus further comprises:

the path determining module is used for determining paths which point to nodes corresponding to the first type entities in the first topological graph;

the topological graph processing module is further used for obtaining a second topological graph according to the first type entity corresponding to the first node of the path, the first type entity corresponding to the tail node and the second type entity of the first type entity corresponding to the first node and the second type entity corresponding to the tail node in the association relation between the entities;

13. The apparatus of claim 10, wherein the data processing apparatus further comprises:

14. The apparatus of claim 13, wherein the data processing module further comprises:

the entity processing module is used for extracting a first type entity of which the key index meets the set requirement; and a second class of entities that do not meet the set requirements;

the path module is used for determining paths which point to nodes corresponding to the first type entities in the first topological graph;

the topology processing module is further used for obtaining the association relation between the first type entities according to the first type entities corresponding to the head nodes and the first type entities corresponding to the tail nodes of the paths and the second type entities of the first type entities corresponding to the head nodes and the tail nodes in the association relation between the entities; obtaining a second topological graph according to the association relation between the first type entities; and correspondingly storing the path and the second topological graph.

15. The apparatus according to claim 11 or 13, wherein the relationship obtaining module is configured to obtain a time sequence of the operation event entity data, and determine a time sequence relationship of each operation event entity according to the time sequence.

16. The apparatus of claim 15, wherein the relationship obtaining module is configured to obtain a time sequence of user operation behavior data reported by the terminal; preprocessing the user operation behavior data; and extracting the operation behavior of setting the operation content to obtain the time sequence of the operation event entity data.

17. The apparatus according to any one of claims 11 to 14, further comprising a chart data acquisition module for acquiring entity data; according to the entity data, calculating analysis data corresponding to the set analysis dimension of each entity; obtaining chart data corresponding to each analysis dimension according to the analysis data; and storing each chart data corresponding to the node corresponding to the entity.

18. A data processing apparatus comprising:

the display module is used for displaying the first topological graph;

The display module is also used for receiving and displaying the chart data;

a path acquisition module, configured to acquire a path when an operation on the path of the first topology map is acquired;

the topology graph acquisition module is used for requesting a second topology graph corresponding to the path from a server, wherein the second topology graph is obtained through a first type entity corresponding to the path and an associated second type entity, the first type entity is an entity corresponding to a head node or a tail node of the path, and in the association relationship between the entities, the first type entity corresponding to the head node is associated to the first type entity corresponding to the tail node through each second type entity;

and the display module is also used for receiving and displaying the second topological graph.

19. A computer readable storage medium storing a computer program which, when executed by a processor, causes the processor to perform the steps of the method of any one of claims 1 to 9.

20. A computer device comprising a memory and a processor, the memory storing a computer program that, when executed by the processor, causes the processor to perform the steps of the method of any of claims 1 to 9.