Node display method and related equipment

Abstract

The embodiment of the invention provides a node display method and related equipment. The node display method comprises the following steps: monitoring the number of nodes under each branch in a node graph; if the number of the nodes under the branches exceeds the aggregation number, aggregating the nodes under the branches to form aggregated nodes; and in response to an operation of a user on the node graph, displaying a target node in the aggregated nodes. According to the technical scheme, the number of the nodes under each branch in the node graph is monitored, and when the number of the nodes under one branch exceeds the aggregation number, the nodes under the branch are aggregated to form a large aggregation node, so that the number of the nodes is reduced. And then, after the user operates the node graph, the target node is determined, and the target node is displayed at the downstream of the aggregation node, so that the target node which is not a noisy point is displayed for the user on the basis of reducing the noisy point, the user can more intuitively determine the node which the user needs to use, and the user can conveniently carry out data analysis.

Description

Technical Field

[0001] This application relates to the fields of computer and communication technology, and more specifically, to a node display method and related equipment. Background Technology

[0002] Currently, relationship analysis is typically performed by constructing a node analysis graph. However, existing node analysis graphs often have too many layers, resulting in small nodes that cannot display detailed content when showing the overall picture. Furthermore, many of these nodes are noisy, negatively impacting detailed analysis.

[0003] The above content is only used to help understand the technical solution of the present invention and does not represent an admission that the above content is prior art. Summary of the Invention

[0004] The embodiments of this application provide a node display method and related equipment, which can at least to some extent overcome the problem of excessive nodes affecting detailed analysis in the prior art.

[0005] Other features and advantages of this application will become apparent from the following detailed description, or may be learned in part from practice of this application.

[0006] According to one aspect of the embodiments of this application, a node display method is provided, comprising: monitoring the number of nodes under each branch in a node graph; if the number of nodes under the branch exceeds the aggregation number, aggregating the nodes under the branch to form an aggregate node; and displaying a target node in the aggregate node in response to a user's operation on the node graph.

[0007] In some specific embodiments of this application, the step of displaying the target node in the aggregated node in response to the user's operation on the node graph specifically includes: in response to the user's trigger operation on the aggregated node, generating a node display area in the node graph, wherein the node display area displays each node corresponding to the aggregated node; in response to the user's selection of a node in the node display area, determining the target node; and displaying the target node.

[0008] In some specific embodiments of this application, the step of displaying the target node in the aggregated nodes in response to a user's operation on the node graph specifically includes: determining the target node in response to a user's operation on any node in the node graph; and displaying the target node in the node graph.

[0009] In some specific embodiments of this application, the step of determining the target node in response to a user's operation on any node in the node graph specifically includes: in response to a user's operation on any aggregate node in the node graph, obtaining the node information of all nodes in the aggregate node; and determining the target node based on the node information of each node in the aggregate node.

[0010] In some specific embodiments of this application, determining the target node based on the node information of each node in the aggregated node specifically includes: obtaining the node information of the node preceding the user's operation; pairing the node information of each node in the aggregated node with the node information of the preceding node to form corresponding node information pairs; and inputting each node information pair into a node filtering model to obtain the target node.

[0011] In some specific embodiments of this application, the step of determining the target node in response to a user's operation on any node in the node graph specifically includes: in response to a user's operation on any node in the node graph, determining related nodes, wherein the related nodes are nodes associated with the current node, and the current node is the node operated by the user; and filtering out the target node from the related nodes.

[0012] In some specific embodiments of this application, the step of determining relevant nodes in response to a user's operation on any node in the node graph specifically includes: in response to a user's operation on any node in the node graph, obtaining user operation history data; determining the adjacent nodes of the current node based on the user operation history data, wherein the adjacent nodes are nodes that are adjacent to the current node in the operation sequence; and determining the adjacent nodes of the current node as relevant nodes.

[0013] In some specific embodiments of this application, determining the adjacent nodes of the current node based on the user operation history data specifically includes: sorting the nodes according to the time sequence of user operations based on the user operation history data to obtain the node time sequence; and determining the adjacent nodes of the current node based on the node time sequence.

[0014] In some specific embodiments of this application, the step of filtering out target nodes from the relevant nodes specifically includes: comparing the node information of the current node and the relevant nodes to determine the target probability of each relevant node, wherein the target probability is the probability that the user selects the next node to operate on; and determining the target node based on the target probability.

[0015] In some specific embodiments of this application, the step of comparing the node information of the current node and the related nodes to determine the target probability of each related node specifically includes: comparing the node information of the current node and the related nodes to determine the similarity between each related node and the current node; determining the switching frequency of the current node and each related node based on user operation history data; and determining the target probability based on the switching frequency and the similarity.

[0016] According to one aspect of the embodiments of this application, a node display device is provided, the node display device comprising: a quantity monitoring module, configured to monitor the number of nodes under each branch in a node graph; a node aggregation module, configured to aggregate the nodes under the branch to form an aggregate node if the number of nodes under the branch exceeds the aggregation quantity; and a node display module, configured to display a target node in the aggregate node in response to a user's operation on the node graph.

[0017] In some specific embodiments of this application, the node display module specifically includes: a region generation submodule, used to generate a node display area in the node graph in response to a user's trigger operation on the aggregated node, wherein each node corresponding to the aggregated node is displayed in the node display area; a target node submodule, used to determine a target node in response to a user's selection of a node in the node display area; and a node display submodule, used to display the target node in the node graph.

[0018] In some specific embodiments of this application, the node display module specifically includes:

[0019] The node determination submodule is used to determine the target node in response to a user's operation on any node in the node graph; the node display submodule is used to display the target node in the node graph.

[0020] In some specific embodiments of this application, the node determination submodule specifically includes: a node information acquisition unit, used to acquire node information of all nodes in the aggregate node in response to a user's operation on any aggregate node in the node graph; and a target node determination unit, used to determine a target node based on the node information of each node in the aggregate node.

[0021] In some specific embodiments of this application, the target node determination unit is specifically used to perform the following steps: obtaining the node information of the previous node operated by the user; pairing the node information of each node in the aggregated node with the node information of the previous node to form corresponding node information pairs; and inputting each of the node information pairs into the node filtering model to obtain the target node.

[0022] In some specific embodiments of this application, the node determination submodule specifically includes: a related node determination unit, used to determine related nodes in response to user operation on any node in the node graph, wherein the related nodes are nodes related to the current node, and the current node is the node operated by the user; and a target node filtering unit, used to filter out target nodes from the related nodes.

[0023] In some specific embodiments of this application, the relevant node determination unit specifically includes: a historical data acquisition subunit, used to acquire user operation history data in response to user operation on any node in the node graph; an adjacent node determination subunit, used to determine the adjacent nodes of the current node based on the user operation history data, wherein the adjacent nodes are nodes that are adjacent to the current node in the operation sequence; and a key node determination subunit, used to determine the adjacent nodes of the current node as relevant nodes.

[0024] In some specific embodiments of this application, the adjacent node determination subunit is specifically used to perform the following steps: sorting the nodes according to the time order of the user operation based on the user operation history data to obtain the node time sequence; and determining the adjacent nodes of the current node based on the node time sequence.

[0025] In some specific embodiments of this application, the target node filtering unit specifically includes: a node information comparison subunit, used to compare the node information of the current node and the related nodes to determine the target probability of each related node, wherein the target probability is the probability that the node is selected by the user as the next node to be operated; and a target node determination subunit, used to determine the target node based on the target probability.

[0026] In some specific embodiments of this application, the node information comparison subunit is specifically used to perform the following steps: comparing the node information of the current node and the related nodes to determine the similarity between each related node and the current node; determining the switching frequency of the current node and each of the related nodes based on user operation history data; and determining the target probability based on the switching frequency and the similarity.

[0027] According to one aspect of the embodiments of this application, a computer-readable medium is provided having a computer program stored thereon, which, when executed by a processor, implements the node display method as described in the above embodiments.

[0028] According to one aspect of the embodiments of this application, an electronic device is provided, including: one or more processors; and a storage device for storing one or more programs, which, when executed by the one or more processors, cause the one or more processors to implement the node display method as described in the above embodiments.

[0029] According to one aspect of the embodiments of this application, a computer program product is provided, including a computer program, characterized in that, when the computer program is executed by a processor, it implements the node display method as described in the above embodiments.

[0030] In some embodiments of this application, the technical solutions provide that by monitoring the number of nodes under each branch in the node graph, when the number of nodes under a branch exceeds the aggregation limit (i.e., when the number of nodes under that branch is excessive), the nodes under that branch are aggregated to form a large aggregate node. This reduces the number of nodes, thus reducing noise. Simultaneously, the number of displayed nodes remains within a certain range, ensuring that the nodes are not too small when displaying the entire node graph. Then, when the user interacts with the node graph, the system determines the target node to be displayed based on the user's actions and the nodes involved. This target node is then displayed downstream of the aggregate node, thus reducing noise while simultaneously showing the user a non-noise target node. This allows the user to more intuitively identify the nodes they need, facilitating data analysis.

[0031] It should be understood that the above general description and the following detailed description are exemplary and explanatory only, and do not limit this application. Attached Figure Description

[0032] The accompanying drawings, which are incorporated in and form part of this specification, illustrate embodiments consistent with this application and, together with the description, serve to explain the principles of this application. It is obvious that the drawings described below are merely some embodiments of this application, and those skilled in the art can obtain other drawings based on these drawings without any inventive effort. In the drawings:

[0033] Figure 1 An exemplary implementation environment diagram is shown, in which the technical solutions of the embodiments of this application can be applied.

[0034] Figure 2 A flowchart illustrating a node display method provided in an embodiment of this application is shown.

[0035] Figure 3 This illustration shows a node diagram provided in an embodiment of this application.

[0036] Figure 4 It shows that according to Figure 2 A flowchart illustrating a specific implementation of step S300 in the node display method shown in the corresponding embodiment.

[0037] Figure 5 It shows that according to Figure 4A flowchart illustrating a specific implementation of step S310 in the node display method shown in the corresponding embodiment.

[0038] Figure 6 It shows that according to Figure 4 A flowchart illustrating a specific implementation of step S310 in the node display method shown in the corresponding embodiment.

[0039] Figure 7 A schematic diagram of the structure of a node display device provided in an embodiment of this application is shown.

[0040] Figure 8 A schematic diagram of the structure of a computer system for an electronic device provided in an embodiment of this application is shown. Detailed Implementation

[0041] Exemplary embodiments will now be described more fully with reference to the accompanying drawings. However, these exemplary embodiments can be implemented in many forms and should not be construed as limited to the examples set forth herein; rather, these embodiments are provided to make this application more comprehensive and complete, and to fully convey the concept of the exemplary embodiments to those skilled in the art.

[0042] Furthermore, the described features, structures, or characteristics can be combined in any suitable manner in one or more embodiments. Numerous specific details are provided in the following description to give a thorough understanding of embodiments of this application. However, those skilled in the art will recognize that the technical solutions of this application can be practiced without one or more of the specific details, or other methods, components, apparatuses, steps, etc., can be employed. In other instances, well-known methods, apparatuses, implementations, or operations are not shown or described in detail to avoid obscuring various aspects of this application.

[0043] The block diagrams shown in the accompanying drawings are merely functional entities and do not necessarily correspond to physically independent entities. That is, these functional entities can be implemented in software, in one or more hardware modules or integrated circuits, or in different network and / or processor devices and / or microcontroller devices.

[0044] The flowcharts shown in the accompanying drawings are merely illustrative and do not necessarily include all content and operations / steps, nor do they necessarily have to be performed in the described order. For example, some operations / steps can be broken down, while others can be combined or partially combined; therefore, the actual execution order may change depending on the specific circumstances.

[0045] Figure 1 A schematic diagram of an exemplary system architecture to which the technical solutions of the embodiments of this application can be applied is shown.

[0046] like Figure 1As shown, the system architecture may include terminal devices (such as...) Figure 1 The device shown includes one or more of a smartphone 101, tablet 102, and portable computer 103 (which could also be a desktop computer, etc.), a network 104, and a server 105. The network 104 serves as a medium for providing a communication link between the terminal device and the server 105. The network 104 can include various connection types, such as wired communication links, wireless communication links, etc.

[0047] It should be understood that Figure 1 The number of terminal devices, networks, and servers shown is merely illustrative. Depending on implementation needs, there can be any number of terminal devices, networks, and servers. For example, server 105 could be a server cluster composed of multiple servers.

[0048] Users can interact with server 105 via network 104 using terminal devices to receive or send messages, etc. Server 105 can be a server that provides various services. For example, a user can upload the number of nodes under each branch in a node graph to server 105 using terminal device 103 (or terminal device 101 or 102). When the number of nodes under a branch exceeds the aggregation limit, server 105 can aggregate the nodes under the branch to form an aggregate node; in response to the user's operation on the node graph, it can display the target node in the aggregate node.

[0049] It should be noted that the node display method provided in this application embodiment is generally executed by server 105, and correspondingly, the node display device is generally disposed in server 105. However, in other embodiments of this application, the terminal device may also have similar functions to the server, thereby executing the node display scheme provided in this application embodiment.

[0050] The implementation details of the technical solutions in the embodiments of this application are described in detail below:

[0051] Figure 2 A flowchart of a node display method according to an embodiment of this application is shown. This node display method can be executed by a server, which may be... Figure 1 The server shown.

[0052] Reference Figure 2 As shown, the method for displaying this node includes at least the following:

[0053] S100, monitors the number of nodes under each branch in the node graph.

[0054] S200, if the number of nodes under the branch exceeds the number of aggregations, the nodes under the branch are aggregated to form an aggregate node.

[0055] S300, in response to the user's operation on the node graph, displays the target node in the aggregated node.

[0056] In the embodiments of this application, by monitoring the number of nodes under each branch in the node graph, when the number of nodes under a branch exceeds the aggregation limit (i.e., when the number of nodes under that branch is excessive), the nodes under that branch are aggregated to form a large aggregate node. This reduces the number of nodes, thus reducing noise. Simultaneously, the number of displayed nodes remains within a certain range, ensuring that the nodes are not too small when displaying the entire node graph. Then, when the user interacts with the node graph, the target node to be displayed to the user is determined based on the user's actions and the interacted nodes. This target node is then displayed downstream of the aggregate node, thus reducing noise while simultaneously displaying the target node, which is not considered noise. This allows the user to more intuitively identify the nodes they need, facilitating data analysis.

[0057] In S100, a corresponding listening script can be placed in the terminal device to monitor the number of nodes under each branch in the node graph.

[0058] In some embodiments, the node graph may be multi-level, meaning that each first-level branch contains multiple second-level branches, and each second-level branch contains multiple third-level branches, and so on, nested until the final node. In this case, a branch can be considered a node, and the number of nodes being monitored can also include the number of branches.

[0059] That is, in a node graph, a first-level branch can be regarded as a first-level node, which contains multiple second-level branches; each second-level branch can be regarded as a second-level node, which contains multiple third-level branches; each third-level branch can be regarded as a third-level node, and so on, with the last node being the terminal node.

[0060] Therefore, the number of nodes under a branch is equal to the number of nodes in its next-level sub-branch, which is also the number of branches in its next-level sub-branch. In other words, the number of nodes under an n-level branch is equal to the number of nodes in its (n+1)-level sub-branch, which is also the number of branches in its (n+1)-level sub-branch. This is to retain as many nodes as possible in the node graph, so that users can intuitively obtain as complete node information as possible, reduce the number of operations on the node graph, and improve the user experience.

[0061] It should be noted that the first-level branch mentioned above refers to the branch that starts from the overall starting point of the node graph.

[0062] In other embodiments, the number of nodes under a branch can also be the number of nodes of the terminal nodes it contains, in order to minimize the number of nodes displayed, reduce noise interference, reduce the burden on the device, and speed up the loading of the node graph.

[0063] In S200, when the number of nodes under a branch exceeds the number of aggregations, it proves that there are too many nodes under that branch. At this time, it is necessary to aggregate the nodes under that branch into one node to reduce the number of nodes.

[0064] In S300, there are multiple ways to display target nodes. In some embodiments, the target node can be displayed at a fixed position in the node graph. In other real-time examples, it can also be displayed under its corresponding branch. When the user aggregates the branch, the node can continue to be displayed without being aggregated.

[0065] Specifically, in some embodiments, the specific implementation of step S300 can be found in the following embodiments. This embodiment is based on... Figure 2 According to the detailed description of step S300 in the node display method shown in the corresponding embodiment, step S300 in the node display method may include the following steps:

[0066] In response to a user's triggering operation on the aggregate node, a node display area is generated in the node graph, which displays each node corresponding to the aggregate node.

[0067] In response to the user's selection of a node in the node display area, the target node is determined.

[0068] The target node is shown in the node diagram.

[0069] In this embodiment, the user's triggering operation on the aggregation node can be clicking the aggregation node, moving to the aggregation node, or quickly switching to the aggregation node, etc., and this application does not impose any limitations on this. The position of the node display area can be a fixed position such as a corner, side, or middle of the node graph, or it can change as the position of the aggregation node triggered by the user changes, always displaying near the aggregation node triggered by the user.

[0070] like Figure 3 As shown, the node display area can display the node information of the aggregated nodes in a list format, including name, type, level, and node operations.

[0071] In other embodiments, the aggregated nodes can also be displayed in other forms such as magnified graphs or icon arrangements in the node display area.

[0072] Once a user selects any node in the node display area, that node is designated as the target node and added to the node graph for the user to view.

[0073] Alternatively, in some other embodiments, when a user selects any node in the node display area, that node and all nodes associated with it are added to the node graph as target nodes for the user to view.

[0074] Users can select nodes by clicking, dragging, swiping, using shortcut keys, or triggering actions in the corresponding action bar (e.g., clicking). Figure 3 (Added to the map), this application does not limit this.

[0075] Understandably, in other embodiments, in response to a user's triggering operation on the aggregation node, all aggregated nodes in the aggregation node can be directly identified as target nodes and added to the node graph for user viewing.

[0076] Specifically, in other embodiments, the specific implementation of step S300 can be found in [reference needed]. Figure 4 . Figure 4 It is based on Figure 2 According to the detailed description of step S300 in the node display method shown in the corresponding embodiment, step S300 in the node display method may include the following steps:

[0077] S310, in response to the user's operation on any node in the node graph, determine the target node.

[0078] S320, The target node is displayed in the node diagram.

[0079] In this embodiment, any node can be a node of any level, such as a first-level node, a second-level node, a third-level node, etc. When a user operates on a node, the system predicts the next node the user may need and displays it to the user. This can reduce unnecessary operations by the user, help the user quickly locate the node they need, facilitate data analysis, and improve the user experience.

[0080] In S310, there can be one or more target nodes. There are multiple ways to determine the target nodes, or to predict the nodes that the user needs to use. For details, please refer to the following embodiments.

[0081] Specifically, in some embodiments, the specific implementation of step S310 can be found in [reference needed]. Figure 5 . Figure 5 It is based on Figure 4According to the detailed description of step S310 in the node display method shown in the corresponding embodiment, step S310 in the node display method may include the following steps:

[0082] S312, in response to the user's operation on any aggregate node in the node graph, obtain the node information of all nodes in the aggregate node.

[0083] S314, Determine the target node based on the node information of each node in the aggregated node.

[0084] In this embodiment, the node operated by the user is an aggregation node. At this time, the node that the user may use next is generally a node under the aggregation node, or it may be a node that is strongly related to a node under the aggregation node. Then, the node information of each node in the aggregation node can be obtained and analyzed to determine the corresponding target node.

[0085] In S312, the node information of all nodes in the aggregate node obtained can be the node information of the next-level branch node of the aggregate node, or the node information of all nodes at all levels under the aggregate node. This application does not limit this.

[0086] As mentioned earlier, user operations on aggregated nodes can include expanding nodes, moving nodes, selecting nodes, etc., and specific triggering methods can include clicking, double-clicking, swiping, dragging, etc.

[0087] In S314, the node information of each node in the aggregation node is obtained and analyzed to determine the corresponding target node.

[0088] In some embodiments, analysis can be performed directly based on nodes. Specifically, the node information of each node is vectorized into a corresponding node information vector, and then all node information vectors are input into the corresponding neural network model for analysis. The neural network model then predicts the corresponding target node. The prediction method can be to determine each node individually whether it is a potential target node and output those nodes as target nodes; or it can be to predict the probability of each node being a target node and output nodes with probabilities exceeding a certain probability threshold as target nodes.

[0089] Specifically, in some other embodiments, the specific implementation of step S314 can be found in the following embodiments. This embodiment is based on... Figure 5 According to the detailed description of step S314 in the node display method shown in the corresponding embodiment, step S314 in the node display method may include the following steps:

[0090] Get the node information of the node preceding the user's action.

[0091] The node information of each node in the aggregation node is paired with the node information of the previous node to form corresponding node information pairs.

[0092] The node information is used to filter the model for each input node to obtain the target node.

[0093] In this embodiment, the node information of the previous node operated by the user before operating the aggregation node is combined with the node information of each aggregated node under the aggregation node. Through correlation analysis, it is determined which of the aggregated nodes belong to the target node. Since the node selection model is trained with a large number of samples, its maintenance only requires adjustments based on samples. Compared with other selection methods, the maintenance cost is lower, as it basically only requires maintaining the node information pairs, reducing maintenance costs and improving code stability.

[0094] Specifically, the correlation analysis of node information pairs can be conducted by determining the degree of information similarity and complementarity between the two nodes, thereby identifying the target node.

[0095] Specifically, the training method for the above-mentioned node selection model includes:

[0096] Obtain the node information sample pair set, which contains multiple node information sample pairs, each of which is labeled with a corresponding target node label.

[0097] The node information sample pairs are input one by one into the node filtering model to obtain the target node results.

[0098] Based on the output target node results and the target node labels, the parameters of the node selection model are updated until the predetermined termination condition is met, the training ends, and the trained node selection model is obtained.

[0099] In the embodiments of this application, during training, a set of node information sample pairs containing multiple node information sample pairs can be obtained first, and each node information sample pair is labeled with a corresponding target node label; then, the multiple node information sample pairs are divided into a training set, a validation set, and a test set according to a predetermined ratio; then, the parameters of the encoder and decoder in the node selection model are adjusted and determined according to the node information sample pairs included in the training set, validation set, and test set, and the trained node selection model is obtained.

[0100] When training the model, the node information sample set can be divided into a training set, a validation set, and a test set. Then, the model is trained based on the training set, validated based on the validation set, and tested based on the test set to obtain a trained node selection model.

[0101] Before training on the training set, the node information sample pairs in the training set can be preprocessed. Preprocessing includes vector adjustment, normalization, data augmentation, and class encoding.

[0102] After obtaining the enhanced training set, the node selection model can be trained based on the enhanced training set, and the parameters and weights in the network can be updated.

[0103] Specifically, the node information samples in the training set are used to filter the input nodes of the node selection model, resulting in the target node output. The target node output is then compared with the target node label, and the loss function is calculated. The loss function is then minimized using stochastic gradient descent. The parameters and weights in the node selection model are updated via backpropagation until the loss function meets predetermined conditions, such as convergence or falling below a predetermined threshold.

[0104] In some embodiments, the target node result includes a target contour and target contour parameters, and the target node label may include at least one of a contour label and a contour parameter label. The loss function is calculated by comparing the target contour with the contour label and / or comparing the target contour parameters with the contour parameter label.

[0105] After training, the image target node network with updated parameters from the training set can be validated using a validation set. Specifically, the image target node network is debugged based on the validation set data. When the loss function meets predetermined conditions, the model parameters for that stage are output. If the loss function does not meet the predetermined conditions, hyperparameters such as the learning rate are automatically adjusted, and the next round of network model training is performed.

[0106] When the loss function computed on the validation set meets predetermined conditions, the parameters and weights can be retained, and then the retained parameters are tested based on the test set. Specifically, the input test set data enables the image target node network with retained parameters and weights to output target node results and model weights. By comparing the model loss and corresponding weights across multiple rounds, the model weights with the minimum loss are output, thus determining the trained node selection model.

[0107] After obtaining the trained node selection model, the target node can be selected based on the node selection model.

[0108] Furthermore, data augmentation is not required for the input data in the validation and test sets.

[0109] Specifically, in other embodiments, the specific implementation of step S310 can be found in [reference needed]. Figure 6 . Figure 6 It is based on Figure 4According to the detailed description of step S310 in the node display method shown in the corresponding embodiment, step S310 in the node display method may include the following steps:

[0110] S316, in response to the user's operation on any node in the node graph, determine the related node, the related node being the node associated with the current node, the current node being the node operated on by the user.

[0111] S318, Select the target node from the relevant nodes.

[0112] In this embodiment, the node operated by the user may not be an aggregate node. The node that the user needs to use next may not belong to the same branch as the node that is being operated on. In this case, it is necessary to determine the nodes that are associated with the node operated by the user and to determine the target node among these nodes.

[0113] It should be noted that the aforementioned relationships can include the degree of similarity and complementarity of information between two nodes, whether there is a switching operation between the two nodes, and the frequency of node usage.

[0114] In S316, there are multiple ways to determine the nodes that are associated with the nodes operated by the user. For details, please refer to the following embodiments.

[0115] Specifically, in some embodiments, the specific implementation of step S316 can be found in the following embodiments. This embodiment is based on... Figure 6 According to the detailed description of step S316 in the node display method shown in the corresponding embodiment, step S316 in the node display method may include the following steps:

[0116] In response to a user's operation on any node in the node graph, the user's operation history data is obtained.

[0117] Based on the user operation history data, the neighboring nodes of the current node are determined. The neighboring nodes are those that are adjacent to the current node in the operation sequence.

[0118] The neighboring nodes of the current node are identified as related nodes.

[0119] In this embodiment, based on the analysis of user operation history data, nodes that are adjacent to the user's operation nodes in time (i.e., in operation sequence) are identified as adjacent nodes. When two nodes are adjacent in operation sequence, it is generally considered that these two nodes are likely to have a correlation, so adjacent nodes can be directly identified as related nodes.

[0120] Specifically, in some embodiments, adjacent nodes can be determined through the following steps:

[0121] Based on the user operation history data, the nodes are sorted according to the time sequence of user operations to obtain the node time sequence.

[0122] Based on the node timing sequence, determine the neighboring nodes of the current node.

[0123] In this embodiment, neighboring nodes are identified through node time sequence; nodes adjacent to the current node in the time sequence are considered neighboring nodes. If a node's user operation history data shows operations performed at multiple times, these operations will be repeated in the node time sequence.

[0124] Adjacent nodes can be directly adjacent or indirectly adjacent. Directly adjacent nodes are those two nodes that are not connected by any other nodes in the node sequence. Indirectly adjacent nodes are those two nodes that are connected by other nodes in the node sequence.

[0125] For example, in a node sequence, if a user operates on node A first, then node S, and then node D, the sequence is ASD. In this node sequence, there are no other nodes between nodes A and S, or between nodes S and D, so they are directly adjacent. Nodes A and D are connected by node S, so they are indirectly adjacent.

[0126] In some embodiments, adjacent nodes may include only directly adjacent nodes. In other embodiments, in addition to directly adjacent nodes, indirect adjacent nodes may also be included. It should be noted that two indirectly adjacent nodes may include a predetermined number of other nodes. When the number of nodes between two nodes exceeds the predetermined number of indirect nodes, the two nodes cannot be indirectly adjacent. The predetermined number of indirect nodes can be a small integer value such as 1, 2, or 3, and can be determined comprehensively based on the node timing length, required processing precision, and required processing efficiency, or can be manually set by the user according to their own needs.

[0127] It should be noted that in some embodiments, each node in the node time sequence has a timestamp. In the node time sequence, if the number of nodes operated by the user within a predetermined time period exceeds the predetermined number of nodes operated, or if the time interval between a predetermined number of consecutive nodes is less than the predetermined time interval, then these nodes are not considered to be adjacent nodes. This is to filter out the data noise caused by the user frequently switching nodes in a short period of time and improve the accuracy of the correlation analysis.

[0128] In S318, further filtering is needed based on the relevant nodes to determine the target nodes suitable for display in the node graph, in order to reduce noise. In some other embodiments, all relevant nodes may also be identified as target nodes.

[0129] There are several ways to filter target nodes among relevant nodes. For example, you can analyze the frequency of user switching between two nodes, whether the two nodes are on the same branch, the level of the branch to which the two nodes belong, the degree of information similarity between the two nodes, and the degree of information complementarity, and then determine the target node.

[0130] Specifically, in some embodiments, the specific implementation of step S218 can be found in the following embodiments. This embodiment is based on... Figure 6 According to the detailed description of step S218 in the node display method shown in the corresponding embodiment, step S218 in the node display method may include the following steps:

[0131] By comparing the node information of the current node and the related nodes, the target probability of each related node is determined. The target probability is the probability that the user selects the next node to operate on.

[0132] The target node is determined based on the target probability.

[0133] In this embodiment, the target node is determined by comparing the node information of the current node and related nodes. Specifically, the probability that each related node will be selected by the user as the next node to be operated on is first determined by analyzing the similarity and complementarity of the node information between the two nodes, i.e., the target probability of each related node. Then, the related node with the higher target probability is selected as the target node. The specific selection method can be to select all nodes whose target probability is higher than the predetermined target probability as the target node, or to select the top predetermined number of nodes with the highest target probability as the target node.

[0134] Specifically, in some embodiments, the target probability can be determined through the following steps:

[0135] By comparing the node information of the current node and the related nodes, the similarity between each related node and the current node is determined.

[0136] Based on user operation history data, determine the switching frequency of the current node and each of the related nodes.

[0137] The target probability is determined based on the switching frequency and the similarity.

[0138] In this embodiment, the target probability is determined by comparing two dimensions: the similarity between the current node and related nodes, and the frequency with which the user switches between the current node and related nodes. This improves the comprehensiveness and accuracy of target node determination.

[0139] In S320, the corresponding target node is directly displayed in the node graph.

[0140] The following describes an embodiment of the apparatus described in this application, which can be used to execute the node display method described in the above embodiments of this application. For details not disclosed in the apparatus embodiments of this application, please refer to the embodiments of the node display method described above.

[0141] Figure 7 A block diagram of a node display device according to an embodiment of this application is shown.

[0142] Reference Figure 7 As shown, a node display device 700 according to an embodiment of this application includes: a quantity monitoring module 710, a node aggregation module 720, and a node display module 730.

[0143] The quantity monitoring module 710 is used to monitor the number of nodes under each branch in the node graph; the node aggregation module 720 is used to aggregate the nodes under the branch to form an aggregate node if the number of nodes under the branch exceeds the aggregation quantity; and the node display module 730 is used to display the target node in the aggregate node in response to the user's operation on the node graph.

[0144] In some specific embodiments of this application, the node display module specifically includes: a region generation submodule, used to generate a node display area in the node graph in response to a user's trigger operation on the aggregated node, wherein each node corresponding to the aggregated node is displayed in the node display area; a target node submodule, used to determine a target node in response to a user's selection of a node in the node display area; and a node display submodule, used to display the target node in the node graph.

[0145] In some specific embodiments of this application, the node display module specifically includes:

[0146] The node determination submodule is used to determine the target node in response to a user's operation on any node in the node graph; the node display submodule is used to display the target node in the node graph.

[0147] In some specific embodiments of this application, the node determination submodule specifically includes: a node information acquisition unit, used to acquire node information of all nodes in the aggregate node in response to a user's operation on any aggregate node in the node graph; and a target node determination unit, used to determine a target node based on the node information of each node in the aggregate node.

[0148] In some specific embodiments of this application, the target node determination unit is specifically used to perform the following steps: obtaining the node information of the previous node operated by the user; pairing the node information of each node in the aggregated node with the node information of the previous node to form corresponding node information pairs; and inputting each of the node information pairs into the node filtering model to obtain the target node.

[0149] In some specific embodiments of this application, the node determination submodule specifically includes: a related node determination unit, used to determine related nodes in response to user operation on any node in the node graph, wherein the related nodes are nodes related to the current node, and the current node is the node operated by the user; and a target node filtering unit, used to filter out target nodes from the related nodes.

[0150] In some specific embodiments of this application, the relevant node determination unit specifically includes: a historical data acquisition subunit, used to acquire user operation history data in response to user operation on any node in the node graph; an adjacent node determination subunit, used to determine the adjacent nodes of the current node based on the user operation history data, wherein the adjacent nodes are nodes that are adjacent to the current node in the operation sequence; and a key node determination subunit, used to determine the adjacent nodes of the current node as relevant nodes.

[0151] In some specific embodiments of this application, the adjacent node determination subunit is specifically used to perform the following steps: sorting the nodes according to the time order of the user operation based on the user operation history data to obtain the node time sequence; and determining the adjacent nodes of the current node based on the node time sequence.

[0152] In some specific embodiments of this application, the target node filtering unit specifically includes: a node information comparison subunit, used to compare the node information of the current node and the related nodes to determine the target probability of each related node, wherein the target probability is the probability that the node is selected by the user as the next node to be operated; and a target node determination subunit, used to determine the target node based on the target probability.

[0153] In some specific embodiments of this application, the node information comparison subunit is specifically used to perform the following steps: comparing the node information of the current node and the related nodes to determine the similarity between each related node and the current node; determining the switching frequency of the current node and each of the related nodes based on user operation history data; and determining the target probability based on the switching frequency and the similarity.

[0154] In the embodiments of this application, by monitoring the number of nodes under each branch in the node graph, when the number of nodes under a branch exceeds the aggregation limit (i.e., when the number of nodes under that branch is excessive), the nodes under that branch are aggregated to form a large aggregate node. This reduces the number of nodes, thus reducing noise. Simultaneously, the number of displayed nodes remains within a certain range, ensuring that the nodes are not too small when displaying the entire node graph. Then, when the user interacts with the node graph, the target node to be displayed to the user is determined based on the user's actions and the interacted nodes. This target node is then displayed downstream of the aggregate node, thus reducing noise while simultaneously displaying the target node, which is not considered noise. This allows the user to more intuitively identify the nodes they need, facilitating data analysis.

[0155] Figure 8 A schematic diagram of the structure of a computer system suitable for implementing the electronic device of the present application is shown.

[0156] It should be noted that, Figure 8 The computer system of the electronic device shown is merely an example and should not impose any limitation on the functionality and scope of use of the embodiments of this application.

[0157] like Figure 8 As shown, the computer system includes a Central Processing Unit (CPU) 1801, which can perform various appropriate actions and processes based on programs stored in Read-Only Memory (ROM) 1802 or programs loaded from storage portion 1808 into Random Access Memory (RAM) 1803, such as performing the methods described in the above embodiments. The RAM 1803 also stores various programs and data required for system operation. The CPU 1801, ROM 1802, and RAM 1803 are interconnected via a bus 1804. An Input / Output (I / O) interface 1805 is also connected to the bus 1804.

[0158] The following components are connected to I / O interface 1805: an input section 1806 including a keyboard, mouse, etc.; an output section 1807 including a cathode ray tube (CRT), liquid crystal display (LCD), etc., and speakers, etc.; a storage section 1808 including a hard disk, etc.; and a communication section 1809 including a network interface card such as a LAN (Local Area Network) card, modem, etc. The communication section 1809 performs communication processing via a network such as the Internet. A drive 1810 is also connected to I / O interface 1805 as needed. Removable media 1811, such as a disk, optical disk, magneto-optical disk, semiconductor memory, etc., are installed on drive 1810 as needed so that computer programs read from them can be installed into storage section 1808 as needed.

[0159] Specifically, according to embodiments of this application, the processes described above with reference to the flowcharts can be implemented as computer software programs. For example, embodiments of this application include a computer program product comprising a computer program carried on a computer-readable medium, the computer program including a computer program for performing the methods shown in the flowcharts. In such embodiments, the computer program can be downloaded and installed from a network via communication section 1809, and / or installed from removable medium 1811. When the computer program is executed by central processing unit (CPU) 1801, it performs various functions defined in the system of this application.

[0160] It should be noted that the computer-readable medium shown in the embodiments of this application can be a computer-readable signal medium or a computer-readable storage medium, or any combination of the two. A computer-readable storage medium can be, for example,—but not limited to—an electrical, magnetic, optical, electromagnetic, infrared, or semiconductor system, apparatus, or device, or any combination thereof. More specific examples of a computer-readable storage medium may include, but are not limited to: an electrical connection having one or more wires, a portable computer disk, a hard disk, random access memory (RAM), read-only memory (ROM), erasable programmable read-only memory (EPROM), flash memory, optical fiber, portable compact disc read-only memory (CD-ROM), optical storage device, magnetic storage device, or any suitable combination thereof. In this application, a computer-readable storage medium can be any tangible medium containing or storing a program that can be used by or in conjunction with an instruction execution system, apparatus, or device. In this application, a computer-readable signal medium can include a data signal propagated in baseband or as part of a carrier wave, carrying a computer-readable computer program. The transmitted data signal can take various forms, including but not limited to electromagnetic signals, optical signals, or any suitable combination thereof. The computer-readable signal medium can also be any computer-readable medium other than a computer-readable storage medium, which can send, propagate, or transmit a program for use by or in connection with an instruction execution system, apparatus, or device. The computer program contained on the computer-readable medium can be transmitted using any suitable medium, including but not limited to wireless, wired, etc., or any suitable combination thereof.

[0161] The flowcharts and block diagrams in the accompanying drawings illustrate the architecture, functionality, and operation of possible implementations of systems, methods, and computer program products according to various embodiments of this application. Each block in a flowchart or block diagram may represent a module, segment, or portion of code, which contains one or more executable instructions for implementing a specified logical function. It should also be noted that in some alternative implementations, the functions indicated in the blocks may occur in a different order than those indicated in the drawings. For example, two consecutively indicated blocks may actually be executed substantially in parallel, and they may sometimes be executed in reverse order, depending on the functions involved. It should also be noted that each block in a block diagram or flowchart, and combinations of blocks in a block diagram or flowchart, can be implemented using a dedicated hardware-based system that performs the specified function or operation, or using a combination of dedicated hardware and computer instructions.

[0162] The units described in the embodiments of this application can be implemented in software or hardware, and the described units can also be located in a processor. The names of these units do not necessarily limit the specific unit itself.

[0163] In another aspect, this application also provides a computer-readable medium, which may be included in the electronic device described in the above embodiments; or it may exist independently and not assembled into the electronic device. The computer-readable medium carries one or more programs, which, when executed by the electronic device, cause the electronic device to perform the methods described in the above embodiments.

[0164] This specification also provides a computer program product storing at least one instruction, which is loaded and executed by the processor as described above. Figures 1-6 The method described in the illustrated embodiment can be found in the following document for a detailed execution process. Figures 1-6 The specific details of the illustrated embodiments will not be elaborated here.

[0165] It should be noted that although several modules or units for the device used to perform actions have been mentioned in the detailed description above, this division is not mandatory. In fact, according to the embodiments of this application, the features and functions of two or more modules or units described above can be embodied in one module or unit. Conversely, the features and functions of one module or unit described above can be further divided and embodied by multiple modules or units.

[0166] Through the above description of the embodiments, those skilled in the art will readily understand that the exemplary embodiments described herein can be implemented by software or by combining software with necessary hardware. Therefore, the technical solutions according to the embodiments of this application can be embodied in the form of a software product, which can be stored in a non-volatile storage medium (such as a CD-ROM, USB flash drive, external hard drive, etc.) or on a network, including several instructions to cause a computing device (such as a personal computer, server, touch terminal, or network device, etc.) to execute the method according to the embodiments of this application.

[0167] Other embodiments of this application will readily occur to those skilled in the art upon consideration of the specification and practice of the embodiments disclosed herein. This application is intended to cover any variations, uses, or adaptations of this application that follow the general principles of this application and include common knowledge or customary techniques in the art not disclosed herein.

[0168] It should be understood that this application is not limited to the precise structure described above and shown in the accompanying drawings, and various modifications and changes can be made without departing from its scope. The scope of this application is limited only by the appended claims.

Claims

1. A method for displaying nodes, characterized in that, The node display method includes: Monitor the number of nodes under each branch in the node graph; If the number of nodes under a branch exceeds the number of nodes to be aggregated, the nodes under the branch will be aggregated to form an aggregate node. In response to user actions on the node graph, the target node in the aggregated node is displayed.

2. The node display method as described in claim 1, characterized in that, The step of responding to user operations on the node graph and displaying the target node in the aggregated node specifically includes: In response to a user's triggering operation on the aggregate node, a node display area is generated in the node graph, which displays each node corresponding to the aggregate node; In response to the user's selection of a node in the node display area, the target node is determined; The target node is shown in the node diagram.

3. The node display method as described in claim 1, characterized in that, The step of responding to user operations on the node graph and displaying the target node in the aggregated node specifically includes: In response to a user's operation on any node in the node graph, the target node is determined; The target node is shown in the node diagram.

4. The node display method as described in claim 3, characterized in that, The step of determining the target node in response to a user's operation on any node in the node graph specifically includes: In response to a user's operation on any aggregate node in the node graph, obtain the node information of all nodes in that aggregate node; The target node is determined based on the node information of each node in the aggregated node.

5. The node display method as described in claim 4, characterized in that, The step of determining the target node based on the node information of each node in the aggregated node specifically includes: Get the node information of the node preceding the user's action; The node information of each node in the aggregation node is paired with the node information of the previous node to form corresponding node information pairs; The node information is used to filter the model for each input node to obtain the target node.

6. The node display method as described in claim 3, characterized in that, The step of determining the target node in response to a user's operation on any node in the node graph specifically includes: In response to a user's operation on any node in the node graph, a related node is determined, wherein the related node is a node associated with the current node, and the current node is the node operated on by the user; The target node is selected from the relevant nodes.

7. A node display device, characterized in that, The node display device includes: The quantity monitoring module is used to monitor the number of nodes under each branch in the node graph; The node aggregation module is used to aggregate the nodes under the branch to form an aggregate node if the number of nodes under the branch exceeds the aggregation limit. The node display module is used to display the target node in the aggregated node in response to the user's operation on the node graph.

8. A computer-readable medium having a computer program stored thereon, characterized in that, When the computer program is executed by the processor, it implements the node display method as described in any one of claims 1 to 6.

9. An electronic device, characterized in that, include: One or more processors; A storage device for storing one or more programs, which, when executed by one or more processors, cause the one or more processors to implement the node display method as described in any one of claims 1 to 6.

10. A computer program product comprising one or more computer programs, characterized in that, When the one or more computer programs are executed by one or more processors, they implement the steps of the node display method according to any one of claims 1 to 6.

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