Target object persona construction method and system, and storage medium

Abstract

Disclosed are a target object persona construction method and system, and a storage medium, which are applied to the technical field of information, and can dynamically update a target object persona in real time and effectively improve the precision of the target object persona. The method comprises: analyzing target object usage behavior events, and constructing behavior event data, the behavior event data comprising a plurality of target object behavior events; on the basis of the behavior event data, creating a first behavior tree, the first behavior tree comprising a plurality of behavior nodes, and the behavior nodes corresponding to the target object behavior events; acquiring target object behavior data by means of a preset event-driven model, so as to update the first behavior tree on the basis of the target object behavior data and generate a second behavior tree; and constructing and obtaining a target object persona by means of analyzing the second behavior tree.

Description

Target object portrait construction method, system and storage medium Technical Field

[0001] The present invention relates to the field of information technology, and in particular to a method, system and storage medium for constructing a target object portrait. Background Art

[0002] With the advent of the big data era, target persona profiling is gaining increasing importance across various products and dimensions. In real-world applications, understanding the target audience has become crucial for core competitiveness. Related technologies primarily construct target persona profiling by acquiring the target audience's attributes or behavioral characteristics. This requires massive amounts of target object data to accurately identify the target audience's needs. Therefore, the above technical issues urgently need to be addressed.

[0003] Summary of the Invention

[0004] In order to solve at least one of the above technical problems, the present invention proposes a target object portrait construction method, system and storage medium, which can dynamically update the target object portrait in real time and effectively improve the accuracy of the target object portrait.

[0005] In one aspect, an embodiment of the present invention provides a method for constructing a target object portrait, comprising the following steps:

[0006] Analyze the target object's usage behavior events and construct behavior event data; wherein the behavior event data includes a plurality of target object behavior events;

[0007] Creating a first behavior tree according to the behavior event data; wherein the first behavior tree includes a plurality of behavior nodes, and the behavior nodes correspond to the target object behavior events;

[0008] Acquire target object behavior data through a preset event-driven model, and update the first behavior tree according to the target object behavior data to generate a second behavior tree;

[0009] The target object portrait is constructed by analyzing the second behavior tree.

[0010] According to some embodiments of the present invention, the preset event-driven model includes a mediator topology;

[0011] The updating the first behavior tree according to the target object behavior data to generate a second behavior tree includes:

[0012] Each behavior event in the target object behavior data is sent to an initial event queue and managed and controlled by an event intermediary to select the corresponding behavior node in the first behavior tree to generate the second behavior tree; wherein the event intermediary includes a control node of the first behavior tree, and the node type of the control node includes a selection node.

[0013] According to some embodiments of the present invention, the managing and controlling through an event mediator to select the corresponding behavior node in the first behavior tree to generate the second behavior tree includes:

[0014] Generate corresponding pending events through the event intermediary according to each behavior event in the initial event queue, and send them to the corresponding event channel so that the pending events are processed by the corresponding event processor to obtain an execution result;

[0015] The structure of the first behavior tree is updated according to the execution result to generate the second behavior tree.

[0016] According to some embodiments of the present invention, constructing the target object portrait by analyzing the second behavior tree includes:

[0017] A target object behavior pattern analysis is performed by a target object portrait processor according to the second behavior tree and the execution result to generate the target object portrait.

[0018] According to some embodiments of the present invention, before executing the step of sending each behavior event in the target object behavior data to the initial event queue, the method further includes:

[0019] Performing preset data processing on the target object behavior data to obtain converted data; wherein the preset data processing includes data cleaning and data format conversion.

[0020] According to some embodiments of the present invention, before executing the step of processing the to-be-processed event by the corresponding event processor to obtain an execution result, the method further includes:

[0021] Determine whether the event to be processed meets the precondition;

[0022] When it is determined that the event to be processed meets the precondition, the corresponding event to be processed is received by the event processor.

[0023] According to some embodiments of the present invention, when determining that the event to be processed satisfies the precondition, receiving the corresponding event to be processed by the event processor includes:

[0024] When it is determined that the event to be processed meets a first preset condition, the event to be processed is received by the event processor; wherein the first preset condition includes execution success or execution failure;

[0025] Alternatively, when the event to be processed meets a second preset condition, the corresponding event to be processed is received by the event processor; wherein the second preset condition includes meeting a preset number of sub-conditions.

[0026] On the other hand, an embodiment of the present invention further provides a target object portrait construction system, including:

[0027] The first module is used to analyze the target object's usage behavior events and construct behavior event data; wherein the behavior event data includes a plurality of target object behavior events;

[0028] A second module is configured to create a first behavior tree based on the behavior event data; wherein the first behavior tree includes a plurality of behavior nodes, each of which corresponds to a target object behavior event;

[0029] A third module is configured to obtain target object behavior data through a preset event-driven model, so as to update the first behavior tree according to the target object behavior data to generate a second behavior tree;

[0030] The fourth module is used to construct the target object portrait by analyzing the second behavior tree.

[0031] On the other hand, an embodiment of the present invention further provides a target object portrait construction system, including:

[0032] at least one processor;

[0033] at least one memory for storing at least one program;

[0034] When the at least one program is executed by the at least one processor, the at least one processor implements the target object portrait construction method as described in the above embodiment.

[0035] On the other hand, an embodiment of the present invention further provides a computer storage medium, which stores a program executable by a processor. When the program executable by the processor is executed by the processor, it is used to implement the target object portrait construction method as described in the above embodiment.

[0036] According to an embodiment of the present invention, a method, system and storage medium for constructing a target object portrait have at least the following beneficial effects: the embodiment of the present invention first analyzes the target object's usage behavior events and constructs behavior event data. Among them, the behavior event data in the embodiment of the present invention includes several target object behavior events. Then, the embodiment of the present invention creates a first behavior tree including several behavior nodes based on the behavior event data, and the behavior nodes correspond to the target object behavior events. Furthermore, the embodiment of the present invention obtains the target object behavior data through a preset event-driven model to update the constructed first behavior tree according to the target behavior data, thereby generating a second behavior tree, and then by analyzing the second behavior tree, a target object portrait can be constructed, effectively improving the accuracy of the target object portrait. In addition, the embodiment of the present invention can respond to the behavior of the target object in real time through an event-driven behavior tree, thereby realizing real-time dynamic updating of the target object portrait, and can dynamically adjust the behavior tree according to the behavior changes of the target object, making the target object portrait more accurate. BRIEF DESCRIPTION OF THE DRAWINGS

[0037] FIG1 is a flow chart of a method for constructing a target object portrait according to an embodiment of the present invention;

[0038] FIG2 is a flowchart illustrating the steps of updating a first behavior tree based on target object behavior data to generate a second behavior tree according to an embodiment of the present invention;

[0039] FIG3 is a flowchart illustrating the steps of selecting corresponding behavior nodes in a first behavior tree and generating a second behavior tree by performing management control through an event intermediary according to an embodiment of the present invention;

[0040] FIG4 is a schematic diagram of a process for constructing a target object portrait by analyzing a second behavior tree according to an embodiment of the present invention;

[0041] 5 is a schematic diagram of a flow chart of steps for an event processor to receive a corresponding event to be processed according to an embodiment of the present invention;

[0042] 6 is a schematic diagram of a process flow of obtaining target object behavior data through a preset event-driven model according to an embodiment of the present invention;

[0043] 7 is a schematic diagram of the target object portrait construction system architecture provided by an embodiment of the present invention;

[0044] 8 is a schematic diagram of an application scenario of a target object binding device provided by an embodiment of the present invention;

[0045] FIG9 is a modular schematic diagram of a target object portrait construction system provided by an embodiment of the present invention

[0046] FIG10 is a functional block diagram of a target object portrait construction system provided by an embodiment of the present invention. DETAILED DESCRIPTION

[0047] The embodiments described in the embodiments of this application should not be regarded as limitations of this application. All other embodiments obtained by ordinary technicians in this field without making any creative work are within the scope of protection of this application.

[0048] In the following description, reference is made to “some embodiments”, which describes a subset of all possible embodiments, but it will be understood that “some embodiments” may be the same subset or different subsets of all possible embodiments and may be combined with each other without conflict.

[0049] Unless otherwise defined, all technical and scientific terms used herein have the same meaning as commonly understood by those skilled in the art to which this application pertains. The terms used herein are for the purpose of describing the embodiments of this application only and are not intended to limit this application.

[0050] Before introducing the embodiments of the present application, the relevant terms involved in the present application are first explained.

[0051] A tree is a nonlinear data structure consisting of nodes and edges. Each node can have multiple children but only one parent. Tree structures are often used to represent hierarchical relationships. Accordingly, the root node of a tree is unique and has no parent, while leaf nodes are nodes without children.

[0052] Target object portrait: also known as user portrait, refers to a method of depicting the characteristics and features of the target object by analyzing and mining the multi-dimensional data of the target object.

[0053] An event-driven model is a computing model that drives program execution based on the occurrence and subsequent processing of events. Programs are triggered by external events, rather than following a fixed sequence or time interval. Accordingly, in an event-driven model, programs are typically managed by an event loop. This loop continuously listens for events and selects the appropriate handler based on the event type and related information.

[0054] With the advent of the big data era, target persona profiling is gaining increasing importance across various products and dimensions. In real-world applications, understanding the target audience has become crucial for core competitiveness. Related technologies primarily construct target persona profiling by acquiring the target audience's attributes or behavioral characteristics. This requires massive amounts of target object data to accurately identify the target audience's needs. Therefore, the above technical issues urgently need to be addressed.

[0055] One embodiment of the present invention provides a method, system, and storage medium for constructing a target object portrait, which can dynamically update the target object portrait in real time and effectively improve the accuracy of the target object portrait. Referring to Figure 1, the method of this embodiment of the present invention includes but is not limited to steps S110, S120, S130, and S140.

[0056] Specifically, the application process of the method of the embodiment of the present invention includes but is not limited to the following steps:

[0057] S110: Analyze the target object's usage behavior events and construct behavior event data, wherein the behavior event data includes a number of target object behavior events.

[0058] S120: Creating a first behavior tree according to the behavior event data, wherein the first behavior tree includes a plurality of behavior nodes corresponding to the target object behavior events.

[0059] S130: Obtaining target object behavior data through a preset event-driven model, and updating the first behavior tree according to the target object behavior data to generate a second behavior tree.

[0060] S140: Analyze the second behavior tree to construct a target object portrait.

[0061] During the operation of this specific embodiment, the present invention first analyzes target object usage behavior events to construct behavior event data. Specifically, the behavior event data in this embodiment includes several target object behavior events. In this embodiment, target object usage behavior events refer to the target object's operational behaviors when performing related operations, such as clicks, browsing, and swiping. Accordingly, target object behavior events in this embodiment refer to events that the target object may perform in the system, such as device binding, device verification, and query events, obtained by categorizing and organizing target object usage behavior events. This embodiment defines possible events that may occur in the system by categorizing and organizing target object usage behavior events, thereby constructing corresponding behavior event data. Next, the present embodiment creates a first behavior tree based on the behavior event data. Specifically, this first behavior tree in this embodiment includes several behavior nodes, and these behavior nodes correspond to target object behavior events. It will be readily understood that this embodiment describes the target object's behavior through the first behavior tree. In this embodiment, each behavior node in the first behavior tree represents a target object behavior event, meaning that each node in the first behavior tree represents a target object behavior. Accordingly, in the embodiment of the present invention, the connection between behavior nodes represents the relationship between the two behavior nodes.

[0062] Furthermore, embodiments of the present invention utilize a preset event-driven model to acquire target object behavior data, updating the first behavior tree based on the target object behavior data and generating a second behavior tree. Specifically, target object behavior data in embodiments of the present invention refers to event data triggered by target object behavior. Accordingly, the preset event-driven model in embodiments of the present invention refers to a model that drives a program through the occurrence and processing of events. Embodiments of the present invention utilize target object behavior data as event input to update the first behavior tree, thereby generating the second behavior tree. For example, when the preset event-driven model monitors an event occurrence in the first behavior tree, the embodiment of the present invention acquires target object behavior data. Based on this target object behavior data, the embodiment of the present invention locates the corresponding behavior node in the first behavior tree and updates the state of the behavior node, thereby updating the first behavior tree and generating the second behavior tree. Finally, embodiments of the present invention analyze the second behavior tree to construct a target object profile. Specifically, embodiments of the present invention analyze the second behavior tree to understand user behavior patterns, extract and describe corresponding target object behaviors and features, and then construct a target object profile, effectively improving the accuracy of the target object profile. It's easy to understand that by constructing a behavior tree using a preset event-driven model, the embodiments of the present invention can respond to the target object's behavior in real time, enabling real-time updates to the target object's profile. Furthermore, by using event-driven behavior tree construction, the embodiments of the present invention can adjust and optimize the behavior tree based on changes in the target object's behavior, thereby further refining the target object's profile. Furthermore, the event-driven behavior tree in the embodiments of the present invention can also construct personalized target object profiles, creating a corresponding target object profile based on each target object's behavior.

[0063] It should be noted that in this embodiment of the present invention, a behavior tree is constructed using a preset event-driven module. This allows for the construction of a target object profile based on the constructed behavior tree, making it relatively easy to add new events and behaviors, allowing the target object profile to expand as the business evolves. However, this approach offers limited scalability. Furthermore, the behavior tree clearly displays the target object's behavioral path, making the target object profile construction process highly interpretable.

[0064] In conjunction with Figure 1 and referring to Figure 2 , in some embodiments of the present invention, the preset event-driven model includes an intermediary topology. Accordingly, in embodiments of the present invention, updating the first behavior tree based on the target object behavior data to generate the second behavior tree includes, but is not limited to, the following steps:

[0065] S210: Send each behavior event in the target object's behavior data to the initial event queue and manage and control it through an event mediator to select the corresponding behavior node in the first behavior tree to generate a second behavior tree. The event mediator includes a control node in the first behavior tree, and the control node's node type includes a selection node.

[0066] In this specific embodiment, the preset event-driven model in the embodiment of the present invention includes an intermediary topology. Among them, the intermediary topology is an architectural pattern for processing and transmitting time, which coordinates and processes events through an intermediary, thereby realizing a loosely coupled system architecture. Specifically, the embodiment of the present invention first sends each behavior event in the target object behavior data to the initial event queue, and manages and controls it through the event intermediary to select the corresponding behavior node in the first behavior tree for update to generate a second behavior tree. Accordingly, the initial event queue in the embodiment of the present invention refers to an event queue composed of each target object behavior event obtained through the preset event-driven model. In addition, the event intermediary in the embodiment of the present invention is an important component of the preset event-driven model, and the workflow of the initial event is managed and controlled through the event intermediary. Among them, in the embodiment of the present invention, the event intermediary is used as the control node of the first behavior tree to determine the executed sub-node. Accordingly, due to the characteristics of the event intermediary, the control node type in the embodiment of the present invention is a selection node type. It is easy to understand that the embodiment of the present invention uses a preset event-driven model as the operating framework and an intermediary topology, namely a scheduler topology, to manage and control the workflow of the initial event through the event intermediary, thereby selecting the corresponding behavior node for updating and constructing a second behavior tree, which can respond to the target object behavior in real time and update the target object portrait in a timely manner.

[0067] 3 , in some embodiments of the present invention, management control is performed through an event mediator to select corresponding behavior nodes in the first behavior tree and generate a second behavior tree, including but not limited to the following steps:

[0068] S310: Generate corresponding to-be-processed events through the event intermediary according to each behavior event in the initial event queue, and send them to the corresponding event channel so that the to-be-processed events are processed by the corresponding event processor to obtain an execution result.

[0069] S320: Update the structure of the first behavior tree according to the execution result to generate a second behavior tree.

[0070] In this specific embodiment, the present invention first generates corresponding pending events based on each behavior event in the initial event queue through an event broker. Specifically, in this embodiment, the pending events are generated by the event broker based on the corresponding behavior events in the initial event queue. The behavior events in the initial event queue are the initial event information, while the pending events are generated by the event broker. However, the pending events are not the events generated after processing the initial events, but rather the event information corresponding to the initial events. Next, the present invention sends the pending events to the corresponding event channels, where they are processed by the corresponding event handlers to obtain an execution result. Specifically, in this embodiment, an event channel is the connection between two behavior nodes defined in a behavior tree. Accordingly, after the initial event is sent to the initial event queue, the event broker manages each behavior event in the queue, generates corresponding pending events, and controls the selection of the corresponding event handlers for processing. The pending events are then sent to the corresponding event channels, allowing the corresponding event handlers to receive and process the pending events and return the corresponding processing results, i.e., the execution results. It will be readily understood that in this embodiment, each behavior node has a corresponding node state, and after the behavior node completes execution, it must return the corresponding execution result. Furthermore, embodiments of the present invention update the structure of the first behavior tree based on the returned execution result, thereby constructing a second behavior tree. Specifically, when a behavior event occurs in the system through a preset event-driven model, embodiments of the present invention treat the behavior event as the initial event and send it to an event queue, i.e., the initial event queue. The event intermediary generates a corresponding pending event and controls the selection of a corresponding event handler for processing. Specifically, the corresponding behavior node in the first behavior tree is checked for processing, and the state of the corresponding behavior node in the first behavior tree is updated based on the returned execution result, thereby updating the structure of the first behavior tree and dynamically adjusting and optimizing the behavior tree, effectively improving the accuracy of the target profile.

[0071] With reference to FIG1 and FIG4 , in some embodiments of the present invention, constructing a target object portrait by analyzing the second behavior tree includes but is not limited to the following steps:

[0072] S410: Analyze the target object behavior pattern through the target object portrait processor according to the second behavior tree and the execution result, and generate a target object portrait.

[0073] In this specific embodiment, the target object profile processor analyzes the second behavior tree and the execution results of each event handler to generate a target object profile. Specifically, the target object profile processor in this embodiment refers to an event handler used to perform target object profile analysis. After the event mediator receives feedback indicating the successful execution of each step, i.e., after the previous steps have been successfully confirmed, the target object profile processor is executed to understand the target object's behavior pattern based on the updated second behavior tree. Combined with the processing results (i.e., execution results) of each event handler, a comprehensive analysis of the target object's behavior and characteristics is performed to generate a corresponding target object profile. For example, when the event mediator selects a node containing pending events A, B, and C, the event mediator first selects the corresponding event channel through the event handler, sending each event to the corresponding event handler for processing. After processing, each event handler returns a confirmation (i.e., an execution result) to the event mediator. Then, after receiving confirmation from each event handler, the target object profile processor analyzes the target object's behavior pattern based on the corresponding execution results and the updated second behavior tree to generate a target object profile.

[0074] In some embodiments of the present invention, before executing the step of sending each behavior event in the target object behavior data to the initial event queue, the target object profile construction method provided by the embodiment of the present invention further includes but is not limited to the following steps:

[0075] Perform preset data processing on the target object's behavior data to obtain transformed data. The preset data processing includes data cleaning and data format conversion.

[0076] In this specific embodiment, the embodiment of the present invention needs to update and transform the acquired target object behavior data to facilitate subsequent processing and analysis. Specifically, after the embodiment of the present invention acquires the target object behavior data in an event-driven manner, it first performs data preprocessing on the target behavior data, that is, preset data processing, to obtain corresponding conversion data, thereby updating the initial event and converting the data into a format that can be analyzed. Accordingly, the preset data processing in the embodiment of the present invention includes data cleaning and data format conversion. Among them, data cleaning in the embodiment of the present invention refers to filtering, denoising, and error correction operations on the acquired original event data, that is, the target object behavior data, to ensure the accuracy and consistency of the data. For example, data cleaning in the embodiment of the present invention may include removing duplicate data, missing or outlier processing, and data error correction, etc., by removing duplicate data to alleviate the problem of repeated analysis and processing, and by interpolating or filling missing values ​​to alleviate the problem of missing data values, or by deleting or replacing outliers to alleviate the problem of abnormal data values. In addition, the embodiment of the present invention can alleviate errors or consistency problems in the data by performing data error correction on the target object behavior data. Accordingly, data format conversion in the embodiment of the present invention refers to converting the original event data, i.e., the target object behavior data, into a specific data format. For example, in the embodiment of the present invention, the target object behavior data can be converted into a data format through one of the conversion operations of data type conversion, data structure conversion, and data standardization, so as to facilitate subsequent processing and analysis of the data. Among them, data type conversion in the embodiment of the present invention refers to converting the data type of the target object behavior data, such as converting character type data into numeric type data. Data structure conversion in the embodiment of the present invention refers to converting the target object behavior data from a certain data structure to a preset data structure. In addition, data standardization in the embodiment of the present invention refers to formatting the target object behavior data according to a preset standard to meet the needs of subsequent processing or storage. It is easy to understand that the embodiment of the present invention can effectively ensure data quality by performing preset data processing on the target object behavior data to obtain converted data, thereby reducing the cost of subsequent data analysis and improving data analysis efficiency.

[0077] 5 , in some embodiments of the present invention, before executing the step of processing the event to be processed by the corresponding event handler to obtain the execution result, the target object portrait construction method provided by the embodiment of the present invention further includes but is not limited to the following steps:

[0078] S510: Determine whether the event to be processed meets the precondition.

[0079] S520: When it is determined that the event to be processed meets the precondition, the corresponding event to be processed is received through the event processor.

[0080] In this specific embodiment, before the event processor receives the pending event and processes it, the embodiment of the present invention first needs to determine whether the pending event meets the preconditions. Specifically, in the embodiment of the present invention, the specific behaviors of the target object are all materialized as corresponding behavior nodes in the behavior tree, that is, the corresponding event processors, and each behavior node is set with corresponding preconditions. Among them, the preconditions in the embodiment of the present invention refer to the conditions that need to be met before establishing the relationship between the current node and the next node, that is, the prerequisites that need to be met for connecting the event processor. Accordingly, when it is determined that the pending event meets the preconditions, the embodiment of the present invention receives the corresponding pending event through the event processor, and then can verify or process the corresponding pending event. It is easy to understand that before the corresponding event processor receives the pending event, it first determines whether the current state of the condition meets the implementation state of the event processor through the preconditions. By judging the preconditions, it can ensure that all behavior nodes are performing actual operation behaviors.

[0081] 5 and 6 , in some embodiments of the present invention, when it is determined that the event to be processed meets the precondition, the event processor receives the corresponding event to be processed, including but not limited to the following steps:

[0082] S610: When it is determined that the event to be processed meets a first preset condition, the event processor receives the corresponding event to be processed, wherein the first preset condition includes execution success or execution failure.

[0083] S620: When the event to be processed meets a second preset condition, the event processor receives the corresponding event to be processed, wherein the second preset condition includes a preset number of sub-conditions.

[0084] In this specific embodiment, the preconditions of the present invention include a first preset condition and a second preset condition. When the pending event satisfies the first or second preset condition, the present invention receives the pending event through the corresponding event handler. Specifically, the first preset condition in the present invention includes execution success or execution failure. It is readily understood that the execution results in the first preset condition in the present invention only include execution success or execution failure, and no other operations are performed. That is, the precondition does not perform operations other than success or failure, thereby ensuring that all behavior nodes perform actual operations. Furthermore, the second preset condition in the present invention includes a predetermined number of subconditions. It is readily understood that the preconditions in the present invention may include multiple subconditions. When a predetermined number of these subconditions meet the predetermined requirements, the pending event is deemed to meet the second preset condition, and the corresponding pending event is received by the event handler. For example, in the present invention, the precondition includes four subconditions. Before receiving the pending event, the event handler first evaluates the four subconditions of the precondition to determine whether the pending event meets the preconditions. If the condition threshold is three-quarters, then when it is determined that three sub-conditions in the precondition are satisfied, it is considered that the event to be processed meets the second preset condition, and the corresponding event to be processed is received by the event processor. Conversely, when it is determined that the number of sub-conditions that meet the conditions in the precondition is less than three-quarters of the total number of sub-conditions, it is considered that the event to be processed does not meet the second preset condition, and the event processor does not accept the event to be processed. For another example, if the condition threshold is 2, then when it is determined that two or more sub-conditions in the precondition are satisfied, it is considered that the event to be processed meets the second preset condition, and the event processor receives the event to be processed. Conversely, when the number of sub-conditions that meet the precondition is less than 2, it is considered that the event to be processed does not meet the second preset condition, and therefore the event processor does not accept the event to be processed. It is easy to understand that the embodiment of the present invention can select the corresponding behavior node for event processing by judging the precondition, and then update the relevant nodes of the behavior tree, realize dynamic adjustment and optimization of the behavior tree, and make the constructed target object portrait more accurate.

[0085] Refer to Figure 7, which is a schematic diagram of the target object profiling system architecture provided by the present invention. The target object profiling system architecture of the present invention embodiment is constructed using a preset event-driven model to create a highly scalable and high-performance application system. Accordingly, the target object profiling system of the present invention embodiment employs a mediator topology, managing and controlling the workflow of initial events through event mediation. Furthermore, the present invention embodiment first analyzes and organizes target object usage behavior events to construct behavior event data, including several target object behavior events, such as device verification, device binding, and device login. Next, the present invention embodiment creates a first behavior tree based on the behavior event data. The first behavior tree includes several behavior nodes, each corresponding to a target object behavior event in the behavior event data. The present invention embodiment then acquires the target object behavior data using the preset event-driven model. Specifically, the preset event-driven model monitors events occurring in the system and receives the target object behavior data asynchronously. Accordingly, upon receiving the target object behavior data, the present invention embodiment updates the first behavior tree based on the target object behavior data, thereby generating a second behavior tree. Specifically, after asynchronously receiving a target object behavior event, i.e., the target object behavior data, the embodiment of the present invention uses this as the initial time to initiate the entire event flow. First, the embodiment of the present invention sends each behavior event in the target object's selected data to an event queue, generating an initial event queue. Next, the embodiment of the present invention manages and controls each behavior event in the event queue through an event broker, selecting a corresponding event channel and processing the behavior event through the corresponding behavior node processor, thereby updating the behavior nodes in the first behavior tree and generating a second behavior tree. The embodiment of the present invention generates corresponding pending events based on each behavior event in the initial event queue through the event broker and then sends them to the corresponding event channel, enabling the corresponding behavior node processor, i.e., the event processor, to process the pending events. Accordingly, each behavior node in the embodiment of the present invention returns the corresponding execution result to the event broker after processing is completed. Furthermore, each behavior node in the embodiment of the present invention supports interrupt operations for any process, enabling the selection node, i.e., the event broker, to make selections and decisions. Next, the embodiment of the present invention updates the structure of the first behavior tree based on the returned execution results, thereby constructing the second behavior tree.

[0086] Furthermore, before sending each behavioral event in the target object's behavioral data to the initial event queue, embodiments of the present invention first perform preset data processing on the target object's behavioral data to obtain corresponding converted data. For example, in embodiments of the present invention, the preset data processing includes data cleaning or data format conversion. Furthermore, before the event processor receives the corresponding pending event, embodiments of the present invention first determine whether the pending event satisfies a precondition. Only when it is determined that the pending event satisfies the precondition does the event processor receive the corresponding pending event. Specifically, in embodiments of the present invention, the precondition includes a first precondition and a second precondition. When the pending event satisfies either the first precondition or the second precondition, the event processor receives the corresponding pending event. In embodiments of the present invention, the first precondition includes execution success or execution failure, while the second precondition includes satisfying a preset number of subconditions. Finally, embodiments of the present invention construct a target object profile by analyzing the second behavior tree. In embodiments of the present invention, the target object profile processor performs target object pattern analysis based on the second behavior function and the corresponding execution results to construct the target object profile.

[0087] For example, referring to Figure 8 , taking the application scenario of binding a target object to a device as an example, after the target object is bound to the device, an initial event is generated by a preset event-driven module in an embodiment of the present invention. This initial event is then sent to a dedicated event channel connected between two nodes defined in the first behavior tree, where the event information is transmitted through this event channel. Accordingly, upon receiving the initial event, the event mediator in an embodiment of the present invention generates a corresponding pending event for device verification and sends this pending event to the device verification event channel. Before the device verification event processor receives this pending event, the embodiment of the present invention first determines whether it meets the preconditions and then prioritizes determining whether the current state of the pending event matches the processor's implementation state. Next, the embodiment of the present invention determines whether the device type is correct and whether the device has been bound to other target objects. If the pending event is determined to meet the conditions, the device verification event processor receives and verifies the pending event and then returns the execution result, i.e., a confirmation message, to the event mediator. Similarly, the query room event processor and the binding device processor in an embodiment of the present invention also perform the aforementioned steps and return the corresponding execution results, which will not be described in detail here. Furthermore, after the event mediator obtains the successful execution results of the previous steps, the embodiment of the present invention continues to execute the target object portrait processor to analyze the characteristic information of the target object and understand the behavior pattern of the target object according to the corresponding behavior tree, thereby constructing the corresponding target object portrait.

[0088] 9 , an embodiment of the present invention further provides a target object portrait construction system, including:

[0089] The first module 710 is used to analyze the target object's usage behavior events and construct behavior event data, wherein the behavior event data includes a number of target object behavior events.

[0090] The second module 720 is configured to create a first behavior tree based on the behavior event data, wherein the first behavior tree includes a plurality of behavior nodes corresponding to the target object behavior events.

[0091] The third module 730 is configured to obtain target object behavior data through a preset event-driven model, and to update the first behavior tree according to the target object behavior data to generate a second behavior tree.

[0092] The fourth module 740 is configured to construct a target object portrait by analyzing the second behavior tree.

[0093] The contents of the method embodiments of the present invention are all applicable to the system embodiments. The functions specifically implemented by the system embodiments are the same as those of the above method embodiments, and the beneficial effects achieved are also the same as those achieved by the above methods.

[0094] 10 , an embodiment of the present invention further provides a target object portrait construction system, including:

[0095] At least one processor 810 .

[0096] At least one memory 820 is configured to store at least one program.

[0097] When at least one program is executed by at least one processor 810, the at least one processor 810 implements the target object portrait construction method described in the above embodiment.

[0098] The contents of the method embodiments of the present invention are all applicable to the system embodiments. The functions specifically implemented by the system embodiments are the same as those of the above method embodiments, and the beneficial effects achieved are also the same as those achieved by the above methods.

[0099] An embodiment of the present invention also provides a computer-readable storage medium, which stores computer-executable instructions, and the computer-executable instructions are executed by one or more control processors, for example, to execute the steps of the target object portrait construction method described in the above embodiment.

[0100] The contents of the method embodiments of the present invention are all applicable to the system embodiments. The functions specifically implemented by the system embodiments are the same as those of the above method embodiments, and the beneficial effects achieved are also the same as those achieved by the above methods.

[0101] The terms "first", "second", "third", "fourth", etc. (if any) in the specification of the present application and the above-mentioned drawings are used to distinguish similar objects and are not necessarily used to describe a specific order or sequential order. It should be understood that the data used in this way can be interchangeable where appropriate, so that the embodiments of the present application described herein can, for example, be implemented in an order other than those illustrated or described herein. In addition, the terms "including" and "having" and any variations thereof are intended to cover non-exclusive inclusions, for example, a process, method, system, product or device that includes a series of steps or units is not necessarily limited to those steps or units clearly listed, but may include other steps or units that are not clearly listed or inherent to these processes, methods, products or devices.

[0102] It should be understood that in this application, "at least one (item)" means one or more, and "plurality" means two or more. "And / or" is used to describe the association relationship of associated objects, indicating that three relationships may exist. For example, "A and / or B" can mean: only A exists, only B exists, and A and B exist at the same time, where A and B can be singular or plural. The character " / " generally indicates that the previous and next associated objects are in an "or" relationship. "At least one of the following items" or similar expressions refers to any combination of these items, including any combination of single items or plural items. For example, at least one of a, b or c can mean: a, b, c, "a and b", "a and c", "b and c", or "a and b and c", where a, b, c can be single or multiple.

[0103] In the several embodiments provided in this application, it should be understood that the disclosed systems, devices and methods can be implemented in other ways. For example, the device embodiments described above are merely schematic. For example, the division of the units is merely a logical function division. In actual implementation, there may be other division methods, such as multiple units or components can be combined or integrated into another system, or some features can be ignored or not executed. Another point is that the mutual coupling or direct coupling or communication connection shown or discussed can be an indirect coupling or communication connection through some interfaces, devices or units, which can be electrical, mechanical or other forms.

[0104] The units described as separate components may or may not be physically separate, and the components shown as units may or may not be physical units, that is, they may be located in one place or distributed across multiple network units. Some or all of these units may be selected to achieve the purpose of this embodiment according to actual needs.

[0105] In addition, the functional units in the various embodiments of the present application may be integrated into a single processing unit, or each unit may exist physically separately, or two or more units may be integrated into a single unit. The aforementioned integrated units may be implemented in the form of hardware or software functional units.

[0106] Those skilled in the art will appreciate that all or some of the steps and systems in the method disclosed above can be implemented as software, firmware, hardware, and appropriate combinations thereof. Some physical components or all physical components can be implemented as software executed by a processor, such as a central processing unit, a digital signal processor, or a microprocessor, or implemented as hardware, or implemented as an integrated circuit, such as an application-specific integrated circuit. Such software can be distributed on a computer-readable medium, and the computer-readable medium can include computer storage media (or non-transitory media) and communication media (or temporary media). As known to those skilled in the art, the term computer storage media is included in any method or technology for storing information (such as computer-readable instructions, data structures, program modules, or other data) and is volatile and non-volatile, removable, and non-removable. Computer storage media includes, but is not limited to, RAM, ROM, EEPROM, flash memory, or other memory technology, CD-ROM, digital versatile disks (DVD), or other optical disk storage, magnetic cassettes, magnetic tapes, disk storage, or other magnetic storage devices, or any other medium that can be used to store desired information and can be accessed by a computer. Furthermore, as is well known to those skilled in the art, communication media typically embodies computer-readable instructions, data structures, program modules, or other data in a modulated data signal such as a carrier wave or other transport mechanism, and may include any information delivery media.

[0107] The step numbers in the above method embodiment are only provided for the convenience of explanation and do not limit the order of the steps. The execution order of each step in the embodiment can be adaptively adjusted according to the understanding of those skilled in the art.

[0108] The above is a specific description of the preferred implementation of the present application, but the present application is not limited to the embodiments. Those skilled in the art may make various equivalent modifications or substitutions without violating the spirit of the present application. These equivalent modifications or substitutions are all included in the scope defined by the claims of the present application.

Claims

1. A method for constructing a target object portrait, characterized in that: The following steps are involved: Analyze the target object's usage behavior events to construct behavior event data; wherein the behavior event data includes a number of target object behavior events; Creating a first behavior tree according to the behavior event data; wherein the first behavior tree includes a plurality of behavior nodes, and the behavior nodes correspond to the target object behavior events; Acquire target object behavior data through a preset event-driven model, so as to update the first behavior tree according to the target object behavior data and generate a second behavior tree; The target object portrait is constructed by analyzing the second behavior tree.

2. The target object portrait construction method according to claim 1, characterized in that: The preset event-driven model includes an intermediary topology structure; The updating the first behavior tree according to the target object behavior data to generate a second behavior tree includes: Each behavior event in the target object behavior data is sent to an initial event queue, and managed and controlled through an event intermediary to select the corresponding behavior node in the first behavior tree to generate the second behavior tree; wherein the event intermediary includes a control node of the first behavior tree, and the node type of the control node includes a selection node.

3. The target object portrait construction method according to claim 2, characterized in that: The managing and controlling through the event mediator to select the corresponding behavior node in the first behavior tree to generate the second behavior tree includes: Generate corresponding pending events through the event mediator according to each behavior event in the initial event queue, and send them to the corresponding event channel, so that the pending events are processed by the corresponding event processor to obtain the execution result; The structure of the first behavior tree is updated according to the execution result to generate the second behavior tree.

4. The method for constructing a target object portrait according to claim 3, characterized in that: The step of constructing the target object portrait by analyzing the second behavior tree includes: A target object behavior pattern analysis is performed through a target object portrait processor according to the second behavior tree and the execution result to generate the target object portrait.

5. The method for constructing a target object portrait according to claim 2, characterized in that: Before executing the step of sending each behavior event in the target object behavior data to the initial event queue, the method further includes: Perform preset data processing on the target object behavior data to obtain conversion data; wherein the preset data processing includes data cleaning and data format conversion.

6. The method for constructing a target object portrait according to claim 3, characterized in that: Before executing the step of processing the event to be processed by the corresponding event processor to obtain the execution result, the method further includes: Determine whether the event to be processed meets the precondition; When it is determined that the event to be processed meets the precondition, the corresponding event to be processed is received by the event processor.

7. The method for constructing a target object portrait according to claim 6, characterized in that: When it is determined that the event to be processed satisfies the precondition, receiving the corresponding event to be processed through the event processor includes: When it is determined that the event to be processed meets a first preset condition, the event to be processed corresponding to the event is received by the event processor; wherein the first preset condition includes execution success or execution failure; Alternatively, when the event to be processed meets a second preset condition, the corresponding event to be processed is received by the event processor; wherein the second preset condition includes sub-conditions that meet a preset number.

8. A target object portrait construction system, characterized in that: include: The first module is used to analyze the target object's usage behavior events and construct behavior event data; wherein the behavior event data includes a number of target object behavior events; A second module is used to create a first behavior tree according to the behavior event data; wherein the first behavior tree includes a plurality of behavior nodes, and the behavior nodes correspond to the target object behavior events; A third module is used to obtain target object behavior data through a preset event-driven model, so as to update the first behavior tree according to the target object behavior data and generate a second behavior tree; The fourth module is used to construct the target object portrait by analyzing the second behavior tree.

9. A target object portrait construction system, characterized in that: include: at least one processor; at least one memory for storing at least one program; When the at least one program is executed by the at least one processor, the at least one processor implements the target object portrait construction method as described in any one of claims 1 to 7.

10. A computer storage medium storing a program executable by a processor, characterized in that: The program executable by the processor is used to implement the target object portrait construction method as described in any one of claims 1 to 7 when executed by the processor.

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