User behavior path construction method and system

Abstract

The embodiment of the invention provides a user behavior path construction method and system, and the method comprises the steps: obtaining user behavior data related to a target service item, and obtaining behavior event data and user group data through cleaning the user behavior data; in response to a project detection request submitted for the target service project, extracting target event detail data from the behavior event data according to the user group data; constructing a user behavior path according to the target event detail data, and segmenting the user behavior path into a target user behavior path according to a session segmentation strategy; and constructing path visualization information corresponding to the project detection request based on the target user behavior path.

Description

Technical Field

[0001] The embodiments of this specification relate to the technical field of data processing, and particularly to a method and system for constructing a user behavior path. Background Art

[0002] With the development of computer and Internet technologies, in order to provide users with more stable and better service items, during the experience optimization stage of service items, a fine-grained service item analysis method is usually adopted for optimization. Most of this implementation is based on the existing method of combining data logging with manual processing. Non-technical personnel (product personnel, operation personnel) sort out data analysis requirements, record information such as events and statistical indicators, and then hand them over to R & D personnel. The R & D personnel write SQL according to the requirements and submit it to the data processing service to calculate the results. Then, the visualization information corresponding to the service item is generated through the report tool of the service item, so as to complete the optimization operation of the service item in combination with the visualization information. However, during this process, for demand adjustment and new demand, data R & D resources need to be involved, which will correspondingly bring higher costs. At the same time, this processing method has low flexibility and is not friendly to other personnel except technical personnel; therefore, an effective solution is urgently needed to solve the above problems. Summary of the Invention

[0003] In view of this, the embodiments of this specification provide a method for constructing a user behavior path. One or more embodiments of this specification also relate to a device for constructing a user behavior path, a system for constructing a user behavior path, a computing device, a computer-readable storage medium, and a computer program product to solve the technical defects existing in the prior art.

[0004] According to the first aspect of the embodiments of this specification, a method for constructing a user behavior path is provided, including:

[0005] Obtain user behavior data associated with a target service item, and obtain behavior event data and user group data by cleaning the user behavior data;

[0006] In response to a project detection request submitted for the target service item, extract target event detail data from the behavior event data according to the user group data;

[0007] Construct a user behavior path according to the target event detail data, and segment the user behavior path into target user behavior paths according to a session segmentation strategy;

[0008] Construct path visualization information corresponding to the project detection request based on the target user behavior path.

[0009] According to the second aspect of the embodiments of the present specification, a user behavior path construction device is provided, including:

[0010] An acquisition module, configured to acquire user behavior data associated with a target service item, and obtain behavior event data and user group data by cleaning the user behavior data;

[0011] An extraction module, configured to, in response to a project detection request submitted for the target service item, extract target event detail data from the behavior event data according to the user group data;

[0012] A segmentation module, configured to construct a user behavior path according to the target event detail data, and segment the user behavior path into target user behavior paths according to a session segmentation strategy;

[0013] A construction module, configured to construct path visualization information corresponding to the project detection request based on the target user behavior path.

[0014] According to the third aspect of the embodiments of the present specification, a user behavior path construction system is provided, including a client and a server, including:

[0015] The server is configured to acquire user behavior data associated with a target service item, and obtain behavior event data and user group data by cleaning the user behavior data; store the behavior event data and the user group data in a target database;

[0016] The client is configured to receive a project detection request submitted for the target service item, and send the project detection request to the server;

[0017] The server is configured to access the target database according to the project detection request, and extract target event detail data from the behavior event data according to the user group data; construct a user behavior path according to the target event detail data, and segment the user behavior path into target user behavior paths according to a session segmentation strategy; construct path visualization information corresponding to the project detection request based on the target user behavior path; send the path visualization information to the client;

[0018] The client is configured to receive the path visualization information and display it.

[0019] According to the fourth aspect of the embodiments of the present specification, a computing device is provided, including:

[0020] A memory and a processor;

[0021] The memory is used to store computer-executable instructions, and the processor is used to execute the computer-executable instructions. When the computer-executable instructions are executed by the processor, the steps of the above-mentioned user behavior path construction method are implemented.

[0022] According to the fifth aspect of the embodiments of the present specification, a computer-readable storage medium is provided, which stores computer-executable instructions. When the instructions are executed by a processor, the steps of the above-mentioned user behavior path construction method are implemented.

[0023] According to the sixth aspect of the embodiments of the present specification, a computer program product is provided, including a computer program or instructions. When the computer program or instructions are executed by a processor, the steps of the above-mentioned user behavior path construction method are implemented.

[0024] In order to reduce cost investment and improve the detection flexibility of service items, the user behavior path construction method provided in this embodiment can first obtain user behavior data associated with the target service item, so as to obtain behavior event data and user group data by cleaning the user behavior data, and achieve data standardization without introducing additional buried points. Then, in response to a project detection request submitted for the target service item, target event detail data can be extracted from the behavior event data according to the user group data, so that the extracted target event detail data can be directly used. Then, a user behavior path associated with the target service item can be constructed based on the target event detail data. At this time, considering that the user behavior path is not coherent in time, in order to avoid the confusion of project detection caused by this problem, the user behavior path can be segmented into target user behavior paths according to the session segmentation strategy. Thus, the specific behaviors of each user in the target service item can be intuitively and accurately reflected through the target user behavior paths. Then, path visualization information corresponding to the project detection request can be constructed based on the target user behavior paths. It can be realized that without introducing additional resources, the path visualization information can be constructed quickly and accurately, which is more convenient for downstream optimization and analysis of the target service item. And this user behavior path construction method has higher flexibility and can adapt to different types of service items, thereby effectively improving the optimization efficiency of the service items of the service provider. Description of the Drawings

[0025] Figure 1 is a schematic diagram of a user behavior path construction method provided by an embodiment of the present specification;

[0026] Figure 2 is a flowchart of a user behavior path construction method provided by an embodiment of the present specification;

[0027] Figure 3a is a schematic diagram of the storage of event detail data in a user behavior path construction method provided by an embodiment of the present specification;

[0028] Figure 3b It is a schematic diagram of user behavior path construction in a user behavior path construction method provided by an embodiment of this specification;

[0029] Figure 3c It is a schematic diagram of path visualization information in a user behavior path construction method provided by an embodiment of this specification;

[0030] Figure 4 It is a flowchart of the processing procedure of a user behavior path construction method provided by an embodiment of this specification;

[0031] Figure 5 It is a schematic structural diagram of a user behavior path construction device provided by an embodiment of this specification;

[0032] Figure 6 It is a schematic structural diagram of a user behavior path construction system provided by an embodiment of this specification;

[0033] Figure 7 It is a structural block diagram of a computing device provided by an embodiment of this specification. Detailed implementation manners

[0034] Many specific details are set forth in the following description in order to provide a thorough understanding of this specification. However, this specification can be implemented in many other ways different from those described herein, and those skilled in the art can make similar extensions without departing from the connotation of this specification. Therefore, this specification is not limited by the specific implementations disclosed below.

[0035] The terms used in one or more embodiments of this specification are only for the purpose of describing specific embodiments and are not intended to limit one or more embodiments of this specification. The singular forms "a", "the", and "said" used in one or more embodiments of this specification and the appended claims are also intended to include the plural forms unless the context clearly dictates otherwise. It should also be understood that the term "and / or" used in one or more embodiments of this specification refers to and includes any or all possible combinations of one or more of the associated listed items.

[0036] It should be understood that although the terms first, second, etc. may be used in one or more embodiments of this specification to describe various information, such information should not be limited to these terms. These terms are only used to distinguish the same type of information from each other. For example, without departing from the scope of one or more embodiments of this specification, the first may also be referred to as the second, and similarly, the second may also be referred to as the first. Depending on the context, the word "if" as used herein may be interpreted as "when" or "while" or "in response to determining".

[0037] In addition, it should be noted that the user information (including but not limited to user device information, user personal information, etc.) and data (including but not limited to data for analysis, stored data, displayed data, etc.) involved in one or more embodiments of this specification are all information and data that have been authorized by the user or fully authorized by all parties. Moreover, the collection, use, and processing of relevant data need to comply with the relevant laws, regulations, and standards of the relevant countries and regions, and corresponding operation entrances are provided for users to choose to authorize or refuse.

[0038] First, the noun terms involved in one or more embodiments of this specification are explained.

[0039] SQL (Structured Query Language) is a standard programming language for managing and operating relational databases. It allows users to perform various data operations such as querying, updating, inserting, deleting, etc. SQL is widely used in various database management systems (DBMS), such as MySQL, PostgreSQL, SQLite, Oracle, Microsoft SQLServer, etc.

[0040] Event: It is a specific behavior that occurs when a user interacts with a product, service, or application. These events are usually used to track and analyze users' usage habits, preferences, and conversion processes to optimize the user experience and improve effectiveness. For example: page exposure, button click, block exposure, etc.

[0041] Event attribute: It refers to the detailed information associated with a specific event, which helps to further understand and segment the situation of users completing the event. For example: operating system, App version number, city, source, etc.

[0042] User path: It is a term specifically used to describe a series of steps or interaction processes that a user experiences when passing through a product, service, or website to achieve a specific goal. By analyzing and optimizing the user path, product managers can improve the overall user experience, reduce frustration, and increase the conversion rate.

[0043] Session: It refers to a series of interactions of a user with a website, application, or online service within a specific time period. A session starts when the user enters the website or application and ends when the user leaves or there is no further activity within a certain time (usually referred to as session timeout). It is a basic unit for evaluating user behavior because it reflects the overall experience of a user's single visit.

[0044] Holo Data Warehouse: (Hologres) is a one-stop real-time data warehouse that provides data storage and real-time analysis capabilities. Hologres supports multiple storage types, including row storage, column storage, and coexistence of rows and columns, as well as multiple index types to meet the performance requirements in different scenarios. At the same time, Hologres is also compatible with the PostgreSQL ecosystem and supports a variety of extensions and development tools.

[0045] MySQL: is a relational database management system that uses a relational model to store data, which means that data is organized into tables, and relationships can be established between tables through specific fields (such as foreign keys).

[0046] In this specification, a method for constructing a user behavior path is provided. This specification also relates to a device for constructing a user behavior path, a system for constructing a user behavior path, a computing device, a computer-readable storage medium, and a computer program product, which will be described in detail one by one in the following embodiments.

[0047] See Figure 1 the schematic diagram shown. For the method for constructing a user behavior path provided in this embodiment, in order to reduce cost investment and improve the detection flexibility of service items, user behavior data associated with the target service item can be obtained first to achieve obtaining behavior event data and user group data by cleaning the user behavior data, and completing data normalization without introducing additional buried points. Then, in response to a project detection request submitted for the target service item, target event detail data can be extracted from the behavior event data according to the user group data; so that the extracted target event detail data can be directly used. Thus, a user behavior path associated with the target service item can be constructed based on the target event detail data. At this time, considering that the user behavior path is not coherent in time, in order to avoid the confusion of project detection caused by this problem, the user behavior path can be segmented into target user behavior paths according to the session segmentation strategy; thus, the specific behaviors of each user in the target service item can be intuitively and accurately reflected through the target user behavior paths. Then, path visualization information corresponding to the project detection request can be constructed based on the target user behavior paths. It can be realized that without introducing additional resources, the construction of path visualization information can be completed quickly and accurately, which is more convenient for downstream optimization and analysis of the target service item. And this method for constructing a user behavior path has higher flexibility and can adapt to different types of service items, thereby effectively improving the optimization efficiency of the service items of the service provider.

[0048] See Figure 2 , Figure 2 shows a flowchart of a method for constructing a user behavior path according to an embodiment of this specification, which specifically includes the following steps.

[0049] Step S202: Obtain the user behavior data associated with the target service project, and obtain behavior event data and user group data by cleaning the user behavior data.

[0050] The user behavior path construction method provided in this embodiment can be applied to any service project, such as a project that provides logistics services to users, a project that provides shopping services to users, a project that provides video viewing services to users, a project that provides trading services to users, etc. By processing the user behavior data associated with the target service project, it supports extracting the user behavior path based on the user behavior data when there is a need to optimize the service project, so as to construct path visualization information in combination with the user behavior path, enabling the service provider to understand the relevant optimization directions of the associated service project in combination with the path visualization information, such as user behavior intentions, traffic source analysis, churn point identification, abnormal path detection, user behavior differences, user feature comparison, etc. Furthermore, the optimized service project can provide high-quality services to users.

[0051] In this embodiment, taking the target service project as a logistics service project as an example, the user behavior path construction method is described. For the description of the user behavior path construction method in other service scenarios, the same or corresponding description content in this embodiment can be referred to, and this embodiment will not elaborate too much here.

[0052] Specifically, the target service project specifically refers to a project that provides services to users, which is carried by an application program, a web page or a mini-program installed on a terminal device, enabling users to participate in the target service project by using the application program, the web page or the mini-program, and thus obtaining the project services provided by the target service project, such as logistics functions, trading functions, shopping functions, query functions, translation functions, video browsing functions, text reading functions, etc. Correspondingly, the user behavior data specifically refers to the behavior data corresponding to the users participating in the target service project, which is used to record every behavior operation performed by each user when participating in the target service project; for example, a series of operations such as a user using the logistics service, entering the application program, selecting the query logistics function, and inputting the order number will constitute the user behavior data, and in addition to the data recording the behavior actions in the user behavior data, it also includes the attribute data of the behavior actions, such as time, operation method, called function, called function, etc., which is used to accurately construct the behavior path of each user in combination with the user behavior data in the future, so as to reflect the path visualization information of the target service project and facilitate the downstream optimization and use of the service project.

[0053] Correspondingly, the behavioral event data specifically refers to the event description data representing user behavior operations obtained after cleaning the user behavior data. Correspondingly, the user group data specifically refers to the record data corresponding to different groups obtained by dividing the users participating in the target service project according to different needs, which is used to extract relevant event data in combination with the user group data after receiving the project detection request, so as to construct the user behavior path corresponding to the project detection request for use.

[0054] Based on this, in order to reduce cost investment and improve the detection flexibility of service projects, the user behavior data associated with the target service project can be obtained first, so as to obtain behavioral event data and user group data by cleaning the user behavior data, and achieve data standardization without introducing additional buried points. Then, in response to the project detection request submitted for the target service project, the target event detail data can be extracted from the behavioral event data according to the user group data, so that the extracted target event detail data can be directly used. Thus, the user behavior path associated with the target service project can be constructed based on the target event detail data. At this time, considering that the user behavior path is not coherent in time, in order to avoid the confusion of project detection caused by this problem, the user behavior path can be segmented into the target user behavior path according to the session segmentation strategy. Thus, the specific behavior of each user in the target service project can be intuitively and accurately reflected through the target user behavior path. Then, the path visualization information corresponding to the project detection request can be constructed based on the target user behavior path. It can be realized that without introducing additional resources, the path visualization information can be constructed quickly and accurately, which is more convenient for the downstream to optimize and analyze the target service project. And this user behavior path construction method has higher flexibility and can adapt to different types of service projects, thus effectively improving the service project optimization efficiency of the service provider.

[0055] Furthermore, in order to enable the behavioral event data and the user group data to be directly used when receiving the project detection request, the user behavior data can be cleaned to obtain standardized behavioral data, and then the behavioral event data and the user group data can be constructed. In this embodiment, the specific implementation method is as follows:

[0056] Perform data cleaning on the user behavior data according to the preset cleaning rules to obtain the target user behavior data, where the user behavior data is associated with different data sources of the target service project; determine the event detail data and event metadata, as well as the user data and user attribute data according to the target user behavior data; use the event detail data and the event metadata as the behavioral event data, and the user data and the user attribute data as the user group data.

[0057] Specifically, the cleaning rule specifically refers to the rule for cleaning the user behavior data related to the target service project into the data that meets the subsequent usage requirements. This rule can convert the user behavior data corresponding to different data sources of the target service project into the target user behavior data with the same standard, so as to perform project detection and analysis using the target user behavior data with the same standard subsequently. Correspondingly, the event detail data specifically refers to the description data corresponding to each event generated by each user participating in the target service project, and the event metadata specifically refers to the description data of each type of event. For example, if the event detail data records the behavior event details of different users clicking on the "A" control, the event metadata can record the behavior events of a large number of users clicking on the "A" control as one metadata, which is convenient for querying the target event detail data during the application stage. Correspondingly, the user data specifically refers to the description data corresponding to different defined user groups, and the user attribute data specifically refers to the attributes corresponding to different user groups. For example, if the target service project has n participating users, different users can be selected according to one or more conditions such as region, gender, new or old, age, occupation, and activity level, and different user groups can be obtained, and the type of each user group can be described by the attribute data.

[0058] Based on this, in order to be able to convert the user behavior data associated with the target service project into data that is convenient for constructing the user behavior path and support quickly extracting the corresponding detail data for analysis after receiving the project detection request subsequently. The user behavior data can be first cleaned according to the preset cleaning rule to obtain the target user behavior data, so that the user behavior data from different data sources can be unified into a standard to obtain the target user behavior data. On this basis, the event detail data and event metadata, as well as the user data and user attribute data, can be determined according to the target user behavior data. At this time, the event detail data and event metadata can be used as the behavior event data, and the user data and user attribute data can be used as the user group data; to achieve reflecting the behavior event details of each user through the event detail data, and reflecting each type of event through the event metadata; at the same time, reflecting the number of users included in different user groups through the user data, and reflecting the types of different user groups through the user attribute data, so as to facilitate subsequent project optimization use.

[0059] In summary, by combining the event detail data and event metadata to construct the behavior event data, and combining the user data and user attribute data to construct the user group data, the behavior event data and user group data can represent the overall project of the target service project, which is more convenient for subsequent use in constructing the user behavior path.

[0060] Further, when determining event metadata and event detail data, in order to support subsequent usage, the event metadata can be determined in a deduplication manner to improve subsequent data query efficiency. In this embodiment, the specific implementation method is as follows:

[0061] Determine event detail data according to the target user behavior data, and perform deduplication on the event detail data to obtain initial event metadata; perform semantic processing on the initial event metadata, and generate event metadata according to the semantic processing result; wherein, the event detail data is stored in the event detail table of the target service project, and the event metadata is stored in the event metadata table of the target service project.

[0062] Specifically, the initial event metadata specifically refers to that after obtaining the event detail data, considering that each event detail data corresponds to a behavior event, and a large number of event detail data may have the same behavior operation, so by deduplicating the event detail data, the final obtained event detail data can be reduced to only one type. At this time, the type of the remaining event detail data can be used as the initial event metadata, and this event metadata has not been semantically processed and its name cannot be defined. Correspondingly, performing semantic processing on the initial event metadata specifically refers to the processing operation of naming the metadata whose event type is difficult to define, and obtaining non-repetitive event metadata that can express its type attribute through semantic analysis. Correspondingly, the event detail table specifically refers to the data table that records event detail data, which can be implemented through the Holo data warehouse. Correspondingly, the event metadata table specifically refers to the data table that records event metadata, which can be implemented through the MYSQL database.

[0063] Based on this, in order to enable the behavior event data to meet subsequent usage requirements, the event detail data can be determined first according to the target user behavior data. At this time, the initial event metadata with type representation meaning can be obtained by deduplicating the event detail data; on this basis, considering that the original selling points generally identify events through event codes, and it is difficult to understand the specific meaning of events by using event codes, so semantic processing can be performed on the initial event metadata, and event metadata can be generated according to the semantic processing result; by semanticizing events, each type of event can be named, such as code: btn1_click can be named "button 1 click", thereby making the subsequent project detection and processing more efficient. Moreover, the event detail data is stored in the event detail table of the target service project, and the event metadata is stored in the event metadata table of the target service project.

[0064] In practical applications, event metadata can be recorded into the event metadata table through a data model, while event detail data can be recorded into the event detail table through an offline data model. For example, the table name of the event detail table is {dwd_user_behavior_event_detail_di_${tenantId}}, and the content it records is as shown in Table (1) below:

[0065] Field Name Field Type Description Nullable log_id string Log ID No event_code string Event code No local_timestamp bigint Client local timestamp No … … … … data_channel int Data collection channel No (1)

[0067] On this basis, it is possible to persist the event detail data and event metadata of the target service project for use in the project detection phase.

[0068] For example, in a product that provides logistics services, in order to facilitate product optimization, event data related to logistics services can be collected and stored during the optimization phase. As Figure 3a shown in the schematic diagram, after collecting the original user behavior data corresponding to the logistics service project through data points 1 (such as code points preset in an application or web page for collecting user behavior data), 2 (such as basic data collection points in a user behavior tracking system), and 3 (such as code snippets preset in an application or web page for collecting and analyzing user behavior, system performance, etc.) of the logistics service project, the original user behavior data from different data sources can be sorted into user behavior data with a unified standard through cleaning rules. Then, the user behavior data can be processed through a data processing service to obtain event detail data and event metadata. Furthermore, the event detail data can be synchronized to the event detail table Holo that stores the global event detail data associated with the logistics service project; and the event metadata can be synchronized to the event metadata table MYSQL that stores the global event metadata associated with the logistics service project. At the same time, semantic processing can be applied to the newly added event metadata in the event metadata table MYSQL to name the event metadata whose specific meaning is difficult to understand, thus facilitating subsequent use.

[0069] Furthermore, in order to facilitate downstream services to optimize the logistics service project, the users and user attributes corresponding to the logistics service project can also be selected through a user selection platform to obtain different user groups and the user attributes corresponding to different user groups, such as male groups in region A, female groups in region A, groups aged 18 - 20, groups aged over 25, etc., so as to reuse the selected groups to extract event detail data for logistics service optimization later.

[0070] In summary, by processing the user behavior data of the target service project, the user group data of the corresponding users and the behavior event data of the corresponding events can be obtained, so that when constructing the user behavior path in response to the project detection request, the required detailed data can be quickly selected, thereby effectively improving the project detection efficiency.

[0071] Step S204: In response to the project detection request submitted for the target service project, extract the target event detailed data from the behavior event data according to the user group data.

[0072] Specifically, after the above-mentioned processing and persistence of the user behavior data of the target service project, if a project inspection request submitted for the target service project is received, it means that at this time, the target service project needs to be analyzed according to the project detection request, and then the path visualization information matching the project detection request is constructed for the downstream to optimize the target service project according to the path visualization information. Before that, the detailed event data associated with the project detection request needs to be extracted for subsequent analysis. Therefore, in order to ensure the accuracy and efficiency of data extraction, the target event detailed data can be extracted from the behavior event data according to the user group data in response to the project detection request submitted for the target service project, ensuring that the extracted target event detailed data can meet the detection requirements of the project detection request, and then constructing the path visualization information matching the project detection request for the downstream to optimize and analyze the target service project.

[0073] Among them, the project detection request specifically refers to the request submitted when optimizing and analyzing the target service project, and this request includes, but is not limited to, path detection requests, traffic detection requests, churn detection requests, abnormal path detection requests, behavior difference detection requests, etc., for performing different types of detection and processing on the target service project. Correspondingly, the target event detailed data specifically refers to the event detailed data that meets the current project detection requirements filtered out from the above-recorded behavior event data in response to the project detection request; it can be understood as the detection requirement parameters related to the project detection request. According to this parameter, the user group and the event filtering parameters can be determined, and combined with this part of information, the target event detailed data can be extracted from the behavior event data for subsequent detection and processing operations corresponding to the project detection request.

[0074] Furthermore, when extracting the target event detailed data in response to the project detection request, considering that the behavior event data contains the global event detailed data of the target service project, the target group sub-data can be determined first, and then the target event metadata can be determined, and then the target event detailed data can be accurately hit, thereby improving the data extraction efficiency. In this embodiment, the specific implementation method is as follows:

[0075] Receive a project detection request submitted for the target service project, and obtain detection parameters by parsing the project detection request; screen target group sub-data from the user group data according to the detection parameters; determine target event metadata in the behavior event data according to the target group sub-data, and extract target event detail data from the behavior event data based on the target event metadata.

[0076] Specifically, the detection parameters specifically refer to the parameters in the project detection request for screening data that meets the project detection requirements, including but not limited to session time, event information, participating events, time information, screening range information, etc., to ensure that the extracted target event detail data meets the current project detection requirements. Correspondingly, the target group sub-data specifically refers to the description data corresponding to the user group in the user group data that meets the current project detection requirements. Correspondingly, the target event metadata specifically refers to the event metadata for screening event detail data that meets the current project detection requirements.

[0077] Based on this, after receiving a project detection request submitted for the target service project, in order to be able to extract target event detail data that meets the current project detection requirements in response to the project detection request, the project detection request can be parsed first to obtain detection parameters; the data range to be used can be determined through the detection parameters. Then, the target group sub-data can be screened from the user group data according to the detection parameters; then the target event metadata can be determined in the behavior event data according to the target group sub-data, and then the types covered by the event detail data can be determined. Finally, the target event detail data can be extracted from the behavior event data based on the target event metadata, so as to construct path visualization information for the subsequent optimization use of the target service project.

[0078] Continuing with the above example, after storing the event detail data and event metadata in the data table, the data in the data table can be used for the subsequent optimization use of the logistics service project. When receiving a detection request for the logistics service project, parameters such as session events, start events, end events, participating events, user groups, etc. can be determined by parsing the detection request. Then, the event metadata table MYSQL can be accessed according to the above parameters to determine the hit metadata. After that, the event detail table Holo can be accessed using the metadata, and the event detail data corresponding to the users hit by this detection request can be read in the event detail table. This embodiment illustrates the user behavior path construction method with the hit users including User 1 and User 2 as an example. Specifically, the obtained target event detail data is shown in the following table (2):

[0079] User ID (UID) Event code (event_code) 1 a 1 b 1 c 1 c 1 d 1 a 2 a 2 b 2 b (2)

[0081] Among them, 1 and 2 represent User 1 and User 2, and a, b, c, and d represent the specific operation event names performed by the users in the logistics application. After obtaining the target event detail data corresponding to the above detection requirements, subsequent path construction processing can be carried out.

[0082] In summary, by combining the detection parameters in the project detection request to extract the target event detail data, and the extraction process has a more standardized path operation, which can effectively improve the extraction accuracy of the event detail data and can effectively improve the subsequent processing efficiency.

[0083] Step S206: Construct a user behavior path according to the target event detail data, and split the user behavior path into target user behavior paths according to the session segmentation strategy.

[0084] Specifically, after obtaining the target event detail data corresponding to the project detection request above, in order to be able to reflect the requirement results corresponding to the current project detection request through the target event detail data, it is necessary to process the target event detail data so that it can be presented to the user in a visual expression. Therefore, a user behavior path can be constructed first according to the target event detail data. Through the user behavior path, the behavior operations of the users who meet the project detection request when participating in the target service project can be reflected, which is convenient for subsequent analysis and use. At the same time, considering that there may be paths in the user behavior path that affect subsequent analysis and processing, such as abnormal operations with a long session time, the user behavior path can be split. At this time, the user behavior path can be split into target user behavior paths according to the session segmentation strategy, so that the target user behavior path can accurately reflect the behavior operations of each user when participating in the target service project for subsequent construction of path visualization information.

[0085] Among them, the user behavior path specifically refers to the path constructed corresponding to the user behavior operations according to the event detail data of each user recorded in the target event detail data. Correspondingly, the session segmentation strategy specifically refers to the strategy of splitting the user behavior path according to the session time, which is used to ensure that the obtained target user behavior path conforms to the actual operation behavior of the user.

[0086] Furthermore, when constructing the user behavior path, considering that the target event detail data is the event detail data corresponding to all the circumscribed users, in order to be able to accurately reflect the behavior operations of each user with the user behavior path of each user, it can be achieved through the method of grouping and construction; and on this basis, since different project detection requests need to construct different types of user behavior paths, it is necessary to construct the user behavior path in combination with the type of the project detection request. In this embodiment, the specific implementation method is as follows:

[0087] Group the target event detail data according to the user identifier to obtain at least two groups of event detail sub-data;

[0088] In a first aspect, when the project detection request is a subsequent behavior detection request, perform ascending sorting on each of the at least two groups of event detail sub-data; determine the starting event information corresponding to the subsequent behavior detection request, and construct a user behavior path based on the starting event information and the at least two groups of event detail sub-data after ascending sorting.

[0089] In a second aspect, when the project detection request is a previous behavior detection request, perform descending sorting on each of the at least two groups of event detail sub-data; determine the ending event information corresponding to the previous behavior detection request, and construct a user behavior path based on the ending event information and the at least two groups of event detail sub-data after descending sorting.

[0090] Specifically, at least two groups of event detail sub-data specifically refer to a data structure composed of each piece of event detail data corresponding to each user; correspondingly, the subsequent behavior detection request specifically refers to a request that needs to analyze relevant subsequent events after the starting event in the target service project; correspondingly, the starting event information specifically refers to the information corresponding to the starting event set when subsequent behavior analysis is required; correspondingly, the previous behavior detection request specifically refers to a request that needs to analyze relevant previous events before the ending event in the target service project; correspondingly, the ending event information specifically refers to the information corresponding to the ending event set when previous behavior analysis is required.

[0091] Based on this, as Figure 3b shown in the schematic diagram, considering that different detection requests for target service projects need to construct different user behavior paths to meet the subsequent optimization processing requirements, the target event detail data can be grouped according to the user identifier first to obtain at least two groups of event detail sub-data; to achieve grouping of the event detail data of each user.

[0092] In a first aspect, when the project detection request is a subsequent behavior detection request, it indicates that at this time, other subsequent events after the starting event need to be analyzed and processed. Therefore, ascending sorting can be performed on each of the at least two groups of event detail sub-data; so that the event detail data included in each group of event detail sub-data can be arranged in ascending order according to the time sequence. On this basis, then determine the starting event information corresponding to the subsequent behavior detection request, and construct a user behavior path based on the starting event information and the at least two groups of event detail sub-data after ascending sorting.

[0093] In a second aspect, when the project detection request is a previous behavior detection request, it indicates that at this time, other previous events before the termination event need to be analyzed and processed. Therefore, at least two sets of event detail sub-data can be sorted in descending order respectively, so that the event detail data included in each set of event detail sub-data can be sorted in descending order according to the time sequence. On this basis, the termination event information corresponding to the previous behavior detection request is determined, and the user behavior path can be constructed according to the termination event information and at least two sets of event detail sub-data sorted in descending order.

[0094] In summary, setting different sorting methods for event detail sub-data for different project detection requests can enable the event detail sub-data to be accurately sorted according to requirements, thereby ensuring that the constructed user behavior path conforms to the actual operation behavior for subsequent use in constructing path visualization information.

[0095] Furthermore, after obtaining the user behavior path, considering that the user behavior path does not consider the time sequence problem, which may affect subsequent analysis, in order to avoid this problem, the user behavior path can be segmented in combination with the session segmentation strategy. In this embodiment, the specific implementation method is as follows:

[0096] Determine the session time and event information according to the session segmentation strategy, and detect the interval time between adjacent event nodes in the user behavior path; compare the interval time with the session time, and determine the path segmentation position in the user behavior path according to the comparison result; segment the user behavior path according to the segmentation position to obtain at least two candidate user behavior paths; filter the at least two candidate user behavior paths based on the event information to obtain the target user behavior path.

[0097] Specifically, the session time specifically refers to the time threshold preset for detecting whether the time between every two events exceeds the normal operation time; correspondingly, the event information specifically refers to the information corresponding to the starting event; correspondingly, the interval time specifically refers to the time interval between any adjacent event nodes in the user behavior path; correspondingly, the path segmentation position specifically refers to the position used to segment the user behavior path, and this position can divide the user behavior path into at least two candidate user behavior paths.

[0098] Based on this, such as Figure 3bIn the schematic diagram shown, after constructing the user behavior path based on the event detail data, in order to enable the user behavior path to accurately reflect the user behavior operations and facilitate the subsequent construction of path visualization information, the user behavior path can be segmented; specifically, the session time and event information can be determined according to the session segmentation strategy first, and the interval time between adjacent event nodes in the user behavior path can be detected; at this time, the interval time can be compared with the session time, and the adjacent event nodes with an interval time greater than the session time can be selected as the path segmentation positions for segmenting the user behavior path according to the comparison result; thereafter, the user behavior path can be segmented according to the segmentation positions to obtain at least two candidate user behavior paths; on this basis, the at least two candidate user behavior paths can be filtered based on the event information to filter out the user behavior paths that do not meet the project detection requirements, so as to obtain the target user behavior path for subsequent use.

[0099] Continuing with the above example, after obtaining the target event detail data shown in Table (2), the target event detail data can be grouped first according to the user uid, and the following Tables (3) and (4) can be obtained according to the grouping results, which are the event detail data corresponding to User 1 and the event detail data corresponding to User 2 respectively:

[0100]

[0101]

[0102] Table (3)

[0103] User ID (UID) Event code (event_code) 2 a 2 b 2 b

[0104] Table (4)

[0105] First, when the detection request for the logistics service project is to analyze subsequent behaviors, the above Tables (3) and (4) can be sorted in ascending order according to ts (user behavior occurrence time), and the following Tables (5) and (6) can be obtained according to the sorting results:

[0106] User ID (UID) Event code (event_code) 1 a 1 b 1 c 1 c 1 d 1 a

[0107] Table (5)

[0108] User ID (UID) Event code (event_code) 2 a 2 b 2 b

[0109] Table (6)

[0110] On this basis, according to the detection request, event a is used as the starting event, and the user behavior paths of User 1 and User 2 are constructed based on the starting event and the above sorted results. At this time, the user behavior path corresponding to User 1 is obtained as {a->b->c->c->d->a}, and the user behavior path corresponding to User 2 is {a->b->b}. On this basis, according to the session time of 5 minutes and the starting event being event a, the user behavior paths of User 1 and User 2 can be segmented. For example, if the time between adjacent events c in the user behavior path of User 1 exceeds 5 minutes, the user behavior path can be divided into {a->b->c} and {c->d->a}; at the same time, since the starting event is a, c->d in the path {c->d->a} can be filtered out, and then the target user behavior paths corresponding to User 1 can be obtained as {a->b->c} and {a}, and the target user behavior path corresponding to User 2 is {a->b->b}, so as to subsequently construct path visualization information in combination with this path for the optimized use of the logistics service project.

[0111] On the other hand, when the detection request for the logistics service project is to analyze the previous behavior, the above tables (3) and (4) can be sorted in descending order according to ts (the time when the user behavior occurs). According to the sorting results, the following tables (7) and (8) can be obtained:

[0112] User ID (UID) Event code (event_code) 1 a 1 d 1 c 1 c 1 b 1 a

[0113] Table (7)

[0114] User ID (UID) Event code (event_code) 2 b 2 b 2 a

[0115] Table (8)

[0116] On this basis, according to the detection request, event a is used as the termination event, and the user behavior paths of User 1 and User 2 are constructed based on the starting event and the above descending sorted results. Among them, the processes of user behavior path construction, segmentation, and filtering can be referred to the above description. Finally, the target user behavior paths corresponding to User 1 can be obtained as {a->d->c} and {a}, and the target user behavior path corresponding to User 2 is {a}, so as to subsequently construct path visualization information in combination with this path for the optimized use of the logistics service project.

[0117] In summary, by constructing the user behavior paths corresponding to each user respectively and performing segmentation on the user behavior paths, the user behavior paths can accurately reflect the operation behaviors of each user, so as to subsequently construct path visualization information that meets the project detection request for use.

[0118] Step S208, construct the path visualization information corresponding to the project detection request based on the target user behavior path.

[0119] Specifically, after obtaining the target user behavior path as described above, in order to construct visual information combined with the target user behavior path for facilitating the analysis of the target service item, path visualization information can be constructed in combination with the target user behavior path. Among them, the path visualization information specifically refers to a path analysis diagram constructed according to the user behavior path and is convenient for users to view. It can be a path destination diagram as Figure 3c shown, or other types of diagrams convenient for project optimization. This embodiment does not make any limitation here.

[0120] Continuing with the above example, after obtaining the target user behavior path corresponding to each user, the target user behavior paths corresponding to each user can be clustered and transformed according to the detection request, and then a path destination diagram as Figure 3c shown is generated; so that the service provider of the logistics service project can optimize the logistics service according to this diagram, and then provide more stable logistics services to users.

[0121] Furthermore, for different project detection requests, the constructed path visualization information is also different, and thus its reflection of the problems of the target service project is also different. In this embodiment, the following specific situations are included:

[0122] In the case where the project detection request is a path detection request, the path visualization information is used to characterize the participation intention of the user in the target service project;

[0123] In the case where the project detection request is a traffic detection request, the path visualization information is used to characterize the traffic source information of the target service project;

[0124] In the case where the project detection request is a churn detection request, the path visualization information is used to characterize the churn node information of the target service project;

[0125] In the case where the project detection request is an abnormal path detection request, the path visualization information is used to characterize the abnormal behavior path information in the target service project;

[0126] In the case where the project detection request is a behavior difference detection request, the path visualization information is used to characterize the behavior difference information associated with the target service project.

[0127] Specifically, the path detection request specifically refers to a detection request for exploring whether the user uses the target service item according to the main operation path designed and expected for the target service item; the traffic detection request specifically refers to a detection request for analyzing the distribution ratio of different traffic sources and the user quality of each source; the churn detection request specifically refers to a detection request for identifying which links have a high churn volume and a high churn rate during the use of the target service item; the abnormal path detection request specifically refers to a detection request for detecting whether there are abnormal user behavior paths (such as loop paths or unexpected paths) in the target service item; the behavior difference detection request specifically refers to a detection request for analyzing the difference in user behavior paths under different conditions such as different user groups, label classifications, and device types, or for comparing the characteristic distributions of churn users and successful users to find the common points and differences.

[0128] That is to say, in the case where the project detection request is a traffic detection request, the path visualization information can be used to analyze the traffic source information of the target service item; in the case where the project detection request is a churn detection request, the path visualization information can be used to analyze the churn node information of the target service item; in the case where the project detection request is an abnormal path detection request, the path visualization information can be used to analyze the abnormal behavior path information in the target service item; in the case where the project detection request is a behavior difference detection request, the path visualization information can be used to analyze the behavior difference information associated with the target service item.

[0129] For the user behavior path construction method provided in this embodiment, in order to reduce cost investment and improve the detection flexibility of the service item, the user behavior data associated with the target service item can be obtained first to achieve the normalization of data without introducing additional buried points by cleaning the user behavior data to obtain behavior event data and user group data. Then, in response to the project detection request submitted for the target service item, the target event detail data can be extracted from the behavior event data according to the user group data, so that the extracted target event detail data can be directly used. Thus, the user behavior path associated with the target service item can be constructed based on the target event detail data. At this time, considering that the user behavior path is not coherent in time, in order to avoid the confusion of project detection caused by this problem, the user behavior path can be segmented into target user behavior paths according to the session segmentation strategy. Thus, the specific behavior of each user in the target service item can be intuitively and accurately reflected through the target user behavior path. Then, the path visualization information corresponding to the project detection request can be constructed based on the target user behavior path. It can be realized that without introducing additional resources, the construction of path visualization information can be completed quickly and accurately, thus making it more convenient for the downstream to optimize and analyze the target service item. And this user behavior path construction method has higher flexibility and can adapt to different types of service items, thereby effectively improving the optimization efficiency of the service items of the service provider.

[0130] The following combines the attached Figure 4 , taking the application of the user behavior path construction method provided in this specification in the analysis scenario of a shopping application as an example, further illustrate the user behavior path construction method. Among them, Figure 4 shows the process flow chart of a user behavior path construction method provided in an embodiment of this specification, specifically including the following steps.

[0131] Step S402, obtain the user behavior data associated with the target service item, perform data cleaning on the user behavior data according to the preset cleaning rules, and obtain the target user behavior data. Among them, the user behavior data is associated with different data sources of the target service item.

[0132] Step S404, determine the event detail data and event metadata, as well as the user data and user attribute data according to the target user behavior data.

[0133] Step S406, use the event detail data and event metadata as the behavior event data, and the user data and user attribute data as the user group data.

[0134] Step S408, receive a project detection request submitted for the target service item, and obtain the detection parameters by parsing the project detection request.

[0135] Step S410, screen the target group sub-data from the user group data according to the detection parameters.

[0136] Step S412, determine the target event metadata in the behavior event data according to the target group sub-data, and extract the target event detail data from the behavior event data based on the target event metadata.

[0137] Step S414, group the target event detail data according to the user identifier, and obtain at least two groups of event detail sub-data.

[0138] Step S416, in the case where the project detection request is a subsequent behavior detection request, perform ascending sorting on at least two groups of event detail sub-data respectively.

[0139] Step S418, determine the start event information corresponding to the subsequent behavior detection request, and construct the user behavior path according to the start event information and at least two groups of event detail sub-data after ascending sorting.

[0140] Step S420, determine the session time and event information according to the session segmentation strategy, and detect the interval time between adjacent event nodes in the user behavior path.

[0141] Step S422: Compare the interval time with the session time, and determine the path segmentation position in the user behavior path according to the comparison result.

[0142] Step S424: Segment the user behavior path according to the segmentation position to obtain at least two candidate user behavior paths.

[0143] Step S426: Filter at least two candidate user behavior paths based on the event information to obtain the target user behavior path.

[0144] Step S428: Construct the path visualization information corresponding to the project detection request based on the target user behavior path.

[0145] In summary, in order to reduce cost investment and improve the detection flexibility of service projects, user behavior data associated with the target service project can be obtained first, so as to achieve the acquisition of behavior event data and user group data by cleaning the user behavior data, and complete data standardization without introducing additional buried points. Then, in response to a project detection request submitted for the target service project, target event detail data can be extracted from the behavior event data according to the user group data, so that the extracted target event detail data can be directly used. Thus, a user behavior path associated with the target service project can be constructed based on the target event detail data. At this time, considering that the user behavior path is not coherent in time, in order to avoid the confusion of project detection caused by this problem, the user behavior path can be segmented into the target user behavior path according to the session segmentation strategy. Thus, the specific behavior of each user in the target service project can be intuitively and accurately reflected through the target user behavior path. Then, the path visualization information corresponding to the project detection request can be constructed based on the target user behavior path. It can be realized that without introducing additional resources, the construction of path visualization information can be completed quickly and accurately, which is more convenient for downstream optimization and analysis of the target service project. And this user behavior path construction method has higher flexibility and can adapt to different types of service projects, thereby effectively improving the optimization efficiency of the service projects of the service provider.

[0146] Corresponding to the above method embodiment, this specification also provides an embodiment of a user behavior path construction device. Figure 5 It shows a schematic structural diagram of a user behavior path construction device provided by an embodiment of this specification. As Figure 5 shown, the device includes:

[0147] An acquisition module 502, configured to acquire user behavior data associated with the target service project, and obtain behavior event data and user group data by cleaning the user behavior data;

[0148] An extraction module 504, configured to extract target event detail data from the behavior event data according to the user group data in response to a project detection request submitted for the target service item;

[0149] A segmentation module 506, configured to construct a user behavior path based on the target event detail data and segment the user behavior path into target user behavior paths according to a session segmentation strategy;

[0150] A construction module 508, configured to construct path visualization information corresponding to the project detection request based on the target user behavior path.

[0151] In an optional embodiment, the acquisition module 502 is further configured to:

[0152] Perform data cleaning on the user behavior data according to a preset cleaning rule to obtain target user behavior data, where the user behavior data is associated with different data sources of the target service item; determine event detail data and event metadata, as well as user data and user attribute data according to the target user behavior data; use the event detail data and the event metadata as behavior event data, and the user data and the user attribute data as user group data.

[0153] In an optional embodiment, the acquisition module 502 is further configured to:

[0154] Determine event detail data according to the target user behavior data, and perform deduplication on the event detail data to obtain initial event metadata; perform semantic processing on the initial event metadata, and generate event metadata according to the semantic processing result; where the event detail data is stored in the event detail table of the target service item, and the event metadata is stored in the event metadata table of the target service item.

[0155] In an optional embodiment, the extraction module 504 is further configured to:

[0156] Receive a project detection request submitted for the target service item, and obtain detection parameters by parsing the project detection request; screen target group sub-data from the user group data according to the detection parameters; determine target event metadata from the behavior event data according to the target group sub-data, and extract target event detail data from the behavior event data based on the target event metadata.

[0157] In an optional embodiment, the segmentation module 506 is further configured to:

[0158] Group the target event detail data according to the user identifier to obtain at least two groups of event detail sub-data; when the project detection request is a subsequent behavior detection request, perform ascending sorting on the at least two groups of event detail sub-data respectively; determine the start event information corresponding to the subsequent behavior detection request, and construct a user behavior path according to the start event information and the at least two groups of event detail sub-data after ascending sorting.

[0159] In an optional embodiment, the splitting module 506 is further configured to:

[0160] When the project detection request is a previous behavior detection request, perform descending sorting on the at least two groups of event detail sub-data respectively; determine the end event information corresponding to the previous behavior detection request, and construct a user behavior path according to the end event information and the at least two groups of event detail sub-data after descending sorting.

[0161] In an optional embodiment, the splitting module 506 is further configured to:

[0162] Determine the session time and event information according to the session splitting strategy, and detect the interval time between adjacent event nodes in the user behavior path; compare the interval time with the session time, and determine the path splitting position in the user behavior path according to the comparison result; split the user behavior path according to the splitting position to obtain at least two candidate user behavior paths; filter the at least two candidate user behavior paths based on the event information to obtain the target user behavior path.

[0163] In an optional embodiment, the device further includes:

[0164] When the project detection request is a path detection request, the path visualization information is used to represent the participation intention of the user in the target service project; when the project detection request is a traffic detection request, the path visualization information is used to represent the traffic source information of the target service project; when the project detection request is a churn detection request, the path visualization information is used to represent the churn node information of the target service project; when the project detection request is an abnormal path detection request, the path visualization information is used to represent the abnormal behavior path information in the target service project; when the project detection request is a behavior difference detection request, the path visualization information is used to represent the behavior difference information associated with the target service project.

[0165] The user behavior path construction device provided in this embodiment, in order to reduce cost investment and improve the detection flexibility of service items, can first obtain the user behavior data associated with the target service item, so as to achieve obtaining behavior event data and user group data by cleaning the user behavior data, and complete data standardization without introducing additional buried points. Then, in response to a project detection request submitted for the target service item, extract the target event detail data from the behavior event data according to the user group data; so that the extracted target event detail data can be directly used. Then, construct a user behavior path associated with the target service item based on the target event detail data. At this time, considering that the user behavior path is not coherent in time, in order to avoid the confusion of project detection caused by this problem, the user behavior path can be segmented into target user behavior paths according to the session segmentation strategy; thus, the specific behaviors of each user in the target service item can be intuitively and accurately reflected through the target user behavior paths. Then, the path visualization information corresponding to the project detection request can be constructed based on the target user behavior paths. It can be realized that without introducing additional resources, the path visualization information can be constructed quickly and accurately, thereby making it more convenient for downstream to optimize and analyze the target service item. And this user behavior path construction method has higher flexibility and can adapt to different types of service items, thereby effectively improving the service item optimization efficiency of the service provider.

[0166] The above is a schematic solution of a user behavior path construction device in this embodiment. It should be noted that the technical solution of this user behavior path construction device and the technical solution of the above user behavior path construction method belong to the same concept. For the details not described in the technical solution of the user behavior path construction device, reference can be made to the description of the technical solution of the above user behavior path construction method.

[0167] Corresponding to the above method embodiment, this specification also provides a user behavior path construction system embodiment. Figure 6 It shows a schematic structural diagram of a user behavior path construction system provided in an embodiment of this specification. As Figure 6 shown, the user behavior path construction system 600 includes a server 610 and a client 620, including:

[0168] The server 610 is used to obtain the user behavior data associated with the target service item, and obtain behavior event data and user group data by cleaning the user behavior data; store the behavior event data and the user group data in the target database;

[0169] The client 620 is used to receive a project detection request submitted for the target service item, and send the project detection request to the server;

[0170] The server 610 is configured to access the target database according to the project detection request, and extract target event detail data from the behavior event data according to the user group data; construct a user behavior path based on the target event detail data, and segment the user behavior path into target user behavior paths according to a session segmentation strategy; construct path visualization information corresponding to the project detection request based on the target user behavior paths; and send the path visualization information to the client.

[0171] The client 620 is configured to receive and display the path visualization information.

[0172] The user behavior path construction system provided in this embodiment, in order to reduce cost investment and improve the detection flexibility of service projects, can first obtain user behavior data associated with a target service project, so as to realize obtaining behavior event data and user group data by cleaning the user behavior data, and complete data standardization without introducing additional buried points. Then, in response to a project detection request submitted for the target service project, target event detail data can be extracted from the behavior event data according to the user group data; so that the extracted target event detail data can be directly used. Thus, a user behavior path associated with the target service project can be constructed based on the target event detail data. At this time, considering that the user behavior path is not coherent in time, in order to avoid the confusion of project detection caused by this problem, the user behavior path can be segmented into target user behavior paths according to the session segmentation strategy; thus, the specific behavior of each user in the target service project can be intuitively and accurately reflected through the target user behavior paths. Then, path visualization information corresponding to the project detection request can be constructed based on the target user behavior paths. It can be realized that without introducing additional resources, the construction of path visualization information can be completed quickly and accurately, thereby facilitating downstream optimization and analysis of the target service project more conveniently. And this user behavior path construction method has higher flexibility and can adapt to different types of service projects, thereby effectively improving the optimization efficiency of the service projects of the service provider.

[0173] The above is a schematic solution of a user behavior path construction system according to this embodiment. It should be noted that the technical solution of this user behavior path construction system and the technical solution of the above user behavior path construction method belong to the same concept. For the details not described in the technical solution of the user behavior path construction system, reference can be made to the description of the technical solution of the above user behavior path construction method.

[0174] Figure 7FIG. 0 shows a structural block diagram of a computing device 700 provided according to an embodiment of the present specification. The components of the computing device 700 include, but are not limited to, a memory 710 and a processor 720. The processor 720 is connected to the memory 710 via a bus 730, and a database 750 is used to store data.

[0175] The computing device 700 further includes an access device 740, which enables the computing device 700 to communicate via one or more networks 760. Examples of these networks include the Public Switched Telephone Network (PSTN), Local Area Network (LAN), Wide Area Network (WAN), Personal Area Network (PAN), or a combination of communication networks such as the Internet. The access device 740 may include one or more of any type of wired or wireless network interfaces (e.g., a network interface card (NIC)), such as an IEEE 802.11 Wireless Local Area Network (WLAN) wireless interface, a Worldwide Interoperability for Microwave Access (Wi-MAX) interface, an Ethernet interface, a Universal Serial Bus (USB) interface, a cellular network interface, a Bluetooth interface, or a Near Field Communication (NFC) interface.

[0176] In an embodiment of the present specification, the above components of the computing device 700 and Figure 7 other components not shown in FIG. may also be connected to each other, for example, via a bus. It should be understood that Figure 7 the structural block diagram of the computing device shown is only for illustrative purposes and is not a limitation on the scope of the present specification. Those skilled in the art may add or replace other components as needed.

[0177] The computing device 700 can be any type of stationary or mobile computing device, including a mobile computer or mobile computing device (e.g., a tablet computer, a personal digital assistant, a laptop computer, a notebook computer, a netbook, etc.), a mobile phone (e.g., a smart phone), a wearable computing device (e.g., a smart watch, smart glasses, etc.) or other types of mobile devices, or a stationary computing device such as a desktop computer or a personal computer (PC). The computing device 700 can also be a mobile or stationary server.

[0178] Wherein, the processor 720 is configured to execute the following computer-executable instructions, and when the computer-executable instructions are executed by the processor, the steps of the above-mentioned user behavior path construction method are implemented.

[0179] The above is a schematic solution of a computing device according to this embodiment. It should be noted that the technical solution of the computing device and the technical solution of the above-mentioned user behavior path construction method belong to the same concept. For the details not described in detail in the technical solution of the computing device, reference can be made to the description of the technical solution of the above-mentioned user behavior path construction method.

[0180] An embodiment of this specification also provides a computer-readable storage medium, which stores computer-executable instructions, and when the computer-executable instructions are executed by a processor, the steps of the above-mentioned user behavior path construction method are implemented.

[0181] The above is a schematic solution of a computer-readable storage medium according to this embodiment. It should be noted that the technical solution of the storage medium and the technical solution of the above-mentioned user behavior path construction method belong to the same concept. For the details not described in detail in the technical solution of the storage medium, reference can be made to the description of the technical solution of the above-mentioned user behavior path construction method.

[0182] An embodiment of this specification also provides a computer program, wherein when the computer program is executed on a computer, the computer is made to execute the steps of the above-mentioned user behavior path construction method.

[0183] The above is a schematic solution of a computer program according to this embodiment. It should be noted that the technical solution of the computer program and the technical solution of the above-mentioned user behavior path construction method belong to the same concept. For the details not described in detail in the technical solution of the computer program, reference can be made to the description of the technical solution of the above-mentioned user behavior path construction method.

[0184] An embodiment of this specification also provides a computer program product, including a computer program or instructions, and when the computer program or instructions are executed by a processor, the steps of the above-mentioned user behavior path construction method are implemented.

[0185] The above is a schematic solution of a computer program product according to this embodiment. It should be noted that the technical solution of this computer program product and the technical solution of the above user behavior path construction method belong to the same concept. For the details not described in the technical solution of the computer program product, reference can be made to the description of the technical solution of the above user behavior path construction method.

[0186] The above has described specific embodiments of this specification. Other embodiments are within the scope of the appended claims. In some cases, the actions or steps recited in the claims may be performed in a different order than in the embodiments and still achieve the desired result. Additionally, the processes depicted in the figures do not necessarily require the particular order or sequential order shown to achieve the desired result. In certain embodiments, multitasking and parallel processing are also possible or may be advantageous.

[0187] The computer instructions include computer program code, which may be in the form of source code, object code, executable files, or some intermediate form, etc. The computer-readable medium may include: any entity or device capable of carrying the computer program code, recording medium, USB flash drive, mobile hard disk, magnetic disk, optical disc, computer memory, read-only memory (ROM), random access memory (RAM), electrical carrier signals, telecommunication signals, and software distribution media, etc. It should be noted that the content included in the computer-readable medium can be appropriately increased or decreased according to the requirements of patent practice. For example, in some regions, according to patent practice, the computer-readable medium does not include electrical carrier signals and telecommunication signals.

[0188] It should be noted that for the foregoing method embodiments, for the sake of simplicity of description, they are all expressed as a series of action combinations. However, those skilled in the art should know that the embodiments of this specification are not limited by the described action sequence, because according to the embodiments of this specification, certain steps can be performed in other sequences or simultaneously. Secondly, those skilled in the art should also know that the embodiments described in the specification are all preferred embodiments, and the actions and modules involved are not necessarily essential to the embodiments of this specification.

[0189] In the above embodiments, the descriptions of the various embodiments have their own emphases. For the parts not detailed in a certain embodiment, reference can be made to the relevant descriptions of other embodiments.

[0190] The preferred embodiments of the present specification disclosed above are only used to help explain the present specification. The alternative embodiments do not describe all the details in detail, nor do they limit the invention to the specific embodiments described. Obviously, many modifications and variations can be made according to the content of the embodiments of the present specification. The present specification selects and specifically describes these embodiments in order to better explain the principles and practical applications of the embodiments of the present specification, so that those skilled in the art can well understand and utilize the present specification. The present specification is only limited by the claims and their full scope and equivalents.

Claims

1. A method for constructing a user behavior path, comprising: Acquire user behavior data associated with the target service item, and obtain behavior event data and user group data by cleaning the user behavior data; In response to a project detection request submitted for the target service project, extracting target event detail data from the behavior event data according to the user group data; Constructing a user behavior path according to the target event detail data, and segmenting the user behavior path into target user behavior paths according to a session segmentation strategy; Path visualization information corresponding to the project detection request is constructed based on the target user behavior path.

2. The method for constructing a user behavior path according to claim 1, wherein the step of obtaining behavior event data and user group data by cleaning the user behavior data comprises: Cleaning the user behavior data according to preset cleaning rules to obtain target user behavior data, wherein the user behavior data is associated with different data sources of the target service item; Determining event detail data and event metadata, as well as user data and user attribute data according to the target user behavior data; The event detail data and the event metadata are used as behavioral event data, and the user data and the user attribute data are used as user group data.

3. The method for constructing a user behavior path according to claim 2, wherein determining event detail data and event metadata according to the target user behavior data comprises: Determine event detail data according to the target user behavior data, and perform deduplication on the event detail data to obtain initial event metadata; Performing semantic processing on the initial event metadata, and generating event metadata according to the semantic processing result; The event detail data is stored in the event detail table of the target service item, and the event metadata is stored in the event metadata table of the target service item.

4. The method for constructing a user behavior path according to claim 1, wherein in response to the project detection request submitted for the target service project, extracting target event detail data from the behavior event data according to the user group data comprises: Receiving a project detection request submitted for the target service project, and obtaining detection parameters by parsing the project detection request; Filtering target group sub-data from the user group data according to the detection parameters; Determining target event metadata in the behavior event data according to the target group sub-data, and extracting target event detail data from the behavior event data based on the target event metadata; Wherein, constructing a user behavior path according to the target event detailed data includes: Grouping the target event detail data according to the user identifier to obtain at least two groups of event detail sub-data; In the case where the item detection request is a subsequent behavior detection request, the at least two groups of event detail sub-data are respectively sorted in ascending order; The starting event information corresponding to the subsequent behavior detection request is determined, and a user behavior path is constructed according to the starting event information and at least two groups of event detail sub-data sorted in ascending order.

5. The method for constructing a user behavior path according to claim 4, further comprising: In the case where the item detection request is a preceding behavior detection request, the at least two groups of event detail sub-data are sorted in descending order respectively; The termination event information corresponding to the preceding behavior detection request is determined, and a user behavior path is constructed according to the termination event information and at least two groups of event detail sub-data sorted in descending order.

6. The method for constructing a user behavior path according to claim 1, wherein the step of segmenting the user behavior path into target user behavior paths according to a session segmentation strategy comprises: Determine the session time and event information according to the session segmentation strategy, and detect the interval time between adjacent event nodes in the user behavior path; Comparing the interval time with the session time, and determining a path splitting position in the user behavior path according to the comparison result; Segment the user behavior path according to the segmentation position to obtain at least two candidate user behavior paths; Filtering the at least two candidate user behavior paths based on the event information to obtain a target user behavior path; Wherein, the method further comprises: In the case where the project detection request is a path detection request, the path visualization information is used to represent the user's participation intention in participating in the target service project; In the case where the project detection request is a flow detection request, the path visualization information is used to characterize the flow source information of the target service project; In the case where the project detection request is a churn detection request, the path visualization information is used to characterize churn node information of the target service project; In the case where the project detection request is an abnormal path detection request, the path visualization information is used to characterize abnormal behavior path information in the target service project; In the case where the item detection request is a behavior difference detection request, the path visualization information is used to represent the behavior difference information associated with the target service item.

7. A user behavior path construction system, including a client and a server, including: The server is used to obtain user behavior data associated with the target service item, and obtain behavior event data and user group data by cleaning the user behavior data; storing the behavior event data and the user group data in a target database; The client is used to receive a project detection request submitted for the target service project, and send the project detection request to the server; The server is used to access the target database according to the item detection request, and extract target event detail data from the behavior event data according to the user group data; Constructing a user behavior path according to the target event detail data, and segmenting the user behavior path into target user behavior paths according to a session segmentation strategy; Constructing path visualization information corresponding to the project detection request based on the target user behavior path; and sending the path visualization information to the client; The client is used to receive and display the path visualization information.

8. A computing device comprising: Memory and processor; The memory is used to store computer-executable instructions, and the processor is used to execute the computer-executable instructions. When the computer-executable instructions are executed by the processor, the steps of the method described in any one of claims 1 to 6 are implemented.

9. A computer-readable storage medium storing computer-executable instructions, wherein the computer-executable instructions, when executed by a processor, implement the steps of the method according to any one of claims 1 to 6.

10. A computer program product, comprising a computer program or instructions, which implement the steps of the method according to any one of claims 1 to 6 when executed by a processor.

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