Information processing method and device, electronic equipment and storage medium

Abstract

The invention provides an information processing method, relates to the technical field of artificial intelligence and big data, in particular to the technical field of information processing, and can be applied to a burying point information processing scene. According to the specific implementation scheme, in response to a first operation input through a visual interface, first information corresponding to the first operation is generated, and the first information is used for representing a point burying mode combination or a point burying event combination adopted for collecting target point burying information and a processing requirement for the target point burying information; generating a target query statement based on the first information; processing target burying point information obtained from pre-stored burying point information based on the target query statement to obtain a processing result; and displaying the processing result. The invention further provides an information processing device, electronic equipment and a storage medium.

Description

Technical Field

[0001] The present disclosure relates to the fields of artificial intelligence and big data technologies, and particularly to the field of information processing technologies, and can be applied to the scenario of buried point information processing. More specifically, the present disclosure provides an information processing method, apparatus, electronic device, and storage medium. Background Art

[0002] With the development of artificial intelligence technology and big data technology, data users need to perform data analysis more efficiently and accurately in order to better grasp market trends and user needs. In digital operation, buried point information is a key data source, and high-precision and high-efficiency buried point information arrangement is a key factor in realizing digital operation. Summary of the Invention

[0003] The present disclosure provides an information processing method, apparatus, device, and storage medium.

[0004] According to one aspect of the present disclosure, there is provided an information processing method, the method including: in response to a first operation input via a visual interface, generating first information corresponding to the first operation, the first information being used to represent a combination of buried point methods or a combination of buried point events for collecting target buried point information and a processing requirement for the target buried point information; generating a target query statement based on the first information; processing the target buried point information obtained from the pre-stored buried point information based on the target query statement to obtain a processing result; and presenting the processing result.

[0005] According to another aspect of the present disclosure, there is provided an information processing apparatus, the apparatus including: a response module, configured to generate first information corresponding to a first operation in response to the first operation input via a visual interface, the first information being used to represent a combination of buried point methods or a combination of buried point events for collecting target buried point information and a processing requirement for the target buried point information; a generation module, configured to generate a target query statement based on the first information; a processing module, configured to obtain target buried point information from the pre-stored buried point information based on the target query statement and process the target buried point information to obtain a processing result; and a presentation module, configured to present the processing result.

[0006] According to another aspect of the present disclosure, there is provided an electronic device, including: at least one processor; and a memory communicatively connected to the at least one processor; wherein, the memory stores instructions executable by the at least one processor, and the instructions are executed by the at least one processor to enable the at least one processor to execute the method provided by the present disclosure.

[0007] According to another aspect of the present disclosure, there is provided a non-transitory computer-readable storage medium storing computer instructions, the computer instructions being used to cause a computer to execute the method provided by the present disclosure.

[0008] According to another aspect of the present disclosure, there is provided a computer program product including a computer program which, when executed by a processor, implements the method provided according to the present disclosure.

[0009] It should be understood that the content described in this part is not intended to identify the key or important features of the embodiments of the present disclosure, nor is it used to limit the scope of the present disclosure. Other features of the present disclosure will become readily understood through the following description. Description of the Drawings

[0010] The drawings are used to better understand the solution and do not constitute a limitation to the present disclosure. Among them:

[0011] Figure 1 is a schematic diagram of an exemplary system architecture to which an information processing method and apparatus according to an embodiment of the present disclosure can be applied;

[0012] Figure 2 is a flowchart of an information processing method according to an embodiment of the present disclosure;

[0013] Figure 3 is a visualization interface diagram according to an embodiment of the present disclosure;

[0014] Figure 4 is a flowchart of generating a target query statement in an information processing method according to an embodiment of the present disclosure;

[0015] Figure 5 is a flowchart of generating a target query statement in an information processing method according to another embodiment of the present disclosure;

[0016] Figure 6 is a flowchart of obtaining buried point information according to an embodiment of the present disclosure;

[0017] Figure 7 is a block diagram of an information processing apparatus according to an embodiment of the present disclosure;

[0018] Figure 8 is a block diagram of an electronic device according to an embodiment of the present disclosure; and

[0019] Figure 9 shows a schematic block diagram of an exemplary electronic device 900 that can be used to implement the embodiments of the present disclosure. Detailed Embodiments

[0020] The following describes exemplary embodiments of the present disclosure with reference to the accompanying drawings. Various details of the embodiments of the present disclosure are included to facilitate understanding, and they should be considered merely exemplary. Therefore, those of ordinary skill in the art should recognize that various changes and modifications can be made to the embodiments described herein without departing from the scope and spirit of the present disclosure. Similarly, descriptions of well-known functions and structures are omitted below for clarity and conciseness.

[0021] Currently, there are problems in the arrangement and analysis of buried point information, such as high data arrangement complexity, dependence on professional teams, cumbersome data acquisition processes, and difficulty in adapting to business changes. The high data arrangement complexity is reflected in: the structure of buried point information is diverse, business personnel lack data engineering capabilities, and it is difficult to effectively arrange data tables and analysis logics. The dependence on professional teams is reflected in: traditional data analysis requires relying on data engineers or developers to perform core process processing (Extract-Transform-Load, abbreviated as ETL) in data integration. ETL processing is the core process in data integration and data warehouse construction, which is used to extract, clean, transform, and load data from scattered and heterogeneous data sources into the target system to support subsequent data analysis and decision-making, affecting the timeliness and flexibility of business decisions. The cumbersome data acquisition process is reflected in: different buried point sources (mobile terminals, Web terminals) have different storage tables, and the analysis of buried point information is not unified, making it impossible to efficiently and automatically complete data organization. The difficulty in adapting to business changes is reflected in: when the business logic is adjusted, the acquisition method and storage format of buried point information also need to be modified, and the traditional method has a slow response, affecting the analysis efficiency.

[0022] In some examples, the arrangement analysis methods for buried point information may include, for example, the method of manual buried point combined with data warehouse analysis, the method of visual buried point combined with automated analysis, the method of log collection combined with data collection, and the method of direct database query. The method of manual buried point combined with data warehouse analysis is that developers manually add buried point code in the application code, and the buried point information is stored in the database or data warehouse; business personnel perform data query and analysis through query tools. This method requires developers to maintain the buried points, and the cost of buried point changes is high. The method of visual buried point combined with automated analysis automatically buries points at the user interface layer (UIL) through a Software Development Kit (SDK), without manually inserting code; predefined event and user behavior models are used to automatically generate data analysis reports. This method is limited by the capabilities of the SDK and it is difficult to support complex business logics. The method of log collection combined with data collection is to record user behavior logs based on the application side and upload them to the server; the data engineering team writes ETL processes to clean and transform the data and then store it in the data warehouse; business personnel analyze through query tools. This method relies on a professional data team and the information processing cycle is long. The method of direct database query is to directly query the business database to obtain buried point information. This method has poor flexibility and it is difficult to meet the requirements for arranging buried point information. Generally speaking, these methods cannot meet the needs of non-technical personnel (such as business personnel) for arranging buried point information, and there are limitations in flexibility and usability, and they cannot quickly adapt to business changes.

[0023] In view of this, embodiments of the present disclosure provide an information processing method, which includes: in response to a first operation input on a visual interface, generating first information corresponding to the first operation, where the first information is used to characterize the combination of buried point methods or the combination of buried point events for collecting target buried point information and the processing requirements for the target buried point information; generating a target query statement based on the first information; obtaining the target buried point information from the pre-stored buried point information based on the target query statement, and processing the target buried point information to obtain a processing result; and displaying the processing result. This method can be applied to, for example, APP products, enabling non-technical personnel such as operation and product personnel to efficiently utilize data to drive business optimization.

[0024] Figure 1 is a schematic diagram of an exemplary system architecture to which the information processing method and apparatus according to an embodiment of the present disclosure can be applied. It should be noted that, Figure 1 The illustration shown is only an example of the system architecture to which the embodiments of the present disclosure can be applied, to help those skilled in the art understand the technical content of the present disclosure, but it does not mean that the embodiments of the present disclosure cannot be used in other devices, systems, environments or scenarios.

[0025] As Figure 1As shown, the system architecture 100 according to this embodiment may include terminal devices 101, 102, 103, a network 104, and a server 105. The network 104 is used to provide a medium for communication links between the terminal devices 101, 102, 103 and the server 105. The network 104 may include various connection types, such as wired and / or wireless communication links, etc.

[0026] The terminal devices 101, 102, 103 may be various electronic devices with a display screen and supporting data visualization arrangement, including but not limited to smartphones, tablets, laptop computers, desktop computers, etc. Users can input operations on the display screens of the terminal devices 101, 102, 103 and interact with the server 105 through the network 104 to receive or send information, etc.

[0027] The server 105 may be a server providing various services, such as a background management server (for example only) that supports operations executed by users on the terminal devices 101, 102, 103. The background management server can respond to operations input by users on the terminal devices 101, 102, 103, automatically implement the arrangement and processing of buried point information, and send the processing results to the display screens of the terminal devices 101, 102, 103 for display.

[0028] It should be noted that the information processing method provided by the embodiments of the present disclosure can generally be executed by the server 105. Correspondingly, the information processing device provided by the embodiments of the present disclosure can generally be set in the server 105. The information processing method provided by the embodiments of the present disclosure can also be executed by a server or a server cluster different from the server 105 and capable of communicating with the terminal devices 101, 102, 103 and / or the server 105. Correspondingly, the information processing device provided by the embodiments of the present disclosure can also be set in a server or a server cluster different from the server 105 and capable of communicating with the terminal devices 101, 102, 103 and / or the server 105.

[0029] It can be understood that Figure 1 The numbers and types of the terminal devices, network, and server in

[0030] are merely illustrative. According to the implementation requirements, there can be any number of terminal devices, network, and server.

[0031] In the technical solution of the present disclosure, the information and data involved (including but not limited to data for analysis, stored data, displayed data, etc.) are all authorized information and data. Moreover, the processing of relevant data, such as collection, storage, use, processing, transmission, provision, disclosure, and application, complies with relevant laws, regulations, and standards, takes necessary confidentiality measures, does not violate public order and good customs, and provides corresponding operation entrances for users to choose to authorize or reject.

[0032] Figure 2 It is a flowchart of an information processing method according to an embodiment of the present disclosure.

[0033] As Figure 2 shown, the method 200 may include operation S210 to operation S240.

[0034] In operation S210, in response to a first operation input on the visualization interface, a first piece of information corresponding to the first operation is generated.

[0035] According to an embodiment of the present disclosure, the logic of complex buried point information can be disassembled and modularized in advance, a visual orchestration analysis system can be constructed, and then the technology of user-system interaction can be realized through a graphical user interface (GUI) using visual drag-and-drop technology, allowing users to build interfaces, configure processes, or operate data by dragging (Drag) and dropping (Drop) elements. In this way, when the user inputs the first operation via the visualization interface, the orchestration analysis system for buried point information can be triggered for orchestration analysis without the user having to concern about the underlying code logic.

[0036] According to an embodiment of the present disclosure, the first operation can be determined according to the orchestration requirements of buried point information, and different types of first operations can trigger the orchestration analysis of different types of buried point information.

[0037] Figure 3 It is a visualization interface diagram according to an embodiment of the present disclosure.

[0038] For example, multiple controls can be correspondingly displayed on the visualization interface. For example, buried point orchestration 310, buried point list 320. Clicking on the buried point list 320 can, for example, pop up controls such as all 321, operation position display 322, event display 323, purchase click 324, purchase behavior 325, search 326, etc. Clicking on controls such as all 321, operation position display 322, event display 323, purchase click 324, purchase behavior 325, search 326, etc. can further pop up sub-controls. These controls are all associated with the modularized logic. Clicking or dragging the corresponding control can trigger the corresponding logic, such as marketing event selection, buried point combination selection, etc. Users can freely define the data table structure and buried point field mapping relationship by dragging the controls.

[0039] According to an embodiment of the present disclosure, the first information is used to characterize the combination of data embedding methods or the combination of data embedding events for collecting target data embedding information and the processing requirements for the target data embedding information. The combination of data embedding methods or the combination of data embedding events can be abbreviated as the data embedding combination. The data embedding combination can be understood as referring to the process of reasonably matching different types of data embedding methods or data embedding events during data embedding to comprehensively and accurately collect user behavior data and meet the requirements of business analysis and product optimization. The core goal of the data embedding combination is to solve the limitations that may exist in a single data embedding method or event, and provide richer information for subsequent data analysis through multi-dimensional and multi-level data collection.

[0040] For example, the data embedding combination can include the combination of front-end data embedding and back-end data embedding, the combination of full data embedding and custom data embedding, the combination of event data embedding and attribute data embedding, the combination of visual data embedding and code data embedding, and so on.

[0041] According to an embodiment of the present disclosure, the processing requirements for the target data embedding information can be understood as what form of data the target data embedding information needs to be processed into. For example, analyzing abnormal data in the target data embedding information, predicting the data embedding information at a future time based on the current target data embedding information, displaying the processing results in the form of a report, displaying the processing results in the form of a chart, and so on.

[0042] In operation S220, a target query statement is generated based on the first information.

[0043] According to an embodiment of the present disclosure, the first information indicates a combination of data embedding methods or a combination of data embedding events, and cannot directly perform the arrangement and analysis of data embedding information. A target query statement can be generated based on the first information for the arrangement and analysis of data embedding information. Since the arrangement and analysis of data embedding information are performed in a data warehouse, the target query statement can adopt a Structured Query Language (SQL for short).

[0044] In operation S230, the target data embedding information is obtained from the pre-stored data embedding information based on the target query statement, and the target data embedding information is processed to obtain a processing result.

[0045] According to an embodiment of the present disclosure, after obtaining user authorization, data embedding information can be pre-obtained and stored in a data warehouse. After generating the target query statement, the target query statement is executed in the data warehouse to obtain the target data embedding information from the pre-stored data embedding information and perform processing.

[0046] The processing process can include, for example, analyzing the logic of the target data embedding information to obtain general data; generating a data model table based on the result of the analysis logic based on SQL column mapping to obtain a Suger data source; creating a report task based on API construction; storing the processed data, and so on.

[0047] In operation S240, the processing result is displayed.

[0048] According to an embodiment of the present disclosure, a display area may also be set on the visualization interface for visually displaying the processing result so that the user can intuitively obtain it.

[0049] Through the information processing method of the embodiment of the present disclosure, using the visual drag-and-drop technology, the complex gap process of buried point information arrangement is presented through an intuitive graphical interface interaction method. When the user performs different operations on the visualization interface, different first information is correspondingly generated, and then a target query statement is generated according to the first information to automatically arrange the buried point information in the data warehouse. Non-technical personnel do not need to understand the underlying code logic and can directly perform corresponding operations on the visualization interface according to their needs to independently implement the arrangement and analysis of buried point information, thereby meeting the needs of business personnel for arranging buried point information, and greatly improving flexibility and usability.

[0050] Figure 4 It is a flowchart of generating a target query statement in the information processing method according to an embodiment of the present disclosure.

[0051] In some embodiments, as Figure 4 shown, the target query statement generation method 420 in the information processing method 400 of this embodiment may include operation S421 to operation S422.

[0052] In operation S421, based on the first information and the second information associated with the first information, query parameters and processing parameters for processing the target buried point information are determined.

[0053] According to an embodiment of the present disclosure, the second information may represent the buried point component used to collect the target buried point information.

[0054] For example, the buried point component may include a buried point event component, a simple logic component, and an analysis ability component. The buried point event component can be used to implement display events, click events, etc. The simple logic component can be used to implement event filtering, buried point event order, simple logical operations, etc. The analysis ability component can implement retention analysis, conversion rate analysis, funnel analysis, etc.

[0055] According to an embodiment of the present disclosure, the query parameters can be used to obtain the target buried point information, and the processing parameters can be used to process the target buried point information to generate a data table.

[0056] In operation S422, a target query statement is generated by adding the query parameters and the processing parameters to a predefined target query statement template.

[0057] According to an embodiment of the present disclosure, a predefined target query statement may include placeholders, which may indicate positions for filling query parameters and processing parameters. Query parameters and processing parameters can be added to the positions indicated by the placeholders in the target query statement template to obtain the target query statement.

[0058] Through the information processing method of the embodiments of the present disclosure, a target query statement is generated based on the first information and the second information associated with the first information, and it is possible to simultaneously implement the query and processing of buried point information in the data warehouse only based on the target query statement, with higher processing efficiency. Moreover, different first information corresponds to different target query statements, enabling the arrangement and analysis of buried point information with different requirements, and having stronger flexibility and usability.

[0059] In some embodiments, determining query parameters and processing parameters for processing target buried point information based on the first information and the second information associated with the first information may include:

[0060] Input the first information and the second information associated with the first information into a large model, and output query parameters and processing parameters. The large model is used for semantic understanding of the first information and the second information.

[0061] According to an embodiment of the present disclosure, a user can perform a drag-and-drop operation on a visual interface according to certain constraints, which may rely on a Domain-Specific Language (DSL) or SQL language in the middle, so that the background of the visual orchestration system can parse the first operation and then generate a target query statement.

[0062] Figure 5 It is a flowchart for generating a target query statement in an information processing method according to another embodiment of the present disclosure.

[0063] As Figure 5 shown, for example, a user inputs a first operation via a visual interface to select an activity 521 and a buried point combination 522 (a combination of buried point methods or buried point events), generating the first information.

[0064] Input the first information and the second information associated with the first information into a large model for large model semantic understanding 523, generating query parameters and processing parameters. For example, using the semantic understanding ability of the large model, buried point components can be parsed to obtain the conditions to be queried and the results to be obtained from the final analysis, and buried point events can be parsed to obtain the data to be queried. Query parameters and processing parameters are generated based on the parsing results. Finally, based on the large model semantic understanding 523 and the target query statement template, generation 524 is performed to achieve the generation 525 of the target query statement.

[0065] For example, in the case of target data tracking scenarios, data tracking event components can be pre-set in a product or system, which are code snippets used to capture data tracking information. With user authorization, these data tracking event components can be used to track activities related to target analysis. The second information characterizing the data tracking event components can be input into a large language model, and the data tracking event components can be parsed based on the semantic understanding of the large language model, and key information can be extracted to obtain query conditions, such as user identifiers (e.g., user ID), event names (event_name), event times (event_time), event attributes (e.g., product ID, etc.), and other context information (e.g., device type, geographical location, etc.).

[0066] A data tracking event is a specific instance captured by a data tracking event component during actual operation. Each data tracking event can contain detailed information about user behavior or system status. The first information characterizing the data tracking event is input into a large language model, and based on the semantic understanding of the large language model, data fields directly related to target analysis are parsed from these data tracking events, that is, the data that needs to be queried.

[0067] The analysis capability components in the data tracking component are tools or modules for processing and analyzing the collected data. In the context of a large language model, these analysis capability components may include steps such as data cleaning, feature extraction, model training (if predictive analysis is involved), and result visualization. The queried data is transformed into meaningful analysis results, or a machine learning model is used to predict future trends, that is, the results required by data analysis.

[0068] Based on the above parsing results, query parameters and processing parameters can be generated.

[0069] Through the information processing method of the embodiments of the present disclosure, by combining a predefined target query statement template with the semantic understanding of a large language model to generate a target query statement, an efficient conversion from natural language to a target query statement can be achieved, thereby improving the efficiency of information processing.

[0070] In some embodiments, the information processing method may further include:

[0071] Display the target query statement.

[0072] In response to a second operation input via a visualization interface, modify the query parameters and processing parameters in the target query statement.

[0073] According to the embodiments of the present disclosure, after the system automatically generates a target query statement, the target query statement can also be visually displayed and a modification function can be provided. The user can input a second operation on the visualization interface for adaptive manual modification according to whether the logic of the target query statement meets the requirements.

[0074] Through the information processing method of the embodiments of the present disclosure, after generating a target query statement, the target query statement can be visually displayed, so that users can dynamically adjust query parameters and processing parameters, and further improve the accuracy and flexibility of information processing based on the method of manual intervention calibration.

[0075] In some embodiments, the acquisition methods of pre-stored buried point information may include at least one of the following:

[0076] Collect buried point information based on visual buried points at the user interface layer;

[0077] During the pipeline compilation process of the buried point object, obtain the buried point information by scanning the buried point code.

[0078] Figure 6 It is a flowchart of obtaining buried point information according to an embodiment of the present disclosure.

[0079] As Figure 6 shown, the acquisition methods of pre-stored buried point information may include manual buried point method and automatic buried point method.

[0080] The automatic buried point method can adopt code buried points, and the buried point object can be an active page (such as a marketing activity page, a promotion page, etc.). Through code specification constraints, during the pipeline compilation 631a of the buried point code, the buried point code is scanned 632a to obtain the buried point information, and the buried point information is stored 633. The pipeline compilation of the active page can be understood as the code construction, testing, packaging and deployment processes for the active page during software development and deployment, and efficient and standardized processing is achieved through an automated pipeline. The scanning method of the buried point code can be full-scale scanning, that is, without indexing, and the buried point code is scanned line by line.

[0081] The manual buried point method can be visual buried points. First, a buried point template 631b is formulated, which can be proposed based on the analysis of buried point requirements. According to the analysis link of historical experience, a buried point template is formulated, such as an income analysis, conversion analysis buried point template, etc. Based on the buried point template, the buried point information is imported 632b, and the buried point information can be manually imported with one key through the buried point visualization platform product.

[0082] The buried point template can be understood as an important tool for standardizing data collection behavior and ensuring data accuracy and consistency. The structure of the buried point template may include basic information, event definition, attribute design, data collection method, data storage and management, data analysis and application.

[0083] For example, in the case of the target event tracking scenario, its basic information may include a project overview. The project overview can be used to clarify the goals, expected outcomes, and scope of the event tracking project. For example, with user authorization, design and implement an event tracking solution to track and analyze user event tracking information to optimize the user experience and increase conversion rates.

[0084] Event definition can include user behavior tracking and business process tracking. User behavior tracking can be used to define user behavior events that need to be tracked, and these events can be related to target analysis. Business process tracking can be used to define key nodes in the business process, and these nodes can be related steps to user behavior.

[0085] Attribute design can include event attributes and user attributes. Event attributes can be used to define relevant attributes for each event tracking event, and these attributes help to comprehensively understand user behavior. User attributes can include basic attributes and behavior attributes, etc.

[0086] Data collection methods can include internal collection and third-party collection. For internal collection, for example, with user authorization, event tracking can be performed on the client side or the server side. Client-side event tracking can collect more comprehensive user data, while server-side event tracking has the advantages of high real-time performance and accurate data. Third-party collection can use third-party statistical services for data collection and preliminary analysis. This method requires ensuring the legality and security of the data.

[0087] Data storage and management can include data storage, data model design, and data protection. Data storage can include, for example, relational databases, NoSQL databases, or data warehouses to support the storage and analysis of large-scale data sets. Data model design can include, for example, table structures, field types, index optimization, etc., to ensure the efficiency and queryability of data storage. Data protection can be to ensure that data storage complies with data protection regulations and company policies. For example, encrypt sensitive information for storage.

[0088] Data analysis and application can include data cleaning and transformation, data analysis, business decision-making, and automated report generation. Data cleaning and transformation are used to define data cleaning rules and processes, which can include outlier handling, missing value handling, etc., to ensure data quality. At the same time, define data transformation rules, such as data type conversion, data aggregation, etc., to meet the analysis requirements. Data analysis can include descriptive analysis, predictive analysis, and prescriptive analysis. Descriptive analysis is used to understand the frequency, time distribution, etc. of user behavior; predictive analysis is used to predict users' future behavior; prescriptive analysis is used to recommend strategies for optimizing the purchase process. Business decision-making can be to support business decisions using the results of data analysis, such as optimizing product recommendation algorithms, adjusting promotion strategies, improving user experience, etc. Automated report generation can be, for example, based on an automated report system, regularly providing analysis reports on user behavior and business metrics to key stakeholders so that they can timely understand the business situation and make decisions.

[0089] By defining the data tracking template, the collection and analysis processing of data can be automatically achieved.

[0090] For the conversion analysis scenario, the data tracking template can also specify the analysis link. For example, point a corresponds to the first step of the conversion link, point b corresponds to the second step of the conversion link.....

[0091] Manual data tracking can collect data tracking information at the user interface layer. The user interface layer is the part of the application that directly interacts with users, responsible for presenting information, receiving user input, and passing users' operations to other parts of the application for processing. It is the bridge between users and the system and directly affects user experience and the usability of the application.

[0092] Through the information processing method of the embodiments of the present disclosure, by combining manual data tracking and automatic data tracking, complex business logics can be supported.

[0093] In some embodiments, presenting the processing result can include:

[0094] In response to a third operation input via the visualization interface, import the processing result into a pre-configured data display template for presentation.

[0095] According to the embodiments of the present disclosure, when constructing an orchestration analysis system, report templates can also be used, such as conversion analysis report templates, revenue analysis report templates, population analysis report templates, etc., and the visual drag-and-drop technology is also adopted to present in an intuitive graphical interface interaction manner. After obtaining the processing result, the control corresponding to the processing result can be dragged to the control corresponding to the report template to achieve visual presentation based on the report template. The presentation methods can be, for example, line charts, bar charts, or funnel charts, or tables, etc.

[0096] Through the information processing method of the embodiments of the present disclosure, since the data report is templated in advance and presented in an intuitive graphical interface interaction manner using the visual drag-and-drop technology, non-technical personnel can flexibly select different visualization methods on the visual interface for display, improving the flexibility and practicality of information processing.

[0097] In some embodiments, the processing result includes at least one of the following:

[0098] The actual data value of the target buried point information;

[0099] The predicted data value of the target buried point information;

[0100] The abnormal data item in the target buried point information.

[0101] The actual data value can be, for example, the number of successful user purchases, the predicted data value can be, for example, the number of successful user purchases in a future time period, and the abnormal data item can be, for example, an abnormal field value (such as a negative number in the age field, an invalid value in the gender field), a timestamp error (such as the event time being earlier than the user login time), and so on.

[0102] Through the information processing method of the embodiments of the present disclosure, data can be displayed diversely so that users can obtain effective information more intuitively and efficiently.

[0103] In some embodiments, the buried point methods include at least one of the following:

[0104] Code buried point, visual buried point, full buried point, hybrid buried point, client buried point, server buried point.

[0105] The buried point events include at least one of the following:

[0106] User behavior events, business operation events, system status events, interaction process events, custom events.

[0107] According to the embodiments of the present disclosure, code buried point can be to manually insert buried point code in the application code to record user behavior data; visual buried point can be to configure buried point rules through a visual interface without modifying the code; full buried point automatically collects user behavior data through technical means without manual buried point configuration; hybrid buried point can be to combine multiple buried point methods and flexibly select according to business requirements; client buried point can be to collect user behavior data on the client (such as APP, Web front-end); server buried point can be to record user behavior data on the server (such as API requests, business logic). It should be understood that the collection of user behavior data has obtained the authorization of the users.

[0108] The following will combine Figure 7 to schematically describe an information processing device according to an embodiment of the present disclosure.Figure 7 It is a block diagram of an information processing device according to an embodiment of the present disclosure.

[0109] As Figure 7 shown, the information processing device 700 may include a response module 710, a generation module 720, a display module 730, and a presentation module 740.

[0110] The response module 710 is configured to generate first information corresponding to a first operation in response to the first operation input via the visual interface, where the first information is used to characterize the combination of data collection methods or the combination of data collection events for collecting target data collection information and the processing requirements for the target data collection information.

[0111] The generation module 720 is configured to generate a target query statement based on the first information.

[0112] The processing module 730 is configured to process the target data collection information obtained from the pre-stored data collection information based on the target query statement to obtain a processing result.

[0113] The presentation module 740 is configured to present the processing result.

[0114] According to an embodiment of the present disclosure, generating a target query statement based on the first information includes:

[0115] Determining query parameters and processing parameters for processing the target data collection information based on the first information and second information associated with the first information; the second information characterizes the data collection components used to collect the target data collection information.

[0116] Generating a target query statement by adding the query parameters and processing parameters to a predefined target query statement template.

[0117] According to an embodiment of the present disclosure, determining query parameters and processing parameters based on the first information and second information associated with the first information includes:

[0118] Inputting the first information and the second information associated with the first information into a large model, and outputting the query parameters and processing parameters, where the large model is used to semantically understand the first information and the second information.

[0119] According to an embodiment of the present disclosure, the information processing method further includes:

[0120] Presenting the target query statement.

[0121] In response to a second operation input via the visual interface, modifying the query parameters and processing parameters in the target query statement.

[0122] According to an embodiment of the present disclosure, the acquisition method of the pre-stored data collection information includes at least one of the following:

[0123] Collect buried point information at the user interface layer based on visual buried points.

[0124] During the pipeline compilation of the buried point object, obtain the buried point information by scanning the buried point code.

[0125] According to an embodiment of the present disclosure, display the processing result, including:

[0126] In response to a third operation input via the visual interface, import the processing result into a pre-configured data display template for display.

[0127] According to an embodiment of the present disclosure, the processing result includes at least one of the following:

[0128] The actual data value of the target buried point information.

[0129] The predicted data value of the target buried point information.

[0130] Abnormal data items in the target buried point information.

[0131] According to an embodiment of the present disclosure, the buried point methods include at least one of the following:

[0132] Code buried points, visual buried points, full buried points, hybrid buried points, client buried points, server buried points.

[0133] The buried point events include at least one of the following:

[0134] User behavior events, business operation events, system status events, interaction process events, custom events.

[0135] It should be noted that the details of other embodiments of the information processing device and the technical effects brought are the same as or similar to the details of the embodiments of the information processing method, and will not be elaborated here.

[0136] The following will be combined with Figure 8 Schematically describe an electronic device according to an embodiment of the present disclosure. Figure 8 It is a block diagram of an electronic device according to an embodiment of the present disclosure.

[0137] As Figure 8 shown, the electronic device 800 may include at least one processor 810 and a memory 820.

[0138] The memory 820 is communicatively connected to at least one processor 810. Among them, the memory 820 stores instructions executable by the at least one processor 810, and the instructions are executed by the at least one processor 810 so that the at least one processor 810 can execute the information processing method provided by the embodiments of the present disclosure.

[0139] According to an embodiment of the present disclosure, the electronic device 800 may further include:

[0140] A display device 830, communicatively connected to at least one of the processors 810 and 820. The display device 830 includes a display area in which a visual interface is displayed. A user can perform an operation in the display area of the display device to display the visual interface, and then input a corresponding operation via the visual interface, so that the processor 810 executes the information processing method provided by the embodiment of the present disclosure.

[0141] It should be noted that the details of other embodiments of the electronic device and the technical effects brought about are the same as or similar to the details of the embodiments of the information processing method, and will not be elaborated herein.

[0142] According to an embodiment of the present disclosure, the present disclosure also provides an electronic device, a readable storage medium, and a computer program product.

[0143] Figure 9 A schematic block diagram of an exemplary electronic device 900 that can be used to implement the embodiments of the present disclosure is shown. The electronic device is intended to represent various forms of digital computers, such as, a laptop computer, a desktop computer, a workbench, a personal digital assistant, a server, a blade server, a mainframe computer, and other suitable computers. The electronic device can also represent various forms of mobile devices, such as, a personal digital processor, a cellular phone, a smart phone, a wearable device, and other similar computing devices. The components shown herein, their connections and relationships, and their functions are merely examples and are not intended to limit the implementation of the present disclosure described and / or claimed herein.

[0144] As Figure 9 shown, the device 900 includes a computing unit 901, which can execute various appropriate actions and processes according to a computer program stored in a read-only memory (ROM) 902 or a computer program loaded from a storage unit 908 into a random access memory (RAM) 903. In the RAM 903, various programs and data required for the operation of the device 900 can also be stored. The computing unit 901, the ROM 902, and the RAM 903 are connected to each other via a bus 904. An input / output (I / O) interface 905 is also connected to the bus 904.

[0145] Multiple components in device 900 are connected to I / O interface 905, including: input unit 906, such as a keyboard, mouse, etc.; output unit 907, such as various types of displays, speakers, etc.; storage unit 908, such as a disk, optical disc, etc.; and communication unit 909, such as a network card, modem, wireless communication transceiver, etc. Communication unit 909 allows device 900 to exchange information / data with other devices via a computer network such as the Internet and / or various telecommunication networks.

[0146] Computing unit 901 can be various general-purpose and / or special-purpose processing components with processing and computing capabilities. Some examples of computing unit 901 include, but are not limited to, a central processing unit (CPU), a graphics processing unit (GPU), various dedicated artificial intelligence (AI) computing chips, various computing units running machine learning model algorithms, a digital signal processor (DSP), and any suitable processor, controller, microcontroller, etc. Computing unit 901 executes the various methods and processes described above, such as a text processing method and / or a deployment method of a deep learning framework. For example, in some embodiments, the text processing method and / or the deployment method of the deep learning framework can be implemented as a computer software program that is tangibly contained in a machine-readable medium, such as storage unit 908. In some embodiments, part or all of the computer program can be loaded and / or installed onto device 900 via ROM 902 and / or communication unit 909. When the computer program is loaded into RAM 903 and executed by computing unit 901, one or more steps of the text processing method and / or the deployment method of the deep learning framework described above can be executed. Alternatively, in other embodiments, computing unit 901 can be configured to execute the text processing method and / or the deployment method of the deep learning framework by any other suitable means (e.g., by means of firmware).

[0147] The various embodiments of the systems and techniques described above in this specification can be implemented in digital electronic circuitry, integrated circuit systems, field programmable gate arrays (FPGAs), application specific integrated circuits (ASICs), application specific standard parts (ASSPs), system on chip (SOC) systems, complex programmable logic devices (CPLDs), computer hardware, firmware, software, and / or combinations thereof. These various embodiments can include: being implemented in one or more computer programs that are executable and / or interpretable on a programmable system including at least one programmable processor, which may be a special-purpose or general-purpose programmable processor that receives data and instructions from, and transmits data and instructions to, a storage system, at least one input device, and at least one output device.

[0148] The program code for implementing the methods of the present disclosure can be written in any combination of one or more programming languages. These program codes can be provided to a processor or controller of a general purpose computer, special purpose computer, or other programmable information processing device, such that the program codes, when executed by the processor or controller, cause the functions / operations specified in the flowcharts and / or block diagrams to be implemented. The program code can be executed entirely on the machine, partly on the machine, as a stand-alone software package partly on the machine and partly on a remote machine, or entirely on the remote machine or server.

[0149] In the context of this disclosure, a machine-readable medium can be a tangible medium that can contain or store a program for use by or in connection with an instruction execution system, apparatus, or device. A machine-readable medium can be a machine-readable signal medium or a machine-readable storage medium. A machine-readable medium can include, but is not limited to, electronic, magnetic, optical, electromagnetic, infrared, or semiconductor systems, apparatus, or devices, or any suitable combination of the foregoing. More specific examples of a machine-readable storage medium would include an electrical connection based on one or more wires, a portable computer diskette, a hard disk, a random access memory, a read-only memory, an erasable programmable read-only memory (EPROM) or flash memory, an optical fiber, a portable compact disc read-only memory (CD-ROM), an optical storage device, a magnetic storage device, or any suitable combination of the foregoing.

[0150] In order to provide interaction with a user, the systems and techniques described herein can be implemented on a computer having: a display device for displaying information to the user (e.g., a cathode ray tube (CRT) display or a liquid crystal display (LCD)); and a keyboard and a pointing device (e.g., a mouse or a trackball) by which the user can provide input to the computer. Other kinds of devices can also be used to provide interaction with the user; for example, the feedback provided to the user can be any form of sensory feedback (e.g., visual feedback, auditory feedback, or tactile feedback); and input from the user can be received in any form (including acoustic input, speech input, or tactile input).

[0151] The systems and techniques described herein can be implemented in a computing system that includes backend components (e.g., as a data server), or a computing system that includes middleware components (e.g., an application server), or a computing system that includes frontend components (e.g., a user computer having a graphical user interface or a web browser through which the user can interact with an implementation of the systems and techniques described herein), or a computing system that includes any combination of such backend components, middleware components, or frontend components. The components of the system can be interconnected by any form or medium of digital data communication (e.g., a communication network). Examples of communication networks include: a local area network (LAN), a wide area network (WAN), and the Internet.

[0152] A computer system may include a client and a server. The client and the server are generally remote from each other and typically interact via a communication network. The relationship between the client and the server is generated by computer programs that run on the respective computers and have a client-server relationship with each other.

[0153] It should be understood that the various forms of processes shown above may be used, with steps reordered, added, or deleted. For example, the steps described in this disclosure may be executed in parallel, sequentially, or in a different order, as long as the desired results of the technical solutions disclosed in this disclosure can be achieved, and no limitations are imposed herein.

[0154] The above specific embodiments do not constitute a limitation on the protection scope of this disclosure. Those skilled in the art should understand that various modifications, combinations, sub-combinations, and substitutions can be made according to design requirements and other factors. Any modifications, equivalent substitutions, and improvements made within the spirit and principles of this disclosure shall be included within the protection scope of this disclosure.

Claims

1. An information processing method, comprising: responding to a first operation input via a visual interface, generating first information corresponding to the first operation, the first information characterizing a combination of data logging methods or a combination of data logging events for obtaining target data logging information and a processing requirement for the target data logging information; generating a target query statement based on the first information; processing the target data logging information obtained from pre-stored data logging information based on the target query statement to obtain a processing result; and displaying the processing result.

2. The method according to claim 1, wherein, The generating a target query statement based on the first information includes: determining query parameters and processing parameters for processing the target data logging information based on the first information and second information associated with the first information; the second information characterizes a data logging component used for collecting the target data logging information; and generating the target query statement by adding the query parameters and the processing parameters to a predefined target query statement template.

3. The method according to claim 2, wherein The determining query parameters and processing parameters for processing the target data logging information based on the first information and second information associated with the first information includes: inputting the first information and the second information associated with the first information into a large model, and outputting the query parameters and the processing parameters, the large model being used for semantic understanding of the first information and the second information.

4. The method according to claim 1 or 2, further comprising: displaying the target query statement; responding to a second operation input via the visual interface, and modifying the query parameters and the processing parameters in the target query statement.

5. The method according to claim 1, wherein The obtaining method of the pre-stored data logging information includes at least one of the following: collecting the data logging information based on visual data logging at the user interface layer; obtaining the data logging information by scanning data logging code during the pipeline compilation of a data logging object.

6. The method according to claim 2, wherein The displaying the processing result includes: responding to a third operation input via the visual interface, and importing the processing result into a pre-configured data display template for display.

7. The method according to claim 1 or 6, wherein The processing result includes at least one of the following: the actual data value of the target data logging information; the predicted data value of the target data logging information; abnormal data items in the target data logging information.

8. The method according to claim 1, wherein The data logging method includes at least one of the following: code data logging, visual data logging, full data logging, hybrid data logging, client-side data logging, server-side data logging; The data logging event includes at least one of the following: user behavior events, business operation events, system status events, interaction process events, custom events.

9. An information processing apparatus, comprising: a response module, configured to respond to a first operation input via a visual interface, and generate first information corresponding to the first operation, the first information being used to characterize a combination of data logging methods or a combination of data logging events for collecting target data logging information and a processing requirement for the target data logging information; a generation module, configured to generate a target query statement based on the first information; A processing module, configured to process target buried point information obtained from pre-stored buried point information based on the target query statement to obtain a processing result; and A display module, configured to display the processing result.

10. An electronic device, comprising: At least one processor; and A memory communicatively connected to the at least one processor; wherein, The memory stores instructions executable by the at least one processor, and the instructions are executed by the at least one processor to enable the at least one processor to execute the method according to any one of claims 1 to 8.

11. The electronic device according to claim 10, further comprising: A display device communicatively connected to the at least one processor, the display device includes a display area, and a visualization interface is displayed in the display area.

12. A non-transitory computer-readable storage medium storing computer instructions, wherein, The computer instructions are used to cause the computer to execute the method according to any one of claims 1 to 8.

13. A computer program product, comprising a computer program, which when executed by a processor, implements the method according to any one of claims 1 to 8.

Images