CN-121996496-A - Data embedding method, device, electronic equipment and storage medium

CN121996496ACN 121996496 ACN121996496 ACN 121996496ACN-121996496-A

Abstract

The invention relates to the technical field of data acquisition and analysis and discloses a data embedding method, a device, electronic equipment and a storage medium, wherein the method comprises the steps of selecting a preset triggering mode based on a service scene and constructing a multi-mode embedding point inlet based on the preset triggering mode; based on rule instance and requirement of collecting service scene, corresponding embedding point method is matched from preset rule-method mapping table, and embedding point strategy is generated based on embedding point method. The invention converts the traditional hard-coded and solidified embedded point logic into a highly flexible and configurable strategy driving mode through the core flow of configuring and constructing a multi-mode entrance, generating a rule instance of an adaptable service, dynamically matching and generating an embedded point strategy.

Inventors

XU YUYAN
SHENG QUN

Assignees

北京人笙智能科技有限公司

Dates

Publication Date: 20260508
Application Date: 20251202

Claims (10)

1. A method of embedding data, the method comprising: selecting a preset triggering mode based on a service scene, and constructing a multi-mode buried point entry based on the preset triggering mode; Generating a rule instance adapting to a service scene based on the multi-mode buried point entry and a preset rule type; based on the rule instance and the service scene acquisition requirement, matching a corresponding point burying method from a preset rule-method mapping table, and generating a point burying strategy based on the point burying method.
2. The method for embedding data according to claim 1, wherein the selecting a preset trigger mode based on the service scenario and constructing the multi-mode embedded point entry based on the preset trigger mode includes: The method comprises the steps of receiving a service scene selection instruction and a triggering mode choosing instruction, wherein the service scene selection instruction is used for determining a target scene from a predefined service scene library, and the triggering mode choosing instruction is used for choosing at least one mode from a plurality of preset triggering modes; calling a preset scene-trigger mode mapping relation based on the service scene selection instruction to obtain a recommended trigger mode combination adapted to the target scene; and generating a corresponding multi-mode embedded point entry based on the trigger mode choosing instruction or the recommended trigger mode combination, wherein the multi-mode embedded point entry adopts at least two of a page loading trigger mode, a user interaction trigger mode, a timing trigger mode, a condition meeting trigger mode, an API calling trigger mode and an SDK integrated trigger mode.
3. The method of claim 1, wherein generating a rule instance for adapting to a business scenario based on the multi-modal embedded point entry and a preset rule type comprises: Selecting a target rule type from preset rule types and rule parameters corresponding to the target rule type; inquiring a preset rule type-class mapping table based on the target rule type and the corresponding rule parameters, and acquiring a rule implementation class corresponding to the target rule type; instantiating the rule realization class through a reflection mechanism, and injecting the rule parameters into the rule realization class to generate an initial rule object; And verifying the validity of the rule parameters in the initial rule object, and generating a rule instance adapting to the service scene based on the verified initial rule object.
4. The method of claim 1, wherein matching a corresponding embedded point method from a preset rule-method mapping table based on the rule instance and the traffic scene acquisition requirement, and generating an embedded point policy based on the embedded point method, comprises: The candidate embedded point method comprises at least one of an immediate embedded point method, a batch embedded point method, a delayed embedded point method, a conditional embedded point method, a heartbeat embedded point method, a page stay embedded point method, an event driven embedded point method and a self-defined embedded point method; Determining a final target buried point method from the candidate buried point methods based on the service scene acquisition requirements; instantiating the target point burying method, associating corresponding rule examples, and combining to generate a point burying strategy.
5. The method of claim 4, wherein the matching of the corresponding embedded point method from the preset rule-method mapping table is based on the rule instance and the traffic scene acquisition requirement, further comprising: Receiving a new buried point method type, a new buried point method implementation class and a basic buried point method class, wherein the basic buried point method class comprises an immediate buried point method, a batch buried point method, a delayed buried point method, a conditional buried point method, a heartbeat buried point method, a page stay buried point method, an event driven buried point method and a self-defined buried point method; Verifying whether the new buried point method implementation class inherits from the basic buried point method class; and if inherited from the basic embedded point method type and the new embedded point method type does not exist in the preset rule-method mapping table, adding a new mapping relation into the preset rule-method mapping table.
6. The method for embedding data according to claim 1, characterized in that the method further comprises: Executing the buried point strategy to obtain effective buried point data; and carrying out multidimensional analysis and visualization processing on the effective buried data to generate a business analysis report and a visualization chart.
7. The method of claim 6, wherein said executing the embedding policy to obtain valid embedding data comprises: Responding to the triggering condition of the rule instance being met, executing the associated buried point method in the buried point strategy to acquire original buried point data; Packaging and standardizing the original buried data to generate data to be verified; And carrying out quality check on the data to be checked by adopting a seven-dimensional data check mechanism to obtain effective buried point data.
8. A data burial point device, said device comprising: The multi-mode buried point entrance construction module is used for selecting a preset triggering mode based on a service scene and constructing a multi-mode buried point entrance based on the preset triggering mode; the rule instance generation module is used for generating a rule instance adapting to the service scene based on the multi-mode buried point entry and a preset rule type; The embedded point strategy generation module is used for matching corresponding embedded point methods from a preset rule-method mapping table based on the rule examples and the service scene acquisition requirements, and generating embedded point strategies based on the embedded point methods.
9. An electronic device, comprising: a memory and a processor, the memory and the processor being communicatively connected to each other, the memory having stored therein computer instructions, the processor executing the computer instructions to perform the data embedding method of any of claims 1 to 7.
10. A computer-readable storage medium having stored thereon computer instructions for causing a computer to perform the data embedding method of any of claims 1 to 7.

Description

Data embedding method, device, electronic equipment and storage medium Technical Field The invention relates to the technical field of data acquisition and analysis, in particular to a data point burying method, a data point burying device, electronic equipment and a storage medium. Background With the deep digitization of internet services, user behavior data becomes a core basis for enterprise decision making, but the prior art has significant defects: 1. the traditional embedded point defects are that hard coding is needed to embed logic, a new embedded point (such as E-commerce commodity collection) needs to be modified and re-online, the adaptation efficiency is low, an expansion rule (such as only counting new user behaviors) needs to reconstruct a module, risks are easy to introduce, standardized verification is not needed, invalid data such as 'timestamp abnormality', 'user ID deletion', and the like are frequently generated, and the maintenance cost is high. 2. The existing buried point technology is insufficient in that although partial technology supports buried point configuration reading, the capability of multi-mode triggering and rule combination is lacking, and the problem of dynamic adaptation of buried point rules is not solved while partial data processing technology focuses on analysis and visualization. Therefore, a data embedding method for solving the problems of insufficient flexibility, poor expansibility, difficult data quality assurance, high maintenance cost, single trigger, uncombinable rule, embedding point and analysis dislocation in the prior art is needed. Disclosure of Invention The invention provides a data embedding method, a device, electronic equipment and a storage medium, which are used for solving the problems of insufficient flexibility, poor expansibility, difficult data quality assurance, high maintenance cost, single triggering, incapability of combining rules and disjointing embedding and analysis of the traditional embedding point configuration. In a first aspect, the present invention provides a method for embedding data, the method comprising: selecting a preset triggering mode based on a service scene, and constructing a multi-mode buried point entry based on the preset triggering mode; generating a rule instance adapting to the service scene based on the multi-mode buried point entry and a preset rule type; Based on rule examples and service scene acquisition requirements, matching corresponding embedded point methods from a preset rule-method mapping table, and generating embedded point strategies based on the embedded point methods. The invention provides a data embedding method, which converts the traditional hard-coded and solidified embedding point logic into a highly flexible and configurable strategy driving mode through a core flow of configurating and constructing a multi-mode entrance, generating a rule instance of an adaptable service, dynamically matching and generating embedding point strategy. The method directly solves the problem of single triggering through a multi-mode entrance, realizes flexible combination of rules and on-demand generation of strategies through generation of rule examples and dynamic matching of buried point methods, overcomes the defects of insufficient configuration flexibility, poor expansibility and incapability of combining the rules, and finally lays a solid foundation for realizing tight connection of buried points and analysis and reducing maintenance cost by the strategy configuration management system of the full link. In an alternative embodiment, selecting a preset triggering mode based on a service scenario, and constructing a multi-mode buried point entry based on the preset triggering mode, including: the method comprises the steps of receiving a service scene selection instruction and a triggering mode choosing instruction, wherein the service scene selection instruction is used for determining a target scene from a predefined service scene library, and the triggering mode choosing instruction is used for choosing at least one mode from a plurality of preset triggering modes; based on the service scene selection instruction, calling a preset scene-trigger mode mapping relation to obtain a recommended trigger mode combination matched with the target scene; and generating a corresponding multi-mode embedded point entry based on a trigger mode choosing instruction or a recommended trigger mode combination, wherein the multi-mode embedded point entry adopts at least two of a page loading trigger mode, a user interaction trigger mode, a timing trigger mode, a condition satisfaction trigger mode, an API calling trigger mode and an SDK integrated trigger mode. According to the data embedding method, intelligent recommendation is realized by introducing the preset scene-trigger mode mapping relation, and the multi-mode embedding entrance integrating at least two trigger modes is constructed by combining the auton