CN-122019631-A - Resume processing system and method for recruitment platform

CN122019631ACN 122019631 ACN122019631 ACN 122019631ACN-122019631-A

Abstract

The application discloses a resume processing system and method for a recruitment platform. The system comprises a Web management console, a trigger, a scheduler, a message queue, a trigger and a resume processing instruction, wherein the Web management console is used for providing a visual interface for managing resume processing tasks, the trigger is used for initiating resume processing requests to the scheduler when preset trigger conditions are met, the scheduler is used for dividing a resume data set into a plurality of resume data fragments and generating a plurality of resume processing tasks comprising resume data fragments and resume processing logic, recommending executor types are marked for each resume processing task, the message queue is used for storing the plurality of resume processing tasks, each executor is used for calling resume processing tasks of the recommended executor types from the message queue, the resume processing logic in the resume processing tasks is converted into resume processing instructions which are locally operated by the executor, and the resume data fragments in the resume processing tasks are processed based on the resume processing instructions. The application can realize the rapid update of resume data and reduce the complexity of operation and maintenance.

Inventors

LI SHENGTANG
LI XIANGHUA
Du Baokun

Assignees

前锦网络信息技术(上海)有限公司

Dates

Publication Date: 20260512
Application Date: 20251223

Claims (10)

1. A resume processing system for a recruitment platform, comprising a Web management console, a trigger, a scheduler, a message queue, and a plurality of actuators: The Web management console is used for providing a visual interface for managing resume processing tasks; The trigger is used for initiating a resume processing request to the scheduler when the trigger is monitored to meet a preset trigger condition, wherein the resume processing request comprises the identification of each resume data in a resume data set to be processed; The scheduler is used for acquiring a resume data set according to the identification, dividing the resume data set into a plurality of resume data fragments, generating a plurality of resume processing tasks comprising at least one resume data fragment and resume processing logic, and marking a recommended executor type for each resume processing task according to equipment information of a plurality of executors; The message queue is used for receiving and storing a plurality of resume processing tasks; Each executor is used for calling resume processing tasks of recommended executor types corresponding to the equipment information of the executor from the message queue, converting resume processing logic in the resume processing tasks into resume processing instructions which are locally operated by the executor, and processing resume data fragments in the resume processing tasks based on the resume processing instructions.
2. The system of claim 1, wherein the plurality of actuators are heterogeneous actuators, at least some of which differ in hardware configuration, operating system type, and/or software operating environment from one actuator to another; The preset triggering condition comprises at least one of the following steps that a preset time period is reached, business events related to resume are monitored, and the CPU idle rate and/or the memory idle rate of at least one actuator are/is monitored to exceed a preset threshold value.
3. The system of claim 1, wherein the scheduler is specifically configured to divide a resume data set into a plurality of resume data fragments according to an activity level of a job-seeking user, a delivery time of a resume, an area where the job-seeking user is located, or an industry category in resume data, wherein a plurality of resume data of a same activity level, a same delivery time range, a same area, or a same industry category are divided into a same resume data fragment.
4. A system according to claim 3, wherein an environmental adapter and an execution engine are provided within each actuator; the environment adapter is used for selecting a corresponding target instruction mapping rule from a preset instruction mapping rule set according to the type of a local operating system, and mapping resume processing logic described in a declarative language or a general interface in a resume processing task into resume processing instructions executed in a local command line or a script interpreter according to the target instruction mapping rule; The execution engine is used for executing at least one of the following processes on the resume data in the resume data fragments based on the resume processing instruction, wherein the resume data comprises the following steps of cleaning, normalizing and information extracting, evaluating the activity of the resume data, grading the quality of the resume data, calculating the matching degree of the resume data and the positions, and updating the characteristic representation of the resume data in the recommendation system.
5. The system of claim 4, wherein the activity evaluation of the resume data comprises: Acquiring behavior data of a job seeker to which resume data belong, wherein the behavior data comprises at least one of login frequency, historical activity level, number of job checking times, number of resume delivery times and number of communication times with a recruitment enterprise of the job seeker on a recruitment platform; Invoking a preset user activity analysis model, and calculating activity scores of job-seeking users based on behavior data of the job-seeking users; According to the activity score, an activity state label is distributed to resume data, wherein the activity state label comprises at least one of a high activity state, a general activity state, a low activity state and a state to be cleaned; and setting the display priority of the resume data in a platform recommendation list or search results according to the active state label.
6. The system according to claim 1, wherein the scheduler is specifically configured to perform the following: Analyzing resume data fragments and resume processing logic in resume processing tasks, and determining data processing feature categories of the resume data fragments; Acquiring equipment performance information of each actuator by inquiring an actuator registry; Recommending an actuator type for the resume processing task mark based on the matching relation between the data processing characteristic category of the resume data fragment and the equipment performance information.
7. The system of claim 6, wherein analyzing the resume data shards and resume processing logic in the resume processing task to determine the class of data processing characteristics of the resume data shards comprises: Acquiring attribute information of the resume data fragments and configuration information of resume processing logic; Estimating the calculation complexity and the data access amount score of the resume data fragment based on the attribute information and the configuration information; if the calculation complexity is greater than a preset complexity threshold, determining that the data processing feature class is computationally intensive; if the data access quantity score is larger than a preset access quantity threshold value, determining that the data processing characteristic class is input-output intensive; if the calculation complexity is smaller than or equal to a preset complexity threshold value and the data access volume fraction is smaller than or equal to a preset access volume threshold value, determining that the data processing characteristic type is balanced or conventional.
8. The system of claim 7, wherein the device performance information includes a computational performance score and a storage input-output performance score; Recommending an actuator type for the resume processing task mark based on the matching relation between the data processing characteristic category of the resume data fragment and the equipment performance label, wherein the method comprises the following steps: If the data processing characteristic category is computationally intensive, screening out an actuator with a computational performance score greater than a first performance threshold from an actuator registry, and marking the recommended actuator type of the resume processing task as the type corresponding to the screened actuator; if the data processing characteristic category is intensive in input and output, screening out an actuator with the stored input and output performance score larger than a second performance threshold value from an actuator registry, and marking the recommended actuator type of the resume processing task as the type corresponding to the screened actuator; And if the data processing characteristic category is balanced or conventional, screening out the executors with the current load smaller than a load threshold, and marking the recommended executor type of the resume processing task as the type corresponding to the screened out executors.
9. The system of claim 1, wherein the Web management console's visualization interface comprises: The task configuration and release component is used for receiving user input, wherein the user input comprises setting a trigger condition of a resume processing task, a resume data range to be processed and resume processing logic to be executed; A heterogeneous resource monitor view component for displaying at least one of a device type, a current load state, a health, and a task processing queue of the plurality of actuators in a group or list; The task full-link tracking component is used for displaying the processing progress of any resume processing task and supporting the inquiry of detailed execution logs of each link in the resume processing process; The result statistics and report form component is used for carrying out aggregation analysis on the task results completed by the resume processing and displaying at least one of resume distribution change trend, task execution efficiency index and system resource consumption report in a chart form.
10. A resume processing method for a recruitment platform, the method being implemented based on the resume processing system for a recruitment platform according to any one of claims 1-9, the method comprising: Providing a visual interface for managing resume processing tasks; when the condition that the preset triggering condition is met is monitored, a resume processing request is initiated to a scheduler, wherein the resume processing request comprises identification of each resume data in a resume data set to be processed; The scheduler is used for acquiring the resume data set according to the identification, dividing the resume data set into a plurality of resume data fragments, generating a plurality of resume processing tasks, wherein each resume processing task comprises at least one resume data fragment and resume processing logic; the method comprises the steps of executing the following operations through each executor, calling resume processing tasks of recommended executor types corresponding to own equipment information from the message queue, converting resume processing logic in the called resume processing tasks into resume processing instructions running locally for the executor, and processing resume data fragments in the resume processing tasks based on the resume processing instructions.

Description

Resume processing system and method for recruitment platform Technical Field The application relates to the technical field of recruitment, in particular to a resume processing system and method for a recruitment platform. Background The core competitiveness of the recruitment platform is the quality and real-time performance of resume data. For resume data, a scheme commonly adopted in the industry at present is to configure a distributed timing task (such as Crontab) on a back-end server cluster, and periodically execute batch scripts to update resume states. In particular, conventional schemes typically employ fixed and low frequency batch processing cycles (e.g., once daily), which makes it difficult for the system to timely perceive and respond to the user's most recent active behavior, such as logging in, updating a resume, etc. The core functions of recommendation engines, talent searching and the like can only rely on outdated data, the accuracy is greatly reduced, and the user experience is seriously affected. Secondly, batch processing scripts in the traditional scheme are usually concentrated in the operation of low peak periods (such as early morning), so that a large amount of database connection and calculation resources can be occupied instantaneously, and interference is caused to other background operations (such as report generation) in the same period. During peak business hours, the system has difficulty in utilizing idle resources for data processing. In addition, the processing script and timing task for resume data are generally distributed on tens or even hundreds of heterogeneous servers, and the configuration, updating and monitoring work is complex. Moreover, script logic is hard coded, and is difficult to adaptively adjust according to the characteristics of different resume (such as job seeker industry and experience years) or the performance difference of different servers. Disclosure of Invention In view of the above, the embodiment of the application provides a resume processing system and a resume processing method for a recruitment platform, which are used for solving at least one of the above technical problems. In a first aspect, the embodiment of the application provides a resume processing system for a recruitment platform, which comprises a Web management console, a trigger, a scheduler, a message queue and a plurality of executors, wherein the Web management console is used for providing a visual interface for managing resume processing tasks, the trigger is used for initiating a resume processing request to the scheduler when the trigger is monitored to meet preset trigger conditions, the resume processing request comprises identifications of resume data in a resume data set to be processed, the scheduler is used for acquiring the resume data set according to the identifications, dividing the resume data set into a plurality of resume data fragments and generating a plurality of resume processing tasks comprising at least one resume data fragment and resume processing logic, the message queue is used for receiving and storing the resume processing tasks, each executor is used for calling the resume processing tasks of the recommended executor type corresponding to the device information from the message queue, the resume processing logic in the resume processing tasks is converted into resume processing tasks according to the identification, and the resume processing logic in the resume processing tasks are converted into resume processing instructions and run based on the resume processing instructions. According to some embodiments of the present application, optionally, the plurality of actuators are heterogeneous actuators, at least part of the actuators differ from each other in hardware configuration, operating system type and/or software running environment, wherein the preset trigger condition includes at least one of reaching a preset time period, detecting a traffic event related to the resume, and detecting that a CPU idle rate and/or a memory idle rate of at least one actuator exceeds a preset threshold. According to some embodiments of the present application, optionally, the scheduler is specifically configured to divide the resume data set into a plurality of resume data slices according to an activity level of the job seeker, a delivery time of the resume, an area where the job seeker is located, or an industry class in the resume data, where a plurality of resume data of a same activity level, a same delivery time range, a same area, or a same industry class are divided into a same resume data slice. According to some embodiments of the application, optionally, an environment adapter and an execution engine are arranged in each executor, the environment adapter is used for selecting a corresponding target instruction mapping rule from a preset instruction mapping rule set according to a local operating system type, mapping resume processing logic des