CN116911811A - Resume collection artificial intelligence big data system - Google Patents
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Abstract
The invention relates to the technical field of Internet recruitment, in particular to a resume collection artificial intelligent big data system which comprises a data acquisition module, a data cleaning and preprocessing module, an artificial intelligent module, a data storage and management module, a data analysis and visualization module and a user interface module. According to the system for collecting the artificial intelligence big data through the adoption of the artificial intelligence big data system, a large amount of resume data can be automatically collected, cleaned and preprocessed, the quality and the accuracy of the resume data can be improved through data cleaning, format conversion, standardization and missing value filling processing, meanwhile, the automatic resume screening and matching can be realized through the machine learning algorithm, the deep learning model and the natural language processing algorithm technology in the artificial intelligence module, the workload of a human resource department is greatly reduced, the resume processing efficiency is improved, and the problem that the workload is too large due to excessive resume is solved if manual screening is carried out through recruiters.
Description
Technical Field
The invention relates to the technical field of Internet recruitment, in particular to a resume collection artificial intelligence big data system.
Background
With the development and popularization of the internet, the life of the internet and people has been in a dense and inseparable relationship, wherein the retrieval of data is perfected and diversified, the internet is also a main way for recruiting staff and staff to apply enterprises, the internet recruitment is a way for talent recruitment through an internet platform, and the internet recruitment utilizes the internet technology and tools, so that recruiters and job seekers can more conveniently and efficiently conduct talent recruitment and job hunting activities.
However, at present, recruitment platforms are numerous, many enterprises can put in recruitment information on a plurality of platforms at the same time, and the resume received by a plurality of hot posts every day can reach tens or even hundreds of parts, and after screening is completed, relevant recruiters are informed to participate in interviews, and because the resume is too many, if manual screening is performed by the recruiters, the workload is too great, the required recruiters are also more, so that the expense of the enterprises in recruiting staff is increased, and therefore, a resume collection artificial intelligence big data system is provided.
Disclosure of Invention
(one) solving the technical problems
Aiming at the defects of the prior art, the invention provides a resume collection artificial intelligence big data system, which has the advantages of realizing automatic resume screening and matching, solves the problems that at present recruitment platforms are numerous, many enterprises can put recruitment information in a plurality of platforms at the same time, the resume received by a plurality of hot posts every day can reach tens or even hundreds of parts, the resume needs to be initially screened, and after screening is finished, relevant recruiters are notified to participate in interviews, and because the resume is too many, if the recruiter is used for manual screening, the workload is too great, and the required recruiters are more, thereby increasing the expense of the enterprises on the recruiters.
(II) technical scheme
In order to achieve the aim of realizing automatic resume screening and matching, the invention provides the following technical scheme: a resume collection artificial intelligence big data system comprises a data acquisition module, a data cleaning and preprocessing module, an artificial intelligence module, a data storage and management module, a data analysis and visualization module and a user interface module;
the data acquisition module comprises a data source interface, a data acquisition device and a data buffer;
the data cleaning and preprocessing module comprises data cleaning, data format conversion, standardization and missing value filling and characteristic engineering;
the artificial intelligence module comprises a machine learning algorithm and model, a deep learning model and a natural language processing algorithm;
the data storage and management module comprises a database management system and a data storage medium;
the data analysis and visualization module comprises a statistical analysis tool, a data mining algorithm and a data visualization tool;
the user interface module includes a graphical interface, a command line interface, and a Web interface.
Preferably, the data collector in the data collection module is in communication connection with an external data source through a data source interface, acquires original data from the external data source, and performs preliminary processing and conversion on the data, wherein the external data source is each large recruitment platform.
Preferably, the original data acquired by the data acquisition device from the external data source in the data acquisition module is temporarily stored in the data buffer for subsequent processing and transmission, and the original data is resume information of the job seeker, including name, gender, age, work experience, education experience and salary requirements of the job seeker.
Preferably, the data cleaning and preprocessing module performs denoising, outlier detection and processing on the original data, ensures the quality and accuracy of the data, converts the original data into a uniform format by data format conversion and standardization for subsequent analysis and use, fills in missing values in the data by missing value filling and feature engineering, and performs feature selection and feature transformation to extract useful features.
Preferably, the machine learning algorithm and model in the artificial intelligence module comprise various supervised learning, unsupervised learning and reinforcement learning algorithms and models for analyzing, mining and predicting data, the deep learning model uses a deep neural network for feature learning and pattern recognition of data, and the natural language processing algorithm is used for processing text data, including text classification, emotion analysis and machine translation.
Preferably, the database management system of the data storage and management module can store and manage the cleaned and processed data to provide an operation of adding, deleting and checking the data, and the data storage medium is used for long-term storage of the data and comprises magnetic disk, optical disk, floppy disk and mobile hard disk.
Preferably, the statistical analysis tool of the data analysis and visualization module is used for performing statistical analysis on the data, including descriptive statistics, hypothesis testing and regression analysis; and the data mining algorithm is used for finding patterns, rules and correlations from a large amount of data; the data visualization tool visually displays analysis results in the form of charts, images and maps so that a user can better understand the data.
Preferably, the graphical interface in the user interface module is used for a user to interact with the system in a graphical mode, the user inputs instructions to interact with the system through a command line interface, and the Web interface is used for the user to access the system through a browser, so that functions of inquiring data, setting parameters and viewing analysis results are provided.
(III) beneficial effects
Compared with the prior art, the invention provides a resume collection artificial intelligence big data system, which has the following beneficial effects:
1. according to the system for collecting the artificial intelligence big data through the manual intelligence big data system, a large amount of resume data can be automatically collected, cleaned and preprocessed, the quality and the accuracy of the resume data can be improved through data cleaning, format conversion, standardization and missing value filling processing, meanwhile, the automatic resume screening and matching can be realized through the machine learning algorithm, the deep learning model and the natural language processing algorithm technology in the manual intelligence module, the workload of a human resource department is greatly reduced, and the resume processing efficiency is improved.
2. According to the resume collection artificial intelligent big data system, the data analysis and visualization module in the artificial intelligent big data system is provided, a statistical analysis tool, a data mining algorithm and a data visualization tool are provided, key information and talent characteristics can be extracted through deep analysis and mining of collected resume data, data-driven decision support is provided for talent recruitment, analysis results and a visualization chart can help human resource departments to better know trends and demands of talent markets, a more scientific recruitment strategy is formulated, and recruitment effects and talent matching degree are improved.
Drawings
FIG. 1 is a schematic diagram of a system architecture of the present invention;
FIG. 2 is a block diagram of a system architecture of the present invention;
FIG. 3 is a block diagram of a system resume processing flow of the present invention.
Detailed Description
The following description of the embodiments of the present invention will be made clearly and fully with reference to the accompanying drawings, in which it is evident that the embodiments described are only some, but not all embodiments of the invention. All other embodiments, which can be made by those skilled in the art based on the embodiments of the invention without making any inventive effort, are intended to be within the scope of the invention.
Referring to fig. 1 to 3, a resume collection artificial intelligence big data system includes a data acquisition module, a data cleaning and preprocessing module, an artificial intelligence module, a data storage and management module, a data analysis and visualization module and a user interface module;
the data acquisition module comprises a data source interface, a data acquisition device and a data buffer;
the data cleaning and preprocessing module comprises data cleaning, data format conversion, standardization and missing value filling and characteristic engineering;
the artificial intelligent module comprises a machine learning algorithm and model, a deep learning model and a natural language processing algorithm;
the data storage and management module comprises a database management system and a data storage medium;
the data analysis and visualization module comprises a statistical analysis tool, a data mining algorithm and a data visualization tool;
the user interface module includes a graphical interface, a command line interface, and a Web interface.
Specifically, the data collector in the data collection module is in communication connection with an external data source through a data source interface, acquires original data from the external data source, performs preliminary processing and conversion on the data, and the external data source is a large recruitment platform.
Furthermore, by establishing connection with each large recruitment platform, a large amount of original resume data can be acquired and integrated into a unified data set, in the data integration process, the acquired data is preprocessed, such as cleaning, format conversion and standardization, so that the quality and accuracy of the data are improved, meanwhile, the resume data are updated periodically or in real time, the timeliness of the data is ensured, and the data preparation work provides a basis for subsequent data analysis and talent matching, so that enterprises are helped to better know the background and the capability of job seekers, and further more accurate recruitment decisions are made.
Specifically, the original data acquired by the data acquisition device from the external data source in the data acquisition module can be temporarily stored in the data buffer for subsequent processing and transmission, wherein the original data is resume information of the job seeker, and the resume information comprises names, sexes, ages, working experiences, education experiences and salary requirements of the job seeker.
Further, resume information of the job seeker is obtained from an external data source through the data collector and is temporarily stored in the data buffer, so that subsequent processing and transmission are facilitated, and accurate and timely job seeker information is provided for recruitment processes.
Specifically, the data cleaning in the data cleaning and preprocessing module performs denoising, outlier detection and processing on the original data, so as to ensure the quality and accuracy of the data, the data format conversion and standardization convert the original data into a unified format for subsequent analysis and use, and fill up the missing values in the data through missing value filling and feature engineering, and simultaneously perform feature selection and feature transformation so as to extract useful features.
Furthermore, the data cleaning and preprocessing module is used for denoising, outlier detection and processing of the original data, so that the quality and accuracy of the data are ensured, meanwhile, the original data are converted into a unified format through data format conversion and standardization so as to be convenient for subsequent analysis and use, in addition, the missing values in the data are filled through missing value filling and feature engineering, feature selection and feature transformation are carried out so as to extract useful features, and through the processing and conversion, the data with high quality, consistency and integrity can be provided, so that an accurate and reliable basis is provided for subsequent data analysis and talent matching.
Specifically, the machine learning algorithms and models in the artificial intelligence module include various supervised learning, unsupervised learning and reinforcement learning algorithms and models for analyzing, mining and predicting data, the deep learning model uses a deep neural network for feature learning and pattern recognition of data, and the natural language processing algorithm is used for processing text data, including text classification, emotion analysis and machine translation.
Further, the supervised learning algorithm and model can be used for classifying, regressing and predicting tasks through the existing marked data, so that characteristics of job seekers, such as suitability and competence of the job seekers, can be analyzed, the unsupervised learning algorithm and model can be used for finding potential modes and association rules in the data, helping enterprises to know the characteristics and professional trends of the job seekers deeply, and the reinforced learning algorithm and model can be used for optimizing decision strategies through interactive learning with the environment, so that enterprises can make more intelligent choices in recruitment processes.
In particular, the database management system of the data storage and management module can store and manage the cleaned and processed data to provide the operations of adding, deleting and checking the data, and the data storage medium is used for long-term storage of the data and comprises magnetic discs, optical discs, floppy discs and mobile hard discs.
Furthermore, the data storage and management module is used for effectively storing, managing and long-term storing the cleaned and processed data through the database management system of the data storage and management module and the selection and management of the data storage medium, so that a reliable basis is provided for the subsequent data analysis, inquiry and use.
Specifically, the statistical analysis tool of the data analysis and visualization module is used for carrying out statistical analysis on the data, including descriptive statistics, hypothesis testing and regression analysis; and the data mining algorithm is used for finding patterns, rules and correlations from a large amount of data; the data visualization tool visually displays analysis results in the form of charts, images and maps so that a user can better understand the data.
Furthermore, through the data analysis and visualization module, statistical analysis, data mining and visualization display of the data are realized, a user is helped to understand the data deeply, patterns and rules in the data are found, analysis results are intuitively transmitted to the user through a visualization display mode, and more accurate, comprehensive and visual support is provided for decision making.
Specifically, the graphical interface in the user interface module is used for a user to interact with the system in a graphical mode, the user inputs instructions to interact with the system through the command line interface, and the Web interface is used for the user to access the system through the browser, so that functions of inquiring data, setting parameters and viewing analysis results are provided.
Furthermore, through the graphical interface, the command line interface and the Web interface in the user interface module, various modes are provided for the user to interact with the system, different requirements and use habits of the user are met, the user can operate through the visual and easy-to-use graphical interface, can perform batch processing through the flexible and efficient command line interface, and can access the system at any time and any place through the online Web interface, so that the purposes of data analysis and visualization are realized.
In summary, the system for collecting the artificial intelligence big data by the resume can automatically collect, clean and preprocess a large amount of resume data by adopting the artificial intelligence big data system, and can improve the quality and accuracy of the resume data by data cleaning, format conversion, standardization and missing value filling processing.
In addition, the resume collects the artificial intelligence big data system, a data analysis and visualization module in the artificial intelligence big data system provides a statistical analysis tool, a data mining algorithm and a data visualization tool, key information and talent characteristics can be extracted through deep analysis and mining of collected resume data, data-driven decision support is provided for talent recruitment, analysis results and a visualization chart can help a human resource department to better know trends and demands of talent markets, a more scientific recruitment strategy is formulated, recruitment effect and talent matching degree are improved, the problem that a plurality of current recruitment platforms are solved, a plurality of enterprises can simultaneously put recruitment information in a plurality of platforms, a plurality of resume received by a plurality of hot posts can reach tens or even hundreds of resume each day, the resume is required to be screened initially, and after the completion of screening, relevant recruiters are informed of participating in the interviews, and due to the fact that the resume is too much, if the recruiters are required to be screened manually, the recruiters are required to be too much, and accordingly the problem of the recruitment staff is increased in the aspect of the aspects of the cost of the enterprises is increased.
The related modules involved in the system are all hardware system modules or functional modules in the prior art combining computer software programs or protocols with hardware, and the computer software programs or protocols involved in the functional modules are all known technologies for those skilled in the art and are not improvements of the system; the system is improved in interaction relation or connection relation among the modules, namely, the overall structure of the system is improved, so that the corresponding technical problems to be solved by the system are solved.
Although embodiments of the present invention have been shown and described, it will be understood by those skilled in the art that various changes, modifications, substitutions and alterations can be made therein without departing from the principles and spirit of the invention, the scope of which is defined in the appended claims and their equivalents.
Claims (8)
1. The resume collection artificial intelligence big data system is characterized by comprising a data acquisition module, a data cleaning and preprocessing module, an artificial intelligence module, a data storage and management module, a data analysis and visualization module and a user interface module;
the data acquisition module comprises a data source interface, a data acquisition device and a data buffer;
the data cleaning and preprocessing module comprises data cleaning, data format conversion, standardization and missing value filling and characteristic engineering;
the artificial intelligence module comprises a machine learning algorithm and model, a deep learning model and a natural language processing algorithm;
the data storage and management module comprises a database management system and a data storage medium;
the data analysis and visualization module comprises a statistical analysis tool, a data mining algorithm and a data visualization tool;
the user interface module includes a graphical interface, a command line interface, and a Web interface.
2. The system of claim 1, wherein the data collector in the data collection module is communicatively connected to an external data source via a data source interface, obtains raw data from the external data source, and performs preliminary processing and conversion on the data, and the external data source is each recruitment platform.
3. The system of claim 1, wherein the raw data obtained by the data collector from the external data source in the data collection module is temporarily stored in the data buffer for subsequent processing and transmission, and the raw data is resume information of job seekers, including job seekers' names, gender, age, work experience, educational experience, and salary requirements.
4. The system of claim 1, wherein the data cleaning and preprocessing module performs denoising, outlier detection and processing on the original data to ensure the quality and accuracy of the data, and the data format conversion and standardization converts the original data into a unified format for subsequent analysis and use, and fills in missing values in the data by missing value filling and feature engineering, and performs feature selection and feature transformation to extract useful features.
5. The system of claim 1, wherein the machine learning algorithms and models in the artificial intelligence module include various supervised learning, unsupervised learning and reinforcement learning algorithms and models for analyzing, mining and predicting data, and the deep learning model uses deep neural networks for feature learning and pattern recognition of data, and natural language processing algorithms for processing text data, including text classification, emotion analysis, machine translation.
6. The system of claim 1, wherein the database management system of the data storage and management module is capable of storing and managing cleaned and processed data to provide data deletion and investigation operations, and the data storage medium is used for long-term data storage, and comprises magnetic disk, optical disk, floppy disk and mobile hard disk.
7. The system for collecting artificial intelligence big data according to claim 1, wherein the statistical analysis tool of the data analysis and visualization module is used for performing statistical analysis on the data, including descriptive statistics, hypothesis testing, regression analysis; and the data mining algorithm is used for finding patterns, rules and correlations from a large amount of data; the data visualization tool visually displays analysis results in the form of charts, images and maps so that a user can better understand the data.
8. The system for collecting artificial intelligence big data according to claim 1, wherein the graphic interface in the user interface module is used for a user to interact with the system in a graphic mode, the user inputs instructions to interact with the system through a command line interface, and the Web interface is used for the user to access the system through a browser, and provides functions of inquiring data, setting parameters and viewing analysis results.
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Cited By (2)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN118505161A (en) * | 2024-07-12 | 2024-08-16 | 杭州浙星科技(集团)有限公司 | Project demand matching system for realizing multi-language algorithm call based on algorithm container |
| CN118505161B (en) * | 2024-07-12 | 2024-10-25 | 杭州浙星科技(集团)有限公司 | Project demand matching system for realizing multi-language algorithm call based on algorithm container |
-
2023
- 2023-08-01 CN CN202310956391.3A patent/CN116911811A/en not_active Withdrawn
Cited By (2)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN118505161A (en) * | 2024-07-12 | 2024-08-16 | 杭州浙星科技(集团)有限公司 | Project demand matching system for realizing multi-language algorithm call based on algorithm container |
| CN118505161B (en) * | 2024-07-12 | 2024-10-25 | 杭州浙星科技(集团)有限公司 | Project demand matching system for realizing multi-language algorithm call based on algorithm container |
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