CN117709917B - Intelligent data processing method and system for recruitment platform - Google Patents
Intelligent data processing method and system for recruitment platform Download PDFInfo
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Abstract
The application provides a data intelligent processing method and system for a recruitment platform. According to the method, a first user terminal in a user terminal cluster sends a first position recommendation request to a recruitment platform, so that the recruitment platform determines a first position information set from a position information database of a cloud server according to first user information and a preset position information screening model, and then determines the first position information set from the first position information set according to a first position feature word sequence and the preset position information recommendation model, so that the first position information set to be recommended is sent to the first user terminal, intelligent processing is conducted on user information input by the user terminal and a position feature word sequence, and accordingly the associated position information set to be recommended to the user terminal is recommended, position information recommendation responding to the position recommendation request is achieved, and the relative position positioning efficiency of a job seeker through the recruitment platform is greatly improved.
Description
Technical Field
The application relates to a data processing technology, in particular to a data intelligent processing method and system for a recruitment platform.
Background
With the rapid development of network technology, the network recruitment platform is widely applied and developed in the global scope, and becomes an important channel for talent recruitment and job hunting.
In the existing network recruitment platform, the job seeker is recommended according to the job searching and the job browsing records of the job seeker, and the recommended job is usually large in number and low in relevance.
Therefore, an intelligent data processing method for a recruitment platform is needed to realize accurate pushing of the recruitment platform to position information of recruiters.
Disclosure of Invention
The application provides a data intelligent processing method and a system for a recruitment platform, which are used for accurately pushing position information based on user information of a job seeker and input position feature words.
In a first aspect, the present application provides a data intelligent processing method for a recruitment platform, applied to a data intelligent processing system, where the data intelligent processing system includes a user terminal cluster and a recruitment platform set up on a cloud server, each user terminal in the user terminal cluster is respectively connected with the recruitment platform in a communication manner, and the method includes:
A first user terminal in the user terminal cluster sends a first position recommendation request to the recruitment platform, wherein the first position recommendation request comprises first user information and a first position feature word sequence;
The recruitment platform determines a first position information set to be selected from a position information database of the cloud server according to the first user information and a preset position information screening model;
The recruitment platform determines a first position information set to be recommended from the first position information set to be recommended according to the first position feature word sequence and a preset position information recommendation model;
and the recruitment platform sends the first position information set to be recommended to the first user terminal.
Optionally, the data intelligent processing system further includes an enterprise terminal cluster, where each enterprise terminal in the enterprise terminal cluster is respectively connected with the recruitment platform in a communication manner; after the recruitment platform determines the first position information set to be recommended from the first position information set to be recommended according to the first position feature word sequence and the preset position information recommendation model, the recruitment platform further includes:
The recruitment platform determines enterprise terminals corresponding to the position information to be recommended in the enterprise terminal cluster in the first position information set to be recommended so as to form a first enterprise terminal cluster to be recommended;
the recruitment platform sends position information confirmation instructions to be recommended to all enterprise terminals in the first enterprise terminal cluster to be recommended, and determines a first position information set to be recommended from the first position information set to be recommended according to position information reply information to be recommended of all enterprise terminals in response to the position information confirmation instructions to be recommended;
and the recruitment platform sends the first recommended position information set to the first user terminal.
Optionally, the determining, according to the to-be-recommended position information reply information of each enterprise terminal in response to the to-be-recommended position information confirmation instruction, a first recommended position information set from the first to-be-recommended position information set includes:
if the first enterprise terminal in the first enterprise terminal cluster to be recommended responds to the job information confirmation instruction to be recommended, and the job information reply information to be recommended sent to the recruitment platform comprises a first characteristic field, the job information to be recommended corresponding to the first enterprise terminal is added to the first recommended job information set, and the first characteristic field is used for representing manual confirmation operation;
If a second enterprise terminal in the first enterprise terminal cluster to be recommended responds to the position information confirmation instruction to be recommended, and the position information reply information to be recommended sent to the recruitment platform comprises a second characteristic field, adding position information to be recommended corresponding to the second enterprise terminal to the first position information set, wherein the second characteristic field is used for representing that manual timeout is not confirmed and the position information to be recommended corresponding to the second enterprise terminal is in an open state;
If the third enterprise terminal in the first enterprise terminal cluster to be recommended responds to the position information confirmation instruction to be recommended, the position information reply information to be recommended sent to the recruitment platform comprises a third characteristic field, position information to be recommended corresponding to the second enterprise terminal is excluded from the first position information set to be recommended, the third characteristic field is used for representing that manual timeout is not confirmed, and the position information to be recommended corresponding to the second enterprise terminal is in a closed state.
Optionally, the first user information includes first resume information of a first user corresponding to the first user terminal; correspondingly, the recruitment platform determines a first to-be-selected position information set from a position information database of the cloud server according to the first user information and a preset position information screening model, and the recruitment platform comprises:
The recruitment platform determines the first position information set from a position information database of the cloud server according to first service field information, first learning information and first working period information in the first resume information, wherein the service field information in each position information to be selected in the first position information set and the first service field information belong to the same service field, the lowest learning requirement information in the position information to be selected is lower than the first learning information, and the lowest working period requirement information in the position information to be selected is lower than the first working period information.
Optionally, before the recruitment platform sends the job information confirmation instruction to be recommended to each enterprise terminal in the first enterprise terminal cluster to be recommended, the recruitment platform further includes:
the recruitment platform acquires first public authority information configured by the first user terminal, determines first public information from the first resume information according to the first public authority information, wherein the first public information is at least part of the first resume information, and the position information to be recommended confirmation instruction comprises the first public information.
Optionally, the recruitment platform determines a first set of job information to be recommended from the first set of job information to be recommended according to the first job feature word sequence and a preset job information recommendation model, including:
The recruitment platform utilizes a preset word embedding model and generates a first representation set corresponding to the first position feature word sequence according to the first position feature word sequence;
The recruitment platform generates a first word segmentation set according to first position information to be selected in the first position information set by using a preset word segmentation tool, and determines a second representation set corresponding to the first word segmentation set by using the preset word embedding model;
The recruitment platform determines a job feature matching degree between the first representation set and the second representation set;
And the recruitment platform adds the position information to be selected, in the first position information set to be recommended, with the feature matching degree larger than a preset feature matching degree threshold value.
Optionally, after the recruitment platform sends the first set of recommended position information to the first user terminal, the recruitment platform further includes:
the first user terminal sends a first position feedback information set to the recruitment platform, wherein position feedback information in the first position feedback information set is feedback information responding to recommended position information in the first recommended position information set;
And if the first relevant feedback proportion determined by the recruitment platform according to the first feedback quantity of the position relevant feedback information and the total number of the feedback information in the first position feedback information set is smaller than a preset relevant feedback proportion threshold value, sending a position recommendation request adjustment instruction to the first user terminal, wherein the position recommendation request adjustment instruction is used for indicating the first user terminal to adjust the first user information and/or the first position feature word sequence, and the position feedback information in the first position feedback information set comprises the position relevant feedback information and the position irrelevant feedback information.
In a second aspect, the present application provides a data intelligent processing system, including: the system comprises a user terminal cluster and a recruitment platform arranged on a cloud server, wherein each user terminal in the user terminal cluster is respectively in communication connection with the recruitment platform;
A first user terminal in the user terminal cluster sends a first position recommendation request to the recruitment platform, wherein the first position recommendation request comprises first user information and a first position feature word sequence;
The recruitment platform determines a first position information set to be selected from a position information database of the cloud server according to the first user information and a preset position information screening model;
The recruitment platform determines a first position information set to be recommended from the first position information set to be recommended according to the first position feature word sequence and a preset position information recommendation model;
and the recruitment platform sends the first position information set to be recommended to the first user terminal.
Optionally, the data intelligent processing system further includes an enterprise terminal cluster, where each enterprise terminal in the enterprise terminal cluster is respectively connected with the recruitment platform in a communication manner; the recruitment platform determines enterprise terminals corresponding to the position information to be recommended in the enterprise terminal cluster in the first position information set to be recommended so as to form a first enterprise terminal cluster to be recommended;
the recruitment platform sends position information confirmation instructions to be recommended to all enterprise terminals in the first enterprise terminal cluster to be recommended, and determines a first position information set to be recommended from the first position information set to be recommended according to position information reply information to be recommended of all enterprise terminals in response to the position information confirmation instructions to be recommended;
and the recruitment platform sends the first recommended position information set to the first user terminal.
Optionally, the determining, according to the to-be-recommended position information reply information of each enterprise terminal in response to the to-be-recommended position information confirmation instruction, a first recommended position information set from the first to-be-recommended position information set includes:
if the first enterprise terminal in the first enterprise terminal cluster to be recommended responds to the job information confirmation instruction to be recommended, and the job information reply information to be recommended sent to the recruitment platform comprises a first characteristic field, the job information to be recommended corresponding to the first enterprise terminal is added to the first recommended job information set, and the first characteristic field is used for representing manual confirmation operation;
If a second enterprise terminal in the first enterprise terminal cluster to be recommended responds to the position information confirmation instruction to be recommended, and the position information reply information to be recommended sent to the recruitment platform comprises a second characteristic field, adding position information to be recommended corresponding to the second enterprise terminal to the first position information set, wherein the second characteristic field is used for representing that manual timeout is not confirmed and the position information to be recommended corresponding to the second enterprise terminal is in an open state;
If the third enterprise terminal in the first enterprise terminal cluster to be recommended responds to the position information confirmation instruction to be recommended, the position information reply information to be recommended sent to the recruitment platform comprises a third characteristic field, position information to be recommended corresponding to the second enterprise terminal is excluded from the first position information set to be recommended, the third characteristic field is used for representing that manual timeout is not confirmed, and the position information to be recommended corresponding to the second enterprise terminal is in a closed state.
Optionally, the first user information includes first resume information of a first user corresponding to the first user terminal;
The recruitment platform determines the first position information set from a position information database of the cloud server according to first service field information, first learning information and first working period information in the first resume information, wherein the service field information in each position information to be selected in the first position information set and the first service field information belong to the same service field, the lowest learning requirement information in the position information to be selected is lower than the first learning information, and the lowest working period requirement information in the position information to be selected is lower than the first working period information.
Optionally, the recruitment platform acquires first public authority information configured by the first user terminal, determines first public information from the first resume information according to the first public authority information, wherein the first public information is at least part of information in the first resume information, and the to-be-recommended position information confirmation instruction includes the first public information.
Optionally, the recruitment platform utilizes a preset word embedding model, and generates a first representation set corresponding to the first position feature word sequence according to the first position feature word sequence;
The recruitment platform generates a first word segmentation set according to first position information to be selected in the first position information set by using a preset word segmentation tool, and determines a second representation set corresponding to the first word segmentation set by using the preset word embedding model;
The recruitment platform determines a job feature matching degree between the first representation set and the second representation set;
And the recruitment platform adds the position information to be selected, in the first position information set to be recommended, with the feature matching degree larger than a preset feature matching degree threshold value.
Optionally, the first user terminal sends a first position feedback information set to the recruitment platform, where position feedback information in the first position feedback information set is feedback information responding to recommended position information in the first recommended position information set;
And if the first relevant feedback proportion determined by the recruitment platform according to the first feedback quantity of the position relevant feedback information and the total number of the feedback information in the first position feedback information set is smaller than a preset relevant feedback proportion threshold value, sending a position recommendation request adjustment instruction to the first user terminal, wherein the position recommendation request adjustment instruction is used for indicating the first user terminal to adjust the first user information and/or the first position feature word sequence, and the position feedback information in the first position feedback information set comprises the position relevant feedback information and the position irrelevant feedback information.
In a third aspect, the present application provides an electronic device comprising:
A processor; and
A memory for storing executable instructions of the processor;
Wherein the processor is configured to perform any one of the possible methods described in the first aspect via execution of the executable instructions.
In a fourth aspect, the present application provides a computer readable storage medium having stored therein computer executable instructions which when executed by a processor are adapted to carry out any one of the possible methods described in the first aspect.
According to the data intelligent processing method and system for the recruitment platform, the first user terminal in the user terminal cluster is used for sending the first position recommendation request to the recruitment platform, so that the recruitment platform determines the first position information set from the position information database of the cloud server according to the first user information and the preset position information screening model, then determines the first position information set from the first position information set according to the first position feature word sequence and the preset position information recommendation model, and sends the first position information set to the first user terminal, and therefore intelligent processing is conducted on the user information input by the user terminal and the position feature word sequence, the position information set to be recommended which is related to the first user information and the first position feature word sequence is recommended to the user terminal, position information recommendation which is in response to the position recommendation request is achieved, and the relevant position positioning efficiency of a worker through the recruitment platform is greatly improved.
Drawings
The accompanying drawings, which are incorporated in and constitute a part of this specification, illustrate embodiments consistent with the application and together with the description, serve to explain the principles of the application.
Fig. 1 is a flow chart of a method for intelligent processing of data for a recruitment platform according to an example embodiment of the present application;
Fig. 2 is a flow chart of a method for intelligent processing of data for a recruitment platform according to another example embodiment of the application;
FIG. 3 is a schematic diagram of a data intelligent processing system according to an example embodiment of the present application;
fig. 4 is a schematic structural view of an electronic device according to an exemplary embodiment of the present application.
Specific embodiments of the present application have been shown by way of the above drawings and will be described in more detail below. The drawings and the written description are not intended to limit the scope of the inventive concepts in any way, but rather to illustrate the inventive concepts to those skilled in the art by reference to the specific embodiments.
Detailed Description
Reference will now be made in detail to exemplary embodiments, examples of which are illustrated in the accompanying drawings. When the following description refers to the accompanying drawings, the same numbers in different drawings refer to the same or similar elements, unless otherwise indicated. The implementations described in the following exemplary examples do not represent all implementations consistent with the application. Rather, they are merely examples of apparatus and methods consistent with aspects of the application as detailed in the accompanying claims.
Fig. 1 is a flow chart illustrating a method for intelligent processing of data for a recruitment platform according to an example embodiment of the present application. As shown in fig. 1, the method provided in this embodiment includes:
S101, a first user terminal in a user terminal cluster sends a first job recommendation request to a recruitment platform.
The data intelligent processing method for the recruitment platform provided by the embodiment can be applied to a data intelligent processing system. The data intelligent processing system can comprise a user terminal cluster and a recruitment platform arranged on the cloud server, wherein each user terminal in the user terminal cluster is respectively in communication connection with the recruitment platform. The recruitment platform may be a cloud server related to a recruitment website or a recruitment application, and the user terminal may be a terminal device of a job seeker that logs in to the recruitment website or loads the recruitment application.
In this step, it may be that a first user terminal in the user terminal cluster sends a first job recommendation request to the recruitment platform, where the first job recommendation request includes first user information and a first job feature word sequence. It should be noted that the first job feature word sequence may include a plurality of job feature words, for example, an e-commerce application, front-end development, project manager, and the like.
And S102, determining a first position information set to be selected from a position information database of the cloud server by the recruitment platform according to the first user information and a preset position information screening model.
Optionally, the recruitment platform may determine the first set of position information to be selected from a position information database of the cloud server according to the first user information and the preset position information screening model. Optionally, the first user information includes first resume information of a first user corresponding to the first user terminal.
Specifically, the recruitment platform may determine a first set of job information from the job information database of the cloud server according to the first service domain information, the first learning information, and the first working year information in the first resume information, where the service domain information and the first service domain information in each job information to be selected in the first set of job information belong to the same service domain, for example, belong to the same application development domain of the electronic commerce. In addition, the minimum learning requirement information in the position information to be selected is lower than the first learning requirement information, and the minimum working life requirement information in the position information to be selected is lower than the first working life information.
And S103, determining a first position information set to be recommended from the first position information set by the recruitment platform according to the first position feature word sequence and the preset position information recommendation model.
In this step, the recruitment platform may determine a first set of job information to be recommended from the first set of job information to be selected according to the first job feature word sequence and the preset job information recommendation model.
Specifically, the recruitment platform may utilize a preset word embedding model and generate a first representation set corresponding to the first job feature word sequence according to the first job feature word sequence. The word embedding model described above is a technique that maps words into a continuous vector space that captures semantic relationships between words and context information by representing each word as a dense real vector. Specifically, the preset Word embedding model may be a Word2Vec Word embedding model, which may learn a distributed representation of words by training a shallow neural network; the method can also be a GloVe word embedding model, which is a word embedding model based on global vocabulary statistics, and can learn the co-occurrence probability among words by utilizing global statistics information and convert the co-occurrence probability into vector representation; furthermore, a FastText word embedding model is possible, in which the entire word can be represented by splitting the word into character-level representations and weighting them to average.
And then, the recruitment platform generates a first word segmentation set according to the first position information to be selected in the first position information set by using a preset word segmentation tool, and determines a second representation set corresponding to the first word segmentation set by using a preset word embedding model. The preset word segmentation tool can segment a continuous text sequence into meaningful words or marks. In particular, a rule-based word segmentation algorithm may be used, such that the rule-based word segmentation algorithm uses manually defined rules to segment words. These rules may be designed based on language characteristics, morphological changes and context of words, etc. For example, chinese word segmentation may use rules such as regular expressions, dictionary matches, and longest matches. For another example, a statistical word segmentation algorithm may also be used to segment words by counting the frequency of occurrence of words in text and contextual information. Among them, hidden markov models and conditional random fields are commonly used statistical models for word segmentation. In addition, the method can be a word segmentation algorithm based on machine learning, training data can be used for learning a word segmentation model, the method can comprise a maximum entropy model, a support vector machine, a neural network and the like, and the word segmentation effect can be improved according to different feature selections and model designs. In addition, a word segmentation algorithm based on word embedding is also adopted, words can be mapped into continuous vector space, and segmentation is carried out according to the similarity between vectors.
The recruitment platform then determines a job feature match between the first set of representations and the second set of representations. And the recruitment platform adds the position information to be selected, in the first position information set to be recommended, with the feature matching degree larger than the preset feature matching degree threshold value.
And S104, the recruitment platform sends a first position information set to be recommended to the first user terminal.
The recruitment platform sends the first position information set to be recommended to the first user terminal after determining the first position information set to be recommended from the first position information set according to the first position feature word sequence and the preset position information recommendation model.
In this embodiment, a first user terminal in the user terminal cluster sends a first position recommendation request to a recruitment platform, so that the recruitment platform determines a first position information set from a position information database of a cloud server according to first user information and a preset position information screening model, then determines the first position information set from the first position information set according to a first position feature word sequence and the preset position information recommendation model, and sends the first position information set to the first user terminal, and intelligent processing is performed on user information input by the user terminal and the position feature word sequence, so that the position information set to be recommended which is associated with the first user information and the first position feature word sequence is recommended to the user terminal, position information recommendation which responds to the position recommendation request is realized, and the relevant position positioning efficiency of a recruiter through the recruitment platform is greatly improved.
Fig. 2 is a flow chart illustrating a method of intelligent processing of data for a recruitment platform according to another example embodiment of the application. As shown in fig. 2, the data intelligent processing method for a recruitment platform provided in this embodiment includes:
S201, a first user terminal in a user terminal cluster sends a first job recommendation request to a recruitment platform.
In this step, it may be that a first user terminal in the user terminal cluster sends a first job recommendation request to the recruitment platform, where the first job recommendation request includes first user information and a first job feature word sequence. It should be noted that the first job feature word sequence may include a plurality of job feature words, for example, an e-commerce application, front-end development, project manager, and the like.
S202, the recruitment platform determines a first position information set to be selected from a position information database of the cloud server according to the first user information and a preset position information screening model.
Optionally, the recruitment platform may determine the first set of position information to be selected from a position information database of the cloud server according to the first user information and the preset position information screening model. Optionally, the first user information includes first resume information of a first user corresponding to the first user terminal.
Specifically, the recruitment platform may determine a first set of job information from the job information database of the cloud server according to the first service domain information, the first learning information, and the first working year information in the first resume information, where the service domain information and the first service domain information in each job information to be selected in the first set of job information belong to the same service domain, for example, belong to the same application development domain of the electronic commerce. In addition, the minimum learning requirement information in the position information to be selected is lower than the first learning requirement information, and the minimum working life requirement information in the position information to be selected is lower than the first working life information.
And S203, determining a first position information set to be recommended from the first position information set by the recruitment platform according to the first position feature word sequence and the preset position information recommendation model.
In this step, the recruitment platform may determine a first set of job information to be recommended from the first set of job information to be selected according to the first job feature word sequence and the preset job information recommendation model.
Specifically, the recruitment platform utilizes a preset word embedding model and based on the first job feature word sequenceGenerating a first job feature word sequence/>Corresponding first representation set/>Wherein/>For the first job feature word sequence/>/>Personal characteristic words,/>For the first job feature word sequence/>/>Word embedding vector corresponding to each job feature word,/>For the first job feature word sequence/>The number of job feature words in (a). The recruitment platform utilizes a preset word segmentation tool and generates a first word segmentation set according to first position information in the first position information set to be selectedAnd determining a first word segmentation set/>, by using the preset word embedding modelCorresponding second set of representations/>Wherein/>For the first word segment set/>/>Word segmentation,/>For the first word segment set/>/>Word embedding vector corresponding to each word segment,/>For the first word segment set/>The number of words in the word segmentation. The recruitment platform calculates the first set of representations/>, according to equation 1And the second representation set/>Job feature matching degree/>The formula 1 is:
；
The recruitment platform matches the feature in the first set of position information to be selected And adding the position information to be selected, which is larger than a preset feature matching degree threshold value, to the first position information set to be recommended.
S204, the recruitment platform determines enterprise terminals corresponding to the position information to be recommended in the enterprise terminal cluster in the first position information set to be recommended so as to form the first enterprise terminal cluster to be recommended.
Optionally, the data intelligent processing system may further include an enterprise terminal cluster, where each enterprise terminal in the enterprise terminal cluster is respectively connected to the recruitment platform in a communication manner.
In addition, the recruitment platform can also acquire first public authority information configured by the first user terminal, determine first public information from the first resume information according to the first public authority information, wherein the first public information is at least part of information in the first resume information, and the position information confirmation instruction to be recommended comprises the first public information.
And S205, the recruitment platform sends position information confirmation instructions to be recommended to all enterprise terminals in the first enterprise terminal cluster to be recommended, and determines a first position information set from the first position information set to be recommended according to position information reply information to be recommended of all enterprise terminals in response to the position information confirmation instructions to be recommended.
Specifically, if the first enterprise terminal in the first enterprise terminal cluster to be recommended responds to the job information confirmation instruction to be recommended and the job information reply information to be recommended sent to the recruitment platform includes a first feature field, the job information to be recommended corresponding to the first enterprise terminal is added to the first recommended job information set, and the first feature field is used for representing manual confirmation operation.
If the second enterprise terminal in the first enterprise terminal cluster to be recommended responds to the position information confirmation instruction to be recommended, the position information reply information to be recommended sent to the recruitment platform comprises a second characteristic field, the position information to be recommended corresponding to the second enterprise terminal is added to the first position information set, the second characteristic field is used for representing that the manual timeout is not confirmed, and the position information to be recommended corresponding to the second enterprise terminal is in an open state.
If a third enterprise terminal in the first enterprise terminal cluster to be recommended responds to the position information confirmation instruction to be recommended, the position information reply information to be recommended sent to the recruitment platform comprises a third characteristic field, the position information to be recommended corresponding to the second enterprise terminal is excluded from the first position information set, the third characteristic field is used for representing that the manual timeout is not confirmed and the position information to be recommended corresponding to the second enterprise terminal is in a closed state.
And S206, the recruitment platform sends a first position information set to be recommended to the first user terminal.
The recruitment platform sends the first position information set to be recommended to the first user terminal after determining the first position information set to be recommended from the first position information set according to the first position feature word sequence and the preset position information recommendation model.
S207, the first user terminal sends a first position feedback information set to the recruitment platform.
Optionally, the first user terminal sends a first position feedback information set to the recruitment platform, wherein position feedback information in the first position feedback information set is feedback information responding to recommended position information in the first recommended position information set. The job feedback information may be indication information for confirming the recommendation job, or resume delivery information for the recommendation job.
And S208, the recruitment platform sends a job recommendation request adjustment instruction to the first user terminal.
Optionally, if the first relevant feedback proportion determined by the recruitment platform according to the first feedback quantity of the position relevant feedback information and the total number of the feedback information in the first position feedback information set is smaller than the preset relevant feedback proportion threshold, sending a position recommendation request adjustment instruction to the first user terminal, where the position recommendation request adjustment instruction is used to instruct the first user terminal to adjust the first user information and/or the first position feature word sequence, and the position feedback information in the first position feedback information set includes position relevant feedback information and position irrelevant feedback information. In this step, whether the user information and/or the job feature word sequence need to be adjusted can be determined according to the relation between the first relevant feedback proportion and the preset relevant feedback proportion threshold, so that the recruitment platform can recommend the effective and relevant job information more accurately, and the job hunting efficiency of the job seeker is further improved.
Further, if the recruitment platform can further determine that the first number of the position information to be selected in the first position information set to be selected is smaller than a preset first number threshold, and a first ratio between the second number and the first number is smaller than the preset first ratio threshold, a first user information adjustment instruction is sent to the first user terminal, where the first user information adjustment instruction is used to instruct a first user of the first user terminal to adjust the first user information and the first position feature word sequence, the first number is the number of the position information to be recommended in the first position information set to be recommended, and the second number is the number of the position information to be selected in the first position information set to be recommended. Therefore, the adjustment prompt of the user information can be realized by determining that the first quantity of the position information to be selected in the first position information set is smaller than the preset first quantity threshold value, and when the first ratio value between the second quantity and the first quantity is smaller than the preset first ratio threshold value, the first user information adjustment instruction is sent to the first user terminal, so that the recruitment platform can recommend the effective and relevant position information more accurately.
FIG. 3 is a schematic diagram of a data intelligent processing system according to an example embodiment of the present application. As shown in fig. 3, the data intelligent processing system 300 provided in this embodiment includes: the cloud server recruitment system comprises a user terminal cluster 310 and a recruitment platform 320 arranged on the cloud server, wherein each user terminal in the user terminal cluster 310 is respectively in communication connection with the recruitment platform 320;
A first user terminal in the user terminal cluster 310 sends a first job recommendation request to the recruitment platform 320, where the first job recommendation request includes first user information and a first job feature word sequence;
The recruitment platform 320 determines a first set of position information to be selected from a position information database of the cloud server according to the first user information and a preset position information screening model;
the recruitment platform 320 determines a first set of job information to be recommended from the first set of job information to be selected according to the first job feature word sequence and a preset job information recommendation model;
the recruitment platform 320 sends the first set of job information to be recommended to the first user terminal.
Optionally, the data intelligent processing system further includes an enterprise terminal cluster 330, where each enterprise terminal in the enterprise terminal cluster 330 is respectively connected with the recruitment platform 320 in a communication manner; the recruitment platform 320 determines an enterprise terminal corresponding to each piece of job information to be recommended in the enterprise terminal cluster 330 in the first set of job information to be recommended, so as to form a first enterprise terminal cluster 330 to be recommended;
the recruitment platform 320 sends a job information confirmation instruction to be recommended to each enterprise terminal in the first enterprise terminal cluster to be recommended 330, and determines a first set of job information to be recommended from the first set of job information to be recommended according to job information reply information to be recommended of each enterprise terminal in response to the job information confirmation instruction to be recommended;
the recruitment platform 320 sends the first set of recommended position information to the first user terminal.
Optionally, the determining, according to the to-be-recommended position information reply information of each enterprise terminal in response to the to-be-recommended position information confirmation instruction, a first recommended position information set from the first to-be-recommended position information set includes:
If the first enterprise terminal in the first enterprise terminal cluster to be recommended 330 responds to the job information confirmation instruction to be recommended and the job information reply information to be recommended sent to the recruitment platform 320 includes a first feature field, adding the job information to be recommended corresponding to the first enterprise terminal to the first recommended job information set, where the first feature field is used for characterizing a manual confirmation operation;
If the second enterprise terminal in the first enterprise terminal cluster to be recommended 330 responds to the job information confirmation instruction to be recommended, and the job information reply information to be recommended sent to the recruitment platform 320 includes a second feature field, the job information to be recommended corresponding to the second enterprise terminal is added to the first recommended job information set, where the second feature field is used for representing that the manual timeout is not confirmed and the job information to be recommended corresponding to the second enterprise terminal is in an open state;
If the third enterprise terminal in the first enterprise terminal to be recommended cluster 330 responds to the job information confirmation instruction to be recommended, and the job information reply information to be recommended sent to the recruitment platform 320 includes a third feature field, the job information to be recommended corresponding to the second enterprise terminal is excluded from the first recommended job information set, where the third feature field is used for characterizing that the manual timeout is not confirmed and the job information to be recommended corresponding to the second enterprise terminal is in a closed state.
Optionally, the first user information includes first resume information of a first user corresponding to the first user terminal;
The recruitment platform 320 determines the first set of job information from the job information database of the cloud server according to the first service area information, the first learning information and the first working year information in the first resume information, wherein the service area information in each piece of job information in the first set of job information and the first service area information belong to the same service area, the lowest learning requirement information in the piece of job information to be selected is lower than the first learning information, and the lowest working year requirement information in the piece of job information to be selected is lower than the first working year information.
Optionally, the recruitment platform 320 acquires first public authority information configured by the first user terminal, determines first public information from the first resume information according to the first public authority information, where the first public information is at least part of information in the first resume information, and the to-be-recommended position information confirmation instruction includes the first public information.
Optionally, the recruitment platform 320 utilizes a preset word embedding model, and generates a first representation set corresponding to the first job feature word sequence according to the first job feature word sequence;
The recruitment platform 320 generates a first word segmentation set according to the first position information to be selected in the first position information set by using a preset word segmentation tool, and determines a second representation set corresponding to the first word segmentation set by using the preset word embedding model;
The recruitment platform 320 determines a job feature match between the first set of representations and the second set of representations;
The recruitment platform 320 adds the job information to be selected in the first set of job information to be recommended, wherein the feature matching degree is greater than a preset feature matching degree threshold.
Optionally, the first user terminal sends a first position feedback information set to the recruitment platform 320, where position feedback information in the first position feedback information set is feedback information in response to recommended position information in the first recommended position information set;
If the first relevant feedback proportion determined by the recruitment platform 320 according to the first feedback quantity and the total number of the job relevant feedback information in the first job feedback information set is smaller than a preset relevant feedback proportion threshold, a job recommendation request adjustment instruction is sent to the first user terminal, and the job recommendation request adjustment instruction is used for indicating the first user terminal to adjust the first user information and/or the first job feature word sequence, wherein the job feedback information in the first job feedback information set includes the job relevant feedback information and the job irrelevant feedback information.
Fig. 4 is a schematic structural view of an electronic device according to an exemplary embodiment of the present application. As shown in fig. 4, an electronic device 400 provided in this embodiment includes: a processor 401 and a memory 402; wherein:
A memory 402 for storing a computer program, which memory may also be a flash memory.
A processor 401 for executing the execution instructions stored in the memory to implement the steps in the above method. Reference may be made in particular to the description of the embodiments of the method described above.
Alternatively, the memory 402 may be separate or integrated with the processor 401.
When the memory 402 is a device separate from the processor 401, the electronic apparatus 400 may further include:
a bus 403 for connecting the memory 402 and the processor 401.
The present embodiment also provides a readable storage medium having a computer program stored therein, which when executed by at least one processor of an electronic device, performs the methods provided by the various embodiments described above.
The present embodiment also provides a program product comprising a computer program stored in a readable storage medium. The computer program may be read from a readable storage medium by at least one processor of an electronic device, and executed by the at least one processor, causes the electronic device to implement the methods provided by the various embodiments described above.
Other embodiments of the application will be apparent to those skilled in the art from consideration of the specification and practice of the application disclosed herein. This application is intended to cover any variations, uses, or adaptations of the application following, in general, the principles of the application and including such departures from the present disclosure as come within known or customary practice within the art to which the application pertains. It is intended that the specification and examples be considered as exemplary only, with a true scope and spirit of the application being indicated by the following claims.
It is to be understood that the application is not limited to the precise arrangements and instrumentalities shown in the drawings, which have been described above, and that various modifications and changes may be effected without departing from the scope thereof. The scope of the application is limited only by the appended claims.
Claims (6)
1. The data intelligent processing method for the recruitment platform is characterized by being applied to a data intelligent processing system, wherein the data intelligent processing system comprises a user terminal cluster and the recruitment platform arranged on a cloud server, and each user terminal in the user terminal cluster is respectively in communication connection with the recruitment platform, and the method comprises the following steps:
A first user terminal in the user terminal cluster sends a first position recommendation request to the recruitment platform, wherein the first position recommendation request comprises first user information and a first position feature word sequence, the first user information comprises first resume information of a first user corresponding to the first user terminal, the first position feature word sequence comprises a plurality of position feature words;
The recruitment platform determines a first position information set to be selected from a position information database of the cloud server according to the first user information and a preset position information screening model;
The recruitment platform determines a first position information set to be recommended from the first position information set to be recommended according to the first position feature word sequence and a preset position information recommendation model;
the recruitment platform sends the first position information set to be recommended to the first user terminal;
The recruitment platform determines a first position information set to be recommended from the first position information set to be recommended according to the first position feature word sequence and a preset position information recommendation model, and the recruitment platform comprises:
the recruitment platform utilizes a preset word embedding model and performs feature word sequence according to the first position Generating a first job feature word sequence/>Corresponding first representation set/>Wherein, the method comprises the steps of, wherein,For the first job feature word sequence/>/>Personal characteristic words,/>For the first job feature word sequence/>/>Word embedding vector corresponding to each job feature word,/>For the first job feature word sequence/>The number of job feature words in the list;
The recruitment platform utilizes a preset word segmentation tool and generates a first word segmentation set according to first position information to be selected in the first position information set to be selected And determining a first word segmentation set/>, by using the preset word embedding modelCorresponding second set of representations/>Wherein/>For the first word segment set/>/>Word segmentation,/>For the first word segment set/>/>Word embedding vector corresponding to each word segment,/>For the first word segment set/>The number of word segments in the database;
the recruitment platform calculates the first set of representations according to equation 1 And the second representation set/>Job feature matching degree/>The formula 1 is:
；
The recruitment platform matches the feature in the first set of position information to be selected Adding position information to be selected, which is larger than a preset feature matching degree threshold value, to the first position information set to be recommended;
the data intelligent processing system further comprises an enterprise terminal cluster, and each enterprise terminal in the enterprise terminal cluster is respectively in communication connection with the recruitment platform; after the recruitment platform determines the first position information set to be recommended from the first position information set to be recommended according to the first position feature word sequence and the preset position information recommendation model, the recruitment platform further includes:
The recruitment platform determines enterprise terminals corresponding to the position information to be recommended in the enterprise terminal cluster in the first position information set to be recommended so as to form a first enterprise terminal cluster to be recommended;
the recruitment platform sends position information confirmation instructions to be recommended to all enterprise terminals in the first enterprise terminal cluster to be recommended, and determines a first position information set to be recommended from the first position information set to be recommended according to position information reply information to be recommended of all enterprise terminals in response to the position information confirmation instructions to be recommended;
The recruitment platform sends the first recommended position information set to the first user terminal;
The determining a first recommended position information set according to the position information reply information to be recommended of each enterprise terminal in response to the position information confirmation instruction to be recommended from the first position information set to be recommended includes:
if the first enterprise terminal in the first enterprise terminal cluster to be recommended responds to the job information confirmation instruction to be recommended, and the job information reply information to be recommended sent to the recruitment platform comprises a first characteristic field, the job information to be recommended corresponding to the first enterprise terminal is added to the first recommended job information set, and the first characteristic field is used for representing manual confirmation operation;
If a second enterprise terminal in the first enterprise terminal cluster to be recommended responds to the position information confirmation instruction to be recommended, and the position information reply information to be recommended sent to the recruitment platform comprises a second characteristic field, adding position information to be recommended corresponding to the second enterprise terminal to the first position information set, wherein the second characteristic field is used for representing that manual timeout is not confirmed and the position information to be recommended corresponding to the second enterprise terminal is in an open state;
If a third enterprise terminal in the first enterprise terminal cluster to be recommended responds to the position information confirmation instruction to be recommended, and the position information reply information to be recommended sent to the recruitment platform comprises a third characteristic field, the position information to be recommended corresponding to the second enterprise terminal is excluded from the first position information set, the third characteristic field is used for representing that manual timeout is not confirmed and the position information to be recommended corresponding to the second enterprise terminal is in a closed state;
after the recruitment platform sends the first set of recommended position information to the first user terminal, the recruitment platform further comprises:
the first user terminal sends a first position feedback information set to the recruitment platform, wherein position feedback information in the first position feedback information set is feedback information responding to recommended position information in the first recommended position information set;
If a first relevant feedback proportion determined by the recruitment platform according to a first feedback quantity of position relevant feedback information and the total number of feedback information in the first position feedback information set is smaller than a preset relevant feedback proportion threshold value, sending a position recommendation request adjustment instruction to the first user terminal, wherein the position recommendation request adjustment instruction is used for indicating the first user terminal to adjust the first user information and/or the first position feature word sequence, and position feedback information in the first position feedback information set comprises position relevant feedback information and position irrelevant feedback information;
and if the recruitment platform determines that the first quantity of the position information to be selected in the first position information set to be selected is smaller than a preset first quantity threshold value, and a first ratio between the second quantity and the first quantity is smaller than the preset first ratio threshold value, a first user information adjustment instruction is sent to the first user terminal, wherein the first user information adjustment instruction is used for indicating a first user of the first user terminal to adjust the first user information and the first position feature word sequence, the first quantity is the quantity of the position information to be recommended in the first position information set to be recommended, and the second quantity is the quantity of the position information to be selected in the first position information set to be recommended.
2. The intelligent data processing method for a recruitment platform according to claim 1, wherein the first user information comprises first resume information of a first user corresponding to the first user terminal; correspondingly, the recruitment platform determines a first to-be-selected position information set from a position information database of the cloud server according to the first user information and a preset position information screening model, and the recruitment platform comprises:
The recruitment platform determines the first position information set from a position information database of the cloud server according to first service field information, first learning information and first working period information in the first resume information, wherein the service field information in each position information to be selected in the first position information set and the first service field information belong to the same service field, the lowest learning requirement information in the position information to be selected is lower than the first learning information, and the lowest working period requirement information in the position information to be selected is lower than the first working period information.
3. The method for intelligently processing data for a recruitment platform according to claim 2, further comprising, before the recruitment platform sends the job information confirmation instruction to be recommended to each enterprise terminal in the first cluster of enterprise terminals to be recommended:
the recruitment platform acquires first public authority information configured by the first user terminal, determines first public information from the first resume information according to the first public authority information, wherein the first public information is at least part of the first resume information, and the position information to be recommended confirmation instruction comprises the first public information.
4. An intelligent data processing system, comprising: the system comprises a user terminal cluster and a recruitment platform arranged on a cloud server, wherein each user terminal in the user terminal cluster is respectively in communication connection with the recruitment platform;
A first user terminal in the user terminal cluster sends a first position recommendation request to the recruitment platform, wherein the first position recommendation request comprises first user information and a first position feature word sequence, the first user information comprises first resume information of a first user corresponding to the first user terminal, the first position feature word sequence comprises a plurality of position feature words;
the recruitment platform utilizes a preset word embedding model and performs word sequence according to the first position feature Generating a first job feature word sequence/>Corresponding first representation set/>Wherein, the method comprises the steps of, wherein,For the first job feature word sequence/>/>Personal characteristic words,/>For the first job feature word sequence/>/>Word embedding vector corresponding to each job feature word,/>For the first job feature word sequence/>The number of job feature words in the list;
The recruitment platform utilizes a preset word segmentation tool and generates a first word segmentation set according to first position information to be selected in the first position information set to be selected And determining a first word segmentation set/>, by using the preset word embedding modelCorresponding second set of representations/>Wherein/>For the first word segment set/>/>Word segmentation,/>For the first word segment set/>/>Word embedding vector corresponding to each word segment,/>For the first word segment set/>The number of word segments in the database;
the recruitment platform calculates the first set of representations according to equation 1 And the second representation set/>Job feature matching degree/>The formula 1 is:
；
The recruitment platform matches the feature in the first set of position information to be selected Adding position information to be selected, which is larger than a preset feature matching degree threshold value, to the first position information set to be recommended;
The recruitment platform determines a first position information set to be recommended from the first position information set to be recommended according to the first position feature word sequence and a preset position information recommendation model;
the recruitment platform sends the first position information set to be recommended to the first user terminal;
the first user terminal sends a first position feedback information set to the recruitment platform, wherein position feedback information in the first position feedback information set is feedback information responding to recommended position information in the first recommended position information set;
If a first relevant feedback proportion determined by the recruitment platform according to a first feedback quantity of position relevant feedback information and the total number of feedback information in the first position feedback information set is smaller than a preset relevant feedback proportion threshold value, sending a position recommendation request adjustment instruction to the first user terminal, wherein the position recommendation request adjustment instruction is used for indicating the first user terminal to adjust the first user information and/or the first position feature word sequence, and position feedback information in the first position feedback information set comprises position relevant feedback information and position irrelevant feedback information;
and if the recruitment platform determines that the first quantity of the position information to be selected in the first position information set to be selected is smaller than a preset first quantity threshold value, and a first ratio between the second quantity and the first quantity is smaller than the preset first ratio threshold value, a first user information adjustment instruction is sent to the first user terminal, wherein the first user information adjustment instruction is used for indicating a first user of the first user terminal to adjust the first user information and the first position feature word sequence, the first quantity is the quantity of the position information to be recommended in the first position information set to be recommended, and the second quantity is the quantity of the position information to be selected in the first position information set to be recommended.
5. An electronic device, comprising:
A processor; and
A memory for storing executable instructions of the processor;
wherein the processor is configured to perform the method of any one of claims 1 to 3 via execution of the executable instructions.
6. A computer readable storage medium having stored therein computer executable instructions which when executed by a processor are adapted to carry out the method of any one of claims 1 to 3.
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Citations (11)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN107844595A (en) * | 2017-11-21 | 2018-03-27 | 安徽网才信息技术股份有限公司 | A kind of job hunting website position intelligent recommendation method |
| CN108416030A (en) * | 2018-03-09 | 2018-08-17 | 黄冈市可以啊网络科技有限公司 | A kind of position recommends method, apparatus and computer readable storage medium |
| CN109558429A (en) * | 2018-11-16 | 2019-04-02 | 广东百城人才网络股份有限公司 | The two-way recommendation method and system of talent service based on internet big data |
| CN109740046A (en) * | 2018-11-22 | 2019-05-10 | 北京网聘咨询有限公司 | Aerial double choosings based on internet recruitment can platform |
| CN111429082A (en) * | 2020-02-18 | 2020-07-17 | 北京网聘咨询有限公司 | Bidirectional matching similarity calculation method for job positions and resumes of recruitment website |
| CN111708929A (en) * | 2020-06-17 | 2020-09-25 | 北京字节跳动网络技术有限公司 | Information searching method and device, electronic equipment and storage medium |
| CN114090878A (en) * | 2021-11-04 | 2022-02-25 | 北京淘友天下科技发展有限公司 | Position recommendation method, position recommendation device, electronic equipment, readable medium and program product |
| CN114090877A (en) * | 2021-11-03 | 2022-02-25 | 北京淘友天下科技发展有限公司 | Position information recommendation method and device, electronic equipment and storage medium |
| CN114491238A (en) * | 2021-12-31 | 2022-05-13 | 北京五八信息技术有限公司 | Recommendation method and device for position information, electronic equipment and storage medium |
| CN114881609A (en) * | 2022-05-26 | 2022-08-09 | 上海优望企业管理咨询有限公司 | Job matching recommendation system based on human resources |
| CN115564393A (en) * | 2022-10-24 | 2023-01-03 | 深圳今日人才信息科技有限公司 | Recruitment requirement similarity-based job recommendation method |
-
2024
- 2024-02-05 CN CN202410164206.1A patent/CN117709917B/en active Active
Patent Citations (11)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN107844595A (en) * | 2017-11-21 | 2018-03-27 | 安徽网才信息技术股份有限公司 | A kind of job hunting website position intelligent recommendation method |
| CN108416030A (en) * | 2018-03-09 | 2018-08-17 | 黄冈市可以啊网络科技有限公司 | A kind of position recommends method, apparatus and computer readable storage medium |
| CN109558429A (en) * | 2018-11-16 | 2019-04-02 | 广东百城人才网络股份有限公司 | The two-way recommendation method and system of talent service based on internet big data |
| CN109740046A (en) * | 2018-11-22 | 2019-05-10 | 北京网聘咨询有限公司 | Aerial double choosings based on internet recruitment can platform |
| CN111429082A (en) * | 2020-02-18 | 2020-07-17 | 北京网聘咨询有限公司 | Bidirectional matching similarity calculation method for job positions and resumes of recruitment website |
| CN111708929A (en) * | 2020-06-17 | 2020-09-25 | 北京字节跳动网络技术有限公司 | Information searching method and device, electronic equipment and storage medium |
| CN114090877A (en) * | 2021-11-03 | 2022-02-25 | 北京淘友天下科技发展有限公司 | Position information recommendation method and device, electronic equipment and storage medium |
| CN114090878A (en) * | 2021-11-04 | 2022-02-25 | 北京淘友天下科技发展有限公司 | Position recommendation method, position recommendation device, electronic equipment, readable medium and program product |
| CN114491238A (en) * | 2021-12-31 | 2022-05-13 | 北京五八信息技术有限公司 | Recommendation method and device for position information, electronic equipment and storage medium |
| CN114881609A (en) * | 2022-05-26 | 2022-08-09 | 上海优望企业管理咨询有限公司 | Job matching recommendation system based on human resources |
| CN115564393A (en) * | 2022-10-24 | 2023-01-03 | 深圳今日人才信息科技有限公司 | Recruitment requirement similarity-based job recommendation method |
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