CN115170094A - Big data artificial intelligence recruitment system and method - Google Patents
Big data artificial intelligence recruitment system and method Download PDFInfo
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- CN115170094A CN115170094A CN202211086517.8A CN202211086517A CN115170094A CN 115170094 A CN115170094 A CN 115170094A CN 202211086517 A CN202211086517 A CN 202211086517A CN 115170094 A CN115170094 A CN 115170094A
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- G06Q—INFORMATION AND COMMUNICATION TECHNOLOGY [ICT] SPECIALLY ADAPTED FOR ADMINISTRATIVE, COMMERCIAL, FINANCIAL, MANAGERIAL OR SUPERVISORY PURPOSES; SYSTEMS OR METHODS SPECIALLY ADAPTED FOR ADMINISTRATIVE, COMMERCIAL, FINANCIAL, MANAGERIAL OR SUPERVISORY PURPOSES, NOT OTHERWISE PROVIDED FOR
- G06Q10/00—Administration; Management
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- G06Q10/105—Human resources
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- G06F16/30—Information retrieval; Database structures therefor; File system structures therefor of unstructured textual data
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- G06F16/335—Filtering based on additional data, e.g. user or group profiles
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Abstract
The invention is suitable for the technical field of recruitment and job hunting, and provides a big data artificial intelligence recruitment system and a method thereof, which comprises the following steps: calling chat information of an enterprise terminal, and analyzing the chat information of the enterprise terminal to obtain enterprise problems and enterprise keywords; calling chat information of the job seeker, and analyzing the chat information of the job seeker to obtain a job seeker question and job seeker keywords; receiving recruitment information sent by an enterprise terminal, and screening personal resumes for one time; secondary screening is carried out on the job seeker keywords of the rest job seekers according to the enterprise screening conditions, and the personal resume, the job seeker questions and the job seeker keywords of the job seekers after the secondary screening are pushed to an enterprise terminal; receiving job hunting information of job seekers, and screening the recruitment information of the enterprise for one time; and carrying out secondary screening on enterprise keywords of the rest enterprises according to the job-seeking screening conditions. Therefore, the enterprise end can obtain more accurate job seekers and more comprehensive job seeker information, and the recruitment process is accelerated.
Description
Technical Field
The invention relates to the technical field of recruitment and job hunting, in particular to a big data artificial intelligence recruitment system and method.
Background
Nowadays, more and more enterprises adopt employees on the internet, more and more people groups are required to find out work through mobile phone recruitment software, the existing recruitment software can screen and match information of recruitment information of the enterprises and personal resumes of job seekers, a large number of job seekers meeting basic conditions are provided for the enterprises, a large number of enterprises meeting basic requirements are also provided for the job seekers, the job seekers and the enterprises need to carry out private chat and ask questions and communicate with each other, two parties can conveniently acquire more information, but the current matching screening is not fine enough, the subsequent inquiry and communication quantity is large, and the recruitment and job hunting progress is influenced. Therefore, it is desirable to provide a big data artificial intelligence recruitment system and method, which aims to solve or alleviate the above problems.
Disclosure of Invention
Aiming at the defects in the prior art, the invention aims to provide a big data artificial intelligence recruitment system and a big data artificial intelligence recruitment method so as to solve or alleviate the problems in the background art.
The invention is realized in such a way that a big data artificial intelligence recruitment method comprises the following steps:
calling chat information of an enterprise terminal, and analyzing the chat information of the enterprise terminal to obtain enterprise problems and enterprise keywords;
calling chat information of the job seeker, and analyzing the chat information of the job seeker to obtain a job seeker question and job seeker keywords;
receiving recruitment information sent by an enterprise terminal, and screening the resumes of all job seekers at one time according to the recruitment information;
receiving enterprise screening conditions sent by an enterprise terminal, performing secondary screening on job seeker keywords of the remaining job seekers meeting the conditions after the primary screening according to the enterprise screening conditions, and pushing personal resume, job seeker questions and job seeker keywords of the job seekers after the secondary screening to the enterprise terminal;
receiving job hunting information sent by job hunters, and carrying out primary screening on the recruitment information of all enterprises according to the job hunting information;
and receiving job hunting screening conditions sent by job seekers, performing secondary screening on enterprise keywords of the rest enterprises meeting the conditions after the primary screening according to the job hunting screening conditions, and pushing recruitment information, enterprise problems and enterprise keywords of the enterprises after the secondary screening to the job seekers.
As a further scheme of the invention: the step of analyzing the chat information of the enterprise terminal to obtain enterprise problems and enterprise keywords specifically comprises the following steps:
classifying question sentences and statement sentences of the chat information of the enterprise terminal;
classifying again after similarity matching is carried out on all the question sentences to obtain a plurality of categories, determining the number of the question sentences in each category, carrying out descending order arrangement on the categories according to the number, and selecting one question sentence from each category arranged in the previous N as an enterprise problem, wherein N is a positive integer;
and after similarity matching is carried out on all the statement sentences, classifying again to obtain a plurality of categories, determining the number of the statement sentences in each category, arranging the categories in a descending order according to the number, selecting one statement sentence from each category arranged in the front M as an enterprise keyword, wherein M is a positive integer.
As a further scheme of the invention: the step of analyzing the chat information of the job seeker to obtain the question of the job seeker and the keyword of the job seeker specifically comprises the following steps:
classifying the question and statement sentence of the chat information of the job seeker;
classifying again after similarity matching is carried out on all the question sentences to obtain a plurality of classes, determining the number of the question sentences in each class when the similarity between any two question sentences in each class is larger than a third set value, carrying out descending order arrangement on the classes according to the number, and selecting one question sentence in each class arranged in the front Q as a job seeker question, wherein Q is a positive integer;
and after similarity matching is carried out on all statement sentences, classifying again to obtain a plurality of categories, determining the number of the statement sentences in each category, carrying out descending order arrangement on the categories according to the number, selecting one statement sentence in each category arranged in the previous P as a keyword of the job seeker, wherein P is a positive integer.
As a further scheme of the invention: the method further comprises the following steps:
receiving a chat information privacy instruction sent by an enterprise terminal or a job seeker;
and receiving a chat information selection instruction sent by the enterprise terminal or the job seeker, wherein the selected chat information is kept secret and cannot be called.
As a further scheme of the invention: before the chat information of the enterprise terminal or the job seeker is called, whether the chat information is allowed to be called or not is sent to the user, and the chat information can be automatically called if and only if the user allows the chat information to be called.
Another object of the present invention is to provide a big data artificial intelligence recruitment system, comprising:
the enterprise chatting information analysis module is used for calling the chatting information of the enterprise terminal and analyzing the chatting information of the enterprise terminal to obtain enterprise problems and enterprise keywords;
the job hunting chat information analysis module is used for calling the chat information of the job hunter and analyzing the chat information of the job hunter to obtain a job hunter question and a job hunter keyword;
the job seeker primary screening module is used for receiving the recruitment information sent by the enterprise terminal and screening the personal resumes of all job seekers at one time according to the recruitment information;
the job seeker secondary screening module is used for receiving the enterprise screening conditions sent by the enterprise terminal, secondarily screening the job seeker keywords of the rest job seekers meeting the conditions after primary screening according to the enterprise screening conditions, and pushing the personal resume, the job seeker questions and the job seeker keywords of the job seekers after secondary screening to the enterprise terminal;
the enterprise primary screening module is used for receiving job hunting information sent by job seekers and carrying out primary screening on the recruitment information of all enterprises according to the job hunting information;
and the enterprise secondary screening module is used for receiving job hunting screening conditions sent by job seekers, performing secondary screening on enterprise keywords of the rest enterprises which meet the conditions after primary screening according to the job hunting screening conditions, and pushing the recruitment information, the enterprise problems and the enterprise keywords of the enterprises which are subjected to secondary screening to the job seekers.
As a further scheme of the invention: the enterprise chat information analysis module comprises:
the first sentence pattern classification unit is used for classifying question sentences and statement sentences of the chat information of the enterprise terminal;
the enterprise problem determining unit is used for classifying again after similarity matching is carried out on all the question sentences to obtain a plurality of categories, the similarity between any two question sentences in each category is larger than a first set value, the number of the question sentences in each category is determined, the categories are arranged in a descending order according to the number, one question sentence in each category arranged in the front N is selected as an enterprise problem, and N is a positive integer;
and the enterprise keyword determining unit is used for classifying all the statement sentences again after similarity matching to obtain a plurality of categories, determining the number of the statement sentences in each category, sequencing the categories in a descending manner according to the number of the statement sentences, selecting one statement sentence from each category arranged in the front M as an enterprise keyword, wherein M is a positive integer.
As a further scheme of the invention: the job-hunting chat information analysis module comprises:
the second sentence pattern classification unit is used for classifying question sentences and statement sentences of the chat information of the job seeker;
the job seeker problem determining unit is used for classifying again after similarity matching is carried out on all the questions to obtain a plurality of categories, the similarity between any two questions in each category is larger than a third set value, the number of the questions in each category is determined, the categories are arranged in a descending order according to the number, one question is selected from each category arranged in the front Q as a job seeker problem, and Q is a positive integer;
and the job hunting keyword determining unit is used for performing similarity matching on all statement sentences and then classifying again to obtain a plurality of categories, the similarity between any two statement sentences in each category is greater than a fourth set value, the number of statement sentences in each category is determined, the categories are arranged in a descending order according to the number, one statement sentence is selected from each category arranged in the previous P as a job hunting keyword, and P is a positive integer.
As a further scheme of the invention: the system also comprises a chat information security module, wherein the chat information security module specifically comprises:
the privacy instruction receiving unit is used for receiving a chat information privacy instruction sent by an enterprise terminal or a job seeker;
and the confidential information selection unit is used for receiving a chat information selection instruction sent by the enterprise terminal or the job seeker, and the selected chat information is confidential and cannot be called.
Compared with the prior art, the invention has the beneficial effects that:
the invention obtains enterprise problems and enterprise keywords by calling the chat information of the enterprise end and analyzing the chat information of the enterprise end; calling the chat information of the job seeker, and analyzing the chat information of the job seeker to obtain a job seeker question and job seeker keywords; screening the keywords of the job seeker according to the screening conditions of the enterprise, and pushing the personal resume of the screened job seeker, the questions of the job seeker and the keywords of the job seeker to the enterprise terminal; and screening the enterprise keywords according to the job hunting screening conditions, and pushing the screened recruitment information, enterprise problems and enterprise keywords of the enterprise to job hunters. So, the enterprise end can obtain more accurate job seeker and can obtain more comprehensive job seeker information, how to prepare in advance to deal with job seeker's problem, and job seeker also can match more accurate enterprise and can obtain more comprehensive enterprise information, how to prepare in advance to deal with enterprise's problem, and follow-up communication is more convenient for recruitment and job hunting process.
Drawings
Fig. 1 is a flow chart of a big data artificial intelligence recruitment method.
Fig. 2 is a flowchart of analyzing chat information of an enterprise terminal to obtain enterprise problems and enterprise keywords in a big data artificial intelligence recruitment method.
Fig. 3 is a flowchart illustrating analyzing chat information of job seekers to obtain job seekers questions and job seeker keywords in a big-data artificial intelligence recruitment method.
Fig. 4 is a flowchart of receiving a chat information privacy instruction sent by an enterprise terminal or a job seeker in the big data artificial intelligence recruitment method.
Fig. 5 is a schematic structural diagram of a big data artificial intelligence recruitment system.
Fig. 6 is a schematic structural diagram of an enterprise chat information analysis module in a big data artificial intelligence recruitment system.
Fig. 7 is a schematic structural diagram of a job hunting and chatting information analysis module in the big data artificial intelligence recruitment system.
Fig. 8 is a schematic structural diagram of a chat information privacy module in a big data artificial intelligence recruitment system.
Detailed Description
In order to make the objects, technical solutions and advantages of the present invention clearer, the present invention is described in further detail below with reference to the accompanying drawings and specific embodiments. It should be understood that the specific embodiments described herein are merely illustrative of the invention and are not intended to limit the invention.
Specific implementations of the present invention are described in detail below with reference to specific embodiments.
As shown in fig. 1, an embodiment of the present invention provides a big data artificial intelligence recruitment method, which includes the following steps:
s100, calling chat information of an enterprise terminal, and analyzing the chat information of the enterprise terminal to obtain enterprise problems and enterprise keywords;
s200, calling chat information of the job seeker, and analyzing the chat information of the job seeker to obtain a job seeker question and job seeker keywords;
s300, receiving recruitment information sent by an enterprise terminal, and screening personal resumes of all job seekers once according to the recruitment information;
s400, receiving enterprise screening conditions sent by an enterprise terminal, carrying out secondary screening on job seeker keywords of the remaining job seekers meeting the conditions after the primary screening according to the enterprise screening conditions, and pushing personal resume of the job seekers, job seeker questions and job seeker keywords after the secondary screening to the enterprise terminal;
s500, receiving job hunting information sent by job seekers, and screening the recruitment information of all enterprises for one time according to the job hunting information;
s600, receiving job hunting and screening conditions sent by job hunters, carrying out secondary screening on enterprise keywords of the rest enterprises which meet the conditions after primary screening according to the job hunting and screening conditions, and pushing recruitment information, enterprise problems and enterprise keywords of the enterprises which are subjected to secondary screening to the job hunters.
It needs to be explained that nowadays, more and more enterprises employ employees on the internet, more and more people groups are found to work through mobile phone recruitment software, the existing recruitment software can screen and match the recruitment information of the enterprises and the personal resumes of job seekers, a large number of job seekers meeting basic conditions are provided for the enterprises, and a large number of enterprises meeting basic requirements are also provided for the job seekers.
In the embodiment of the invention, the chat information of the enterprise end and the chat information of the job seeker are called, and before the chat information of the enterprise end or the job seeker is called, whether the chat information is allowed to be called or not is sent to the user, the user is an enterprise user or a job seeker, and the chat information can be automatically called only when the user is allowed, so that the embodiment of the invention is easy to understand, the chat contents between the enterprise end and the job seeker are originally mutually sent to strangers, and therefore the chat information can be basically accepted and called for use; it should be noted that the enterprise questions are questions that the enterprise frequently asks job seekers, the enterprise keywords are responses to high-frequency questions of all job seekers, the job seeker questions are questions that the job seeker frequently asks the enterprise, the job seeker keywords are responses to high-frequency questions that all the enterprises propose, it is obvious that the enterprise questions can reflect information that the enterprise is interested in, the enterprise keywords can reflect attributes of the enterprise, the job seeker questions can reflect information that the job seeker is interested in, and the job seeker keywords can reflect self attributes of the job seeker.
After the enterprise terminal sends the recruitment information, the personal resumes of all job seekers are screened once according to the recruitment information, the recruitment information generally comprises positions, age requirements, professional requirements, skill requirements, treatment and the like, and the screening once is a common means of the existing recruitment software and is not repeated herein; and then the enterprise end can input enterprise screening conditions, wherein the enterprise screening conditions are set based on the information of the enterprise and are not convenient to be directly written in the job hunting information, such as receiving overtime work, receiving high-intensity work and the like.
After the job seeker sends job hunting information, screening the recruitment information of all enterprises for one time according to the job hunting information, wherein the screening for one time is a common means of the existing recruitment software and is not repeated; and then the job seeker can input job hunting screening conditions, enterprise keywords of the rest of enterprises are screened secondarily according to the job hunting screening conditions, the job hunting screening conditions are set based on information of the job seeker's intention and are inconvenient to be directly written in a personal resume, for example, the job hunting is not accepted, the number of days for the annual holiday is not less than or equal to, and the job seeker is pushed recruitment information, enterprise problems and enterprise keywords of the enterprises subjected to secondary screening, so that the job seeker can be matched with more accurate enterprises and can obtain more comprehensive enterprise information, how to deal with the enterprise problems can be prepared in advance, the follow-up communication is more convenient, and the job hunting process is accelerated.
As shown in fig. 2, as a preferred embodiment of the present invention, the step of analyzing chat information of an enterprise end to obtain an enterprise question and an enterprise keyword specifically includes:
s101, classifying question and statement sentences of chat information of an enterprise terminal;
s102, classifying again after similarity matching is carried out on all question sentences to obtain a plurality of categories, determining the number of the question sentences in each category, carrying out descending order arrangement on the categories according to the number, and selecting one question sentence in each category arranged in the front N as an enterprise problem, wherein N is a positive integer;
s103, classifying again after similarity matching is carried out on all statement sentences to obtain a plurality of categories, determining the number of the statement sentences in each category, arranging the categories in a descending order according to the number, selecting one statement sentence in each category arranged in the former M as an enterprise keyword, wherein M is a positive integer.
In the embodiment of the present invention, question and statement sentence classification is performed on chat information of an enterprise terminal, the chat information of the enterprise terminal refers to unilateral information sent by the enterprise terminal, and first, whether question sentences exist or not is determined, and whether question words or question marks exist in sentences is determined, for example, the question words include: if so, judging a question sentence, otherwise, judging a statement sentence; then, after similarity matching is carried out on all the question sentences, classifying again to obtain a plurality of categories, wherein the similarity between any two question sentences in each category is greater than a first set value, so that the question sentences in each category are similar, the number of the question sentences in each category is determined, the categories are arranged in a descending order according to the number, one question sentence in each category arranged in the previous N is arbitrarily selected as an enterprise problem, and N is a positive integer; classifying again after similarity matching is carried out on all statement sentences to obtain a plurality of categories, wherein the similarity between any two statement sentences in each category is greater than a second set value, so that the statement sentences in each category are similar, the number of the statement sentences in each category is determined, the categories are arranged in a descending order according to the number, one statement sentence in each category arranged in the former M is arbitrarily selected as an enterprise keyword, M is a positive integer, and N, M, a first set value and a second set value are all set fixed values in advance; when the similarity is calculated for two sentences, the similarity = the number of identical characters × 2/the sum of the numbers of characters of the two sentences.
As shown in fig. 3, as a preferred embodiment of the present invention, the step of analyzing the chat information of the job seeker to obtain the question of the job seeker and the keyword of the job seeker specifically includes:
s201, classifying the question and statement sentence of the chat information of the job seeker;
s202, classifying again after similarity matching is carried out on all the question sentences to obtain a plurality of classes, determining the number of the question sentences in each class when the similarity between any two question sentences in each class is larger than a third set value, carrying out descending order arrangement on the classes according to the number, and selecting one question sentence in each class arranged in the front Q as a job seeker question, wherein Q is a positive integer;
s203, classifying again after similarity matching is carried out on all statement sentences to obtain a plurality of categories, determining the number of statement sentences in each category, arranging the categories in descending order according to the number, selecting one statement sentence in each category arranged in the previous P as a keyword of a job seeker, wherein P is a positive integer.
In the embodiment of the invention, the chat information of the job seeker is single-party information sent by the job seeker, and the Q, the P, the third set value and the fourth set value are all set fixed values in advance.
As shown in fig. 4, as a preferred embodiment of the present invention, the method further includes:
s701, receiving a chat information confidentiality instruction sent by an enterprise terminal or a job seeker;
s702, receiving a chat information selection instruction sent by the enterprise terminal or the job seeker, wherein the selected chat information is kept secret and cannot be called.
It is easy to understand that even if the user allows to call the chat information, there is a situation that part of the chat information is not wanted to be called by the system, at this moment, the user directly inputs the chat information security instruction and inputs the chat information selection instruction, and the chat information selection instruction is that the user selects some chat information needing security, so that the selected chat information cannot be called. It should be noted that, the content that has just been chatted cannot be called, and the chat message can be called only after sending out a preset time value, for example, the chat message can be called only after sending out three hours, which ensures that the user has enough time to select the confidential message.
As shown in fig. 5, an embodiment of the present invention further provides a big data artificial intelligence recruitment system, where the system includes:
the enterprise chat information analysis module 100 is used for calling the chat information of the enterprise terminal and analyzing the chat information of the enterprise terminal to obtain enterprise problems and enterprise keywords;
the job hunting chat information analysis module 200 is used for calling the chat information of the job seeker and analyzing the chat information of the job seeker to obtain a job seeker question and a job seeker keyword;
the job seeker primary screening module 300 is used for receiving the recruitment information sent by the enterprise terminal and carrying out primary screening on the personal resumes of all job seekers according to the recruitment information;
the job seeker secondary screening module 400 is used for receiving the enterprise screening conditions sent by the enterprise terminal, secondarily screening job seeker keywords of the remaining job seekers meeting the conditions after primary screening according to the enterprise screening conditions, and pushing personal resumes, job seeker questions and job seeker keywords of the job seekers after secondary screening to the enterprise terminal;
the enterprise primary screening module 500 is used for receiving job hunting information sent by job hunters and carrying out primary screening on the recruitment information of all enterprises according to the job hunting information;
the enterprise secondary screening module 600 is configured to receive job hunting screening conditions sent by job seekers, perform secondary screening on enterprise keywords of remaining enterprises that meet the conditions after the primary screening according to the job hunting screening conditions, and push recruitment information, enterprise problems, and enterprise keywords of the enterprises that are subjected to the secondary screening to the job seekers.
As shown in fig. 6, as a preferred embodiment of the present invention, the enterprise chat information analyzing module 100 includes:
a first sentence pattern classification unit 101, configured to classify question sentences and statement sentences of chat information of the enterprise;
the enterprise problem determining unit 102 is configured to perform similarity matching on all the question sentences and then classify the question sentences again to obtain a plurality of categories, the similarity between any two question sentences in each category is greater than a first set value, determine the number of the question sentences in each category, perform descending order arrangement on the categories according to the number, select one question sentence in each category arranged in the first N as an enterprise problem, and N is a positive integer;
the enterprise keyword determining unit 103 is configured to perform similarity matching on all the declarative sentences, then classify the declarative sentences again to obtain a plurality of categories, determine the number of the declarative sentences in each category, perform descending order arrangement on the categories according to the number, select one declarative sentence in each category arranged in the top M as an enterprise keyword, where M is a positive integer.
As shown in fig. 7, as a preferred embodiment of the present invention, the job-searching chat message analysis module 200 includes:
a second sentence pattern classification unit 201 for classifying the question and statement sentences of the chat information of the job seeker;
the job seeker problem determining unit 202 is used for classifying again after similarity matching is carried out on all the questions to obtain a plurality of categories, the similarity between any two questions in each category is larger than a third set value, the number of the questions in each category is determined, the categories are arranged in a descending order according to the number, one question is selected from each category arranged in the front Q as a job seeker problem, and Q is a positive integer;
the job hunting keyword determining unit 203 is configured to perform similarity matching on all the statement sentences and then classify the statement sentences again to obtain a plurality of categories, where the similarity between any two statement sentences in each category is greater than a fourth set value, determine the number of statement sentences in each category, perform descending order arrangement on the categories according to the number, and select one statement sentence in each category arranged in the previous P as a job hunting keyword, where P is a positive integer.
As shown in fig. 8, as a preferred embodiment of the present invention, the system further includes a chat information security module 700, where the chat information security module 700 specifically includes:
a privacy instruction receiving unit 701, configured to receive a chat information privacy instruction sent by an enterprise or a job seeker;
the confidential information selecting unit 702 is configured to receive a chat information selection instruction sent by the enterprise terminal or the job seeker, where the selected chat information is confidential and cannot be called.
The present invention has been described in detail with reference to the preferred embodiments thereof, and it should be understood that the present invention is not limited thereto, but includes any modifications, equivalents, and improvements within the spirit and scope of the present invention.
It should be understood that, although the steps in the flowcharts of the embodiments of the present invention are shown in sequence as indicated by the arrows, the steps are not necessarily performed in sequence as indicated by the arrows. The steps are not limited to being performed in the exact order illustrated and, unless explicitly stated herein, may be performed in other orders. Moreover, at least a portion of the steps in various embodiments may include multiple sub-steps or multiple stages that are not necessarily performed at the same time, but may be performed at different times, and the order of performance of the sub-steps or stages is not necessarily sequential, but may be performed in turn or alternately with other steps or at least a portion of the sub-steps or stages of other steps.
Other embodiments of the disclosure will be apparent to those skilled in the art from consideration of the specification and practice of the disclosure herein. This application is intended to cover any variations, uses, or adaptations of the disclosure following, in general, the principles of the disclosure and including such departures from the present disclosure as come within known or customary practice within the art to which the disclosure pertains. It is intended that the specification and examples be considered as exemplary only, with a true scope and spirit of the disclosure being indicated by the following claims.
Claims (9)
1. A big data artificial intelligence recruitment method is characterized by comprising the following steps:
calling chat information of an enterprise terminal, and analyzing the chat information of the enterprise terminal to obtain enterprise problems and enterprise keywords;
calling chat information of the job seeker, and analyzing the chat information of the job seeker to obtain a job seeker question and job seeker keywords;
receiving recruitment information sent by an enterprise terminal, and screening the resumes of all job seekers at one time according to the recruitment information;
receiving enterprise screening conditions sent by an enterprise terminal, performing secondary screening on job seeker keywords of the remaining job seekers meeting the conditions after the primary screening according to the enterprise screening conditions, and pushing personal resume, job seeker questions and job seeker keywords of the job seekers after the secondary screening to the enterprise terminal;
receiving job hunting information sent by job hunters, and carrying out primary screening on the recruitment information of all enterprises according to the job hunting information;
and receiving job hunting screening conditions sent by job seekers, performing secondary screening on enterprise keywords of the rest enterprises meeting the conditions after the primary screening according to the job hunting screening conditions, and pushing recruitment information, enterprise problems and enterprise keywords of the enterprises after the secondary screening to the job seekers.
2. The big data artificial intelligence recruitment method according to claim 1, wherein the step of analyzing the chat information of the enterprise end to obtain enterprise problems and enterprise keywords specifically comprises the steps of:
classifying question sentences and statement sentences of the chat information of the enterprise terminal;
classifying again after similarity matching is carried out on all the question sentences to obtain a plurality of categories, determining the number of the question sentences in each category, carrying out descending order arrangement on the categories according to the number, and selecting one question sentence from each category arranged in the previous N as an enterprise problem, wherein N is a positive integer;
and after similarity matching is carried out on all the statement sentences, classifying again to obtain a plurality of categories, determining the number of the statement sentences in each category, arranging the categories in a descending order according to the number, selecting one statement sentence from each category arranged in the front M as an enterprise keyword, wherein M is a positive integer.
3. The big-data artificial intelligence recruitment method according to claim 1, wherein the step of analyzing the chat information of the job seeker to obtain the question of the job seeker and the keyword of the job seeker specifically comprises the steps of:
classifying the question and statement sentence of the chat information of the job seeker;
classifying again after similarity matching is carried out on all the question sentences to obtain a plurality of categories, determining the number of the question sentences in each category, carrying out descending order arrangement on the categories according to the number, and selecting one question sentence from each category of the previous Q as a job seeker question, wherein the Q is a positive integer;
and classifying again after similarity matching is carried out on all statement sentences to obtain a plurality of categories, wherein the similarity between any two statement sentences in each category is greater than a fourth set value, the number of statement sentences in each category is determined, the categories are arranged in a descending order according to the number, one statement sentence in each category arranged in the previous P is selected as a keyword of a job seeker, and P is a positive integer.
4. The big data artificial intelligence recruitment method according to claim 1, further comprising:
receiving a chat information privacy instruction sent by an enterprise terminal or a job seeker;
and receiving a chat information selection instruction sent by the enterprise terminal or the job seeker, wherein the selected chat information is kept secret and cannot be called.
5. The big data artificial intelligence recruitment method according to claim 1, wherein before the chat information of the enterprise terminal or the job seeker is called, whether the chat information is allowed to be called is sent to the user, and if and only if the chat information is allowed by the user, the chat information can be automatically called.
6. A big data artificial intelligence recruitment system, the system comprising:
the enterprise chatting information analysis module is used for calling the chatting information of the enterprise terminal and analyzing the chatting information of the enterprise terminal to obtain enterprise problems and enterprise keywords;
the job hunting chat information analysis module is used for calling the chat information of the job hunter and analyzing the chat information of the job hunter to obtain a job hunter question and a job hunter keyword;
the job seeker primary screening module is used for receiving the recruitment information sent by the enterprise terminal and screening the personal resumes of all job seekers at one time according to the recruitment information;
the job seeker secondary screening module is used for receiving the enterprise screening conditions sent by the enterprise terminal, secondarily screening job seeker keywords of the remaining job seekers meeting the conditions after primary screening according to the enterprise screening conditions, and pushing personal resumes, job seeker questions and job seeker keywords of the job seekers after secondary screening to the enterprise terminal;
the enterprise primary screening module is used for receiving job hunting information sent by job seekers and carrying out primary screening on the recruitment information of all enterprises according to the job hunting information;
and the enterprise secondary screening module is used for receiving job hunting screening conditions sent by job hunters, performing secondary screening on enterprise keywords of the rest enterprises meeting the conditions after primary screening according to the job hunting screening conditions, and pushing recruitment information, enterprise problems and enterprise keywords of the enterprises subjected to secondary screening to the job hunters.
7. The big data artificial intelligence recruitment system of claim 6, wherein the enterprise chat information analysis module comprises:
the first sentence pattern classification unit is used for classifying question sentences and statement sentences of the chat information of the enterprise terminal;
the enterprise problem determining unit is used for classifying again after similarity matching is carried out on all the question sentences to obtain a plurality of categories, the similarity between any two question sentences in each category is larger than a first set value, the number of the question sentences in each category is determined, the categories are arranged in a descending order according to the number, one question sentence in each category arranged in the front N is selected as an enterprise problem, and N is a positive integer;
and the enterprise keyword determining unit is used for classifying again after similarity matching is carried out on all the statement sentences to obtain a plurality of categories, the similarity between any two statement sentences in each category is greater than a second set value, the number of statement sentences in each category is determined, the categories are arranged in a descending order according to the number, one statement sentence in each category arranged in the front M is selected as an enterprise keyword, and M is a positive integer.
8. The big data artificial intelligence recruitment system of claim 6 wherein the job hunting and chat information analysis module comprises:
the second sentence pattern classification unit is used for classifying question sentences and statement sentences of the chat information of the job seeker;
the job seeker problem determining unit is used for classifying again after similarity matching is carried out on all the questions to obtain a plurality of categories, the similarity between any two questions in each category is larger than a third set value, the number of the questions in each category is determined, the categories are arranged in a descending order according to the number, one question is selected from each category arranged in the front Q as a job seeker problem, and Q is a positive integer;
and the job hunting keyword determining unit is used for performing similarity matching on all statement sentences and then classifying again to obtain a plurality of categories, the similarity between any two statement sentences in each category is greater than a fourth set value, the number of statement sentences in each category is determined, the categories are arranged in a descending order according to the number, one statement sentence is selected from each category arranged in the previous P as a job hunting keyword, and P is a positive integer.
9. The big data artificial intelligence recruitment system according to claim 6, wherein the system further comprises a chat information privacy module, and the chat information privacy module specifically comprises:
the privacy instruction receiving unit is used for receiving a chat information privacy instruction sent by an enterprise terminal or a job seeker;
and the confidential information selection unit is used for receiving a chat information selection instruction sent by the enterprise terminal or the job seeker, and the selected chat information is confidential and cannot be called.
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