CN114611003A - Post recommendation method, device and equipment for public recruitment and examination reporting - Google Patents
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Abstract
The invention discloses a post recommendation method, a device and a system for public recruitment and examination reporting, wherein the method comprises the following steps: calculating resume feature codes and post feature codes; judging whether the identical resume feature codes and post feature codes exist in the post data or not, and if so, calling feature resume scores; if not, calculating to obtain a feature resume score, and storing the resume feature code, the post feature code and the feature resume score into a post database; calculating to obtain a non-characteristic resume score, and calculating to obtain a post matching degree result; and returning the post matching degree result to the user. The method can effectively reduce the calculated amount of the public post searching system, improve the service response speed, quickly search the public post information released by each province, city and county, set different matching degrees for different posts based on the personal resume of the examinee, and intuitively solve the post information with higher matching degree by the examinee so as to realize quick screening.
Description
Technical Field
The invention belongs to the technical field of post recommendation, and particularly relates to a post recommendation method, device and equipment for public enrollment and examination reporting.
Background
In recent years, the popularity of entry by a public officer or a public institution has been high, and in general, when a public institution or a public institution issues post recruitment notices, examinees need to constantly pay attention to the entry information issued by each official institution and select a post which is interested in the examinee and meets entry conditions from a large amount of post information. However, in the current environment, the number of the positions for examination published in each province, city, region and county in the country is large, the publishing channels are wide, and the examination information is complicated, so that it is difficult for examinees to search the positions for examination, some important information such as examination report specialties, academic requirements, background requirements and the like are usually presented in non-visual forms such as an attachment table or secondary links, and if the examinees want to find the positions for the mood, each entry needs to be opened successively to be screened and stored, so that the efficiency is very low. Therefore, the design of a unified enrollment information acquisition, release and retrieval platform is of great significance.
In the public post search platform in the prior art, a specific post information list is screened out by searching through keywords and partial preset conditions, scoring is carried out according to the review condition of the matched post by the reviewer filled in by the reviewer, the finally presented post list is arranged in a reverse order according to the score of the matching degree, and the post with the highest matching degree is arranged at the top. However, the post recommendation method involves a large amount of operations, and as the number of released posts increases, the calculation amount of the post matching degree also increases linearly, and more computing resources are consumed, which is not favorable for continuous development.
Disclosure of Invention
The invention aims to provide a post recommendation method, a post recommendation device and post recommendation equipment for public enrollment and submission, which are used for solving at least one technical problem in the prior art.
In order to achieve the purpose, the invention adopts the following technical scheme:
in a first aspect, the present invention provides a post recommendation method for public enrollment and examination, comprising:
respectively calculating resume feature codes of the resume of the examinee and post feature codes of the post information; each resume feature code is a digital code corresponding to each examinee resume, and each position feature code is a digital code corresponding to each position information;
judging whether the identical resume feature codes and post feature codes exist in the post database, if so, calling feature resume scores prestored in the post database;
if not, calculating to obtain a feature resume score by using the feature items of the examinee resume and the feature items of the post information, and storing the feature resume score, the resume feature codes and the post feature codes into the post database after binding the feature resume score, the resume feature codes and the post feature codes;
calculating by using the non-characteristic items in the examinee resume and the non-characteristic items in the position information to obtain a non-characteristic resume score, and calculating according to the non-characteristic resume score and the characteristic resume score to obtain a position matching degree result;
and returning the post matching degree result to the user.
In one possible design, the method further includes:
and retrieving new position information periodically, calculating the position matching degree of the new position information and the resume of the examinee, and pushing the new position information to the user when the position matching degree is higher than a threshold value.
In one possible design, the resume feature code of the examinee resume is calculated, and the method comprises the following steps:
extracting a plurality of resume items key and a value corresponding to each resume item from the examinee resume, and constructing a key-value pair array;
sorting the key value pair arrays according to the resume entry key, and serializing the sorted key value pair arrays;
and converting the serialized data into the resume feature codes by using an MD5 message digest algorithm.
In one possible design, the calculating the feature resume score by using the feature entry of the examinee resume and the feature entry of the position information includes:
sequentially extracting first post items with cardinality lower than a threshold value from the post information, and respectively calculating scores Ki of the resume of the examinee under each first post item;
calculating to obtain a characteristic resume score S1 according to the score Ki of the resume of the examinee under each first post item and the weight value Mi of the item, wherein the calculation formula is as follows:
where n represents the number of first position entries and i represents the ith first position entry in n.
In one possible design, calculating the score Ki of the test taker's resume at each first position entry comprises:
judging whether the current first post item is set as a hidden item in the post information, if so, judging that the resume is not matched, and judging that the resume of the examinee is 0, otherwise, judging whether the resume of the examinee is filled with a value corresponding to the current first post item;
if the examinee resume is filled with a Value corresponding to the current first position entry, judging that the current position requirement is set to be unlimited, if the current position requirement is set to be unlimited, considering that the resume is matched, and judging that the examinee resume is 1, and if the current position requirement is not set to be unlimited, judging that the Value filled in the examinee resume belongs to the Value Values of the current first position entry;
and if the Value filled in the resume of the examinee belongs to the Value corresponding to the current first position item, the resume is considered to be matched, the score of the resume of the examinee is 1, and if the Value filled in the resume of the examinee does not belong to the Value corresponding to the current first position item, the resume is considered to be unmatched, and the score of the resume of the examinee is 0.
In one possible design, the calculating the non-characteristic resume score by using the non-characteristic entries in the examinee resume and the non-characteristic entries in the position information comprises:
sequentially extracting second position items with cardinality larger than or equal to a threshold value from the position information, and respectively calculating scores Gj of the examinees under each second position item;
and calculating to obtain a non-characteristic resume score S2 according to the score Gj of the examinee under each second position item and the weight value Mj of the item, wherein the calculation formula is as follows:
where m represents the number of second position entries and j represents the jth second position entry in m.
In one possible design, the calculating the result of the post matching degree according to the non-feature resume score and the feature resume score includes:
according to the non-feature resume score S2 and the feature resume score S1, a post matching degree result S is obtained through calculation, and the calculation formula is as follows:
wherein, w represents the total number of entries of the position information, w is m + n, d represents the d-th entry in w, Md represents the weight value of the d-th entry, and a represents the set highest threshold of the matching degree.
In a second aspect, the present invention provides a post recommendation apparatus for a public attraction, comprising:
the characteristic code calculating module is used for respectively calculating resume characteristic codes of the resume of the examinee and post characteristic codes of the post information; each resume feature code is a digital code corresponding to each examinee resume, and each post feature code is a digital code corresponding to each post information;
the characteristic code judging module is used for judging whether the identical resume characteristic codes and the identical post characteristic codes exist in the post database, and if so, calling the characteristic resume scores prestored in the post database;
the first score calculating module is used for calculating to obtain a feature resume score by using the feature items of the examinee resume and the feature items of the post information if the examinee resume score is not the same as the feature item of the post information, and storing the feature resume score, the resume feature code and the post feature code into the post database after the feature resume score is bound with the resume feature code and the post feature code;
the second score calculating module is used for calculating a non-characteristic resume score by using a non-characteristic entry in the examinee resume and a non-characteristic entry in the position information, and calculating a position matching degree result according to the non-characteristic resume score and the characteristic resume score;
and the result returning module is used for returning the post matching degree result to the user.
In one possible design, the apparatus further includes:
and the post pushing module is used for periodically retrieving the newly added post information, calculating the post matching degree of the newly added post information and the resume of the examinee, and pushing the newly added post information to the user when the post matching degree is higher than a threshold value.
In one possible design, when calculating the resume feature code of the resume of the examinee, the feature code calculation module is specifically configured to:
extracting a plurality of resume items key and a value corresponding to each resume item from the examinee resume, and constructing a key value pair array;
sorting the key value pair arrays according to the resume entry key, and serializing the sorted key value pair arrays;
and converting the serialized data into the resume feature codes by using an MD5 message digest algorithm.
In one possible design, when the feature resume score is calculated by using the feature entry of the examinee resume and the feature entry of the position information, the first score calculating module is specifically configured to:
sequentially extracting first post items with cardinality lower than a threshold value from the post information, and respectively calculating scores Ki of the resumes of the examinees under each first post item;
calculating to obtain a characteristic resume score S1 according to the score Ki of the resume of the examinee under each first post item and the weight value Mi of the item, wherein the calculation formula is as follows:
where n represents the number of first position entries and i represents the ith first position entry in n.
In one possible design, in calculating the score Ki of the test taker resume under each first position entry, the first score calculation module is specifically configured to:
judging whether the current first post item is set as a hidden item in the post information, if so, judging that the resume is not matched, and judging that the resume score of the examinee is 0, otherwise, judging whether the resume of the examinee is filled with a value corresponding to the current first post item;
if the examinee resume is filled with a Value corresponding to the current first position entry, judging that the current position requirement is set to be unlimited, if the current position requirement is set to be unlimited, considering that the resume is matched, and judging that the examinee resume is 1, and if the current position requirement is not set to be unlimited, judging that the Value filled in the examinee resume belongs to the Value Values of the current first position entry;
and if the Value filled in the resume of the examinee belongs to the Value corresponding to the current first position item, the resume is considered to be matched, the score of the resume of the examinee is 1, and if the Value filled in the resume of the examinee does not belong to the Value corresponding to the current first position item, the resume is considered to be unmatched, and the score of the resume of the examinee is 0.
In one possible design, when the non-feature entry in the test taker resume and the non-feature entry in the position information are used to calculate a non-feature resume score, the second score calculation module is specifically configured to:
sequentially extracting second position items with cardinality larger than or equal to a threshold value from the position information, and respectively calculating scores Gj of the examinees under each second position item;
and calculating to obtain a non-characteristic resume score S2 according to the score Gj of the examinee under each second position item and the weight value Mj of the item, wherein the calculation formula is as follows:
where m represents the number of second position entries and j represents the jth second position entry in m.
In one possible design, when the result of the post matching degree is obtained by calculating according to the non-feature resume score and the feature resume score, the second score calculating module is specifically configured to:
according to the non-feature resume score S2 and the feature resume score S1, a post matching degree result S is obtained through calculation, and the calculation formula is as follows:
wherein, w represents the total number of entries of the position information, w is m + n, d represents the d-th entry in w, Md represents the weight value of the d-th entry, and a represents the set highest threshold of the matching degree.
In a third aspect, the present invention provides a computer device, comprising a memory, a processor and a transceiver, which are communicatively connected in sequence, wherein the memory is used for storing a computer program, the transceiver is used for sending and receiving messages, and the processor is used for reading the computer program and executing the position recommendation method for public offering and checking as described in any one of the possible designs of the first aspect.
In a fourth aspect, the present invention provides a computer-readable storage medium having stored thereon instructions for executing the position recommendation method for public advice and consideration as set forth in any one of the possible designs of the first aspect, when the instructions are run on a computer.
In a fifth aspect, the present invention provides a computer program product comprising instructions which, when run on a computer, cause the computer to perform a position recommendation method for a public attraction as described in any one of the possible designs of the first aspect.
Has the beneficial effects that:
the method comprises the steps of setting a corresponding resume feature code for each examinee resume, setting a corresponding post feature code for each post information, incorporating an entry with a lower base number into feature code calculation, calculating by using examinee resume entry information and post information entry information to obtain a feature score, and storing the resume feature code, the post feature code and the feature score in a post database; in addition, the newly added post information is retrieved at regular time, the matching degree of the newly added post information and the resume of the examinee is calculated, and the newly added post information and the resume of the examinee can be pushed to the examinee when the matching degree is high, so that the real-time post information is continuously provided for the examinee, and the post retrieval service efficiency is improved.
Drawings
FIG. 1 is a flowchart of a post recommendation method for post enrollment in this embodiment;
fig. 2 is a schematic flow chart illustrating the process of calculating the score of the resume at the first position entry in the present embodiment.
Detailed Description
In order to make the objects, technical solutions and advantages of the embodiments of the present disclosure more clear, the technical solutions in the embodiments of the present disclosure will be clearly and completely described below with reference to the drawings in the embodiments of the present disclosure, and it is obvious that the described embodiments are some, but not all embodiments of the present disclosure. All other embodiments, which can be obtained by a person skilled in the art without making any inventive step on the basis of the embodiments in the present description, shall fall within the scope of protection of the present invention.
Examples
In order to solve the technical problems that the public post searching method in the prior art relates to a large amount of operation, the calculated amount of post matching degree is linearly increased along with the increase of the number of issued posts, and more consumed computing resources are consumed, the embodiment of the application provides a post recommendation method for public post examination, the method sets a corresponding resume feature code for each examinee resume, sets a corresponding post feature code for each post information, brings an item with a lower base number into feature code calculation, calculates to obtain a feature score by using examinee resume item information and post information item information, stores the resume feature code, the post feature code and the feature score in a post database, when a new examinee resume and post information are received, firstly searches whether the same feature code exists in the database, and if so, directly calls the feature score, therefore, the characteristic score of a new examinee resume does not need to be calculated, the calculation amount of the system is greatly reduced, and the service response speed is improved.
As shown in fig. 1 and fig. 2, in a first aspect, the present embodiment provides a post recommendation method for public enrollment, including but not limited to the implementation by steps S101 to S105, specifically as follows:
s101, respectively calculating resume feature codes of the resume of the examinee and post feature codes of post information; each resume feature code is a digital code corresponding to each examinee resume, and each post feature code is a digital code corresponding to each post information;
before executing the embodiment, a manager at the back end of the system imports a plurality of post data in batches from different public post systems into the post database, specifically, the post data may be a plurality of public post data issued in a human examination official network, or public post data issued by administrative authorities or public institutions on their own official networks, which is not limited herein.
It should be noted that, the examinee user may fill in personal resume information through a system client, for example, an APP or an H5 web page APP, and the system receives the resume information and performs resume feature code calculation.
In a specific implementation manner of step S101, calculating the resume feature code of the test taker resume includes:
s1011, extracting a plurality of resume items key and a value corresponding to each resume item from the examinee resume, and constructing a key-value pair array;
for example: extracting a plurality of item names such as ' highest academic calendar ', ' professional ', ' native courier ', ' political face ' and the like from the examinee resume, extracting values corresponding to the item names such as ' university ' homeland ', ' material engineering ', ' Sichuan Chengdu ', ' middle party member ' and the like, and constructing a key value pair (item key: item value) based on each item name and the value thereof, wherein the key value pair array is obtained by combining a plurality of key value pairs.
S1012, sequencing the key value pair arrays according to the resume entry key, and serializing the sequenced key value pair arrays;
and S1013, converting the serialized data into the resume feature codes by using an MD5 information summary algorithm.
It can be seen that the resume feature codes in this embodiment are obtained after sorting, serialization and MD5 conversion, and the numerical representation form thereof may be in the form of a character string.
Similarly, when the post feature code of the post information is calculated, the calculation principle is the same as that of the resume feature code, and the difference is only that the extracted item information is different. For example: extracting a plurality of item names such as 'academic requirement', 'professional requirement', 'political face' and the like from the position information, extracting values corresponding to the item names such as 'university subject', 'automation related specialty', 'communist' and the like, and constructing a key value pair (item key: item value) based on each item name and the value thereof, wherein the key value pair array is obtained by combining a plurality of key value pairs.
S102, judging whether the identical resume feature codes and post feature codes exist in the post database, if so, calling feature resume scores prestored in the post database;
it should be noted that, since the entry information extracted from the examinee resume may be the same, the resume feature codes obtained based on the entry information may also be the same, that is, different examinee resumes may correspond to the same resume feature codes, and similarly, the same applies to the post feature codes. Then, after receiving the resume or the post information of a certain examinee, whether the resume or the post information with the same property is received before can be judged firstly, if the resume or the post information exists, the feature resume score which is obtained by calculation and is matched with the resume of the examinee can be called directly, so that repeated calculation is not needed, the calculation amount of a system is greatly reduced, and the service response efficiency is improved.
If not, calculating to obtain a feature resume score by using the feature entry of the examinee resume and the feature entry of the post information, and storing the feature resume score, the resume feature code and the post feature code in the post database after binding the feature resume score with the resume feature code;
it should be noted that, because a plurality of entries are usually involved in one examinee resume or position information, and the radix of the value corresponding to part of the entry key may be larger, for example, "age", and the radix of the value corresponding to the "age" entry in different resumes is larger, and adding the value of the large radix entry to the calculation causes the repetition rate of the feature code to be lower, the purpose of directly extracting the first feature resume score by using the same feature code cannot be achieved, in this embodiment, the entry is divided into the feature entry and the non-feature entry, and only the feature entry is subjected to the feature resume score calculation, and only the feature resume score is repeatedly used, so that the data repetition rate can be improved, the calculation amount is reduced, and the response efficiency is improved.
In a specific implementation manner of step S103, calculating the feature resume score by using the feature entry of the test taker resume and the feature entry of the position information includes:
step S1031, sequentially extracting first post items with cardinality lower than a threshold value from the post information, and respectively calculating scores Ki of the resume of the examinee under each first post item;
specifically, as shown in fig. 2, calculating the score Ki of the resume of the examinee under each first position entry includes:
judging whether the current first post item is set as a hidden item in the post information, if so, judging that the resume is not matched, and judging that the resume of the examinee is 0, otherwise, judging whether the resume of the examinee is filled with a value corresponding to the current first post item;
if the examinee resume is filled with a Value corresponding to the current first position entry, judging that the current position requirement is set to be unlimited, if the current position requirement is set to be unlimited, considering that the resume is matched, and judging that the examinee resume is 1, and if the current position requirement is not set to be unlimited, judging that the Value filled in the examinee resume belongs to the Value Values of the current first position entry;
and if the Value filled in the resume of the examinee belongs to the Value corresponding to the current first position item, the resume is considered to be matched, the score of the resume of the examinee is 1, and if the Value filled in the resume of the examinee does not belong to the Value corresponding to the current first position item, the resume is considered to be unmatched, and the score of the resume of the examinee is 0.
Step S1032, calculating to obtain a feature resume score S1 according to the score Ki of the test taker resume under each first position entry and the weight value Mi of the entry, wherein the calculation formula is as follows:
where n represents the number of first position entries and i represents the ith first position entry in n.
It should be noted that, the weight value Mi of each first position entry may be set according to the importance of the entry, and the higher the importance is, the larger the weight value is, preferably, the value range of the weight value Mi is [1,2 ].
S104, calculating by using non-characteristic items in the examinee resume and non-characteristic items in the position information to obtain a non-characteristic resume score, and calculating according to the non-characteristic resume score and the characteristic resume score to obtain a position matching degree result;
in a specific implementation manner of step S104, calculating a non-feature resume score by using a non-feature entry in the test taker resume and a non-feature entry in the position information, includes:
s1041, sequentially extracting second post items with cardinality larger than or equal to a threshold value from the post information, and respectively calculating scores Gj of the examinees under each second post item;
it should be noted that the calculation principle of the score Gj is the same as that of the score Ki, and the description thereof is omitted here.
Step S1042. according to the score Gj of the examinee under each second position item and the weight value Mj of the item, calculating to obtain a non-characteristic resume score S2, wherein the calculation formula is as follows:
where m represents the number of second position entries and j represents the jth second position entry in m.
In a specific implementation manner of step S104, calculating a post matching degree result according to the non-feature resume score and the feature resume score includes:
according to the non-feature resume score S2 and the feature resume score S1, a post matching degree result S is obtained through calculation, and the calculation formula is as follows:
wherein, w represents the total number of entries of the position information, w is m + n, d represents the d-th entry in w, Md represents the weight value of the d-th entry, and a represents the set highest threshold of the matching degree.
Preferably, the maximum matching degree threshold a takes a value of 6, and the maximum matching degree threshold a can be displayed in a star format.
And returning the post matching degree result to the user.
In a specific embodiment, the method further comprises:
retrieving new post information periodically, calculating the post matching degree of the new post information and the resume of the examinee, and pushing the new post information to the user when the post matching degree is higher than a threshold value; therefore, real-time post information is continuously provided for the examinees, and the post retrieval service efficiency is improved.
Based on the above disclosure, in this embodiment, a corresponding resume feature code is set for each reviewer resume, a corresponding post feature code is set for each post information, an entry with a lower base number is incorporated into the feature code calculation, a feature score is calculated by using the reviewer resume entry information and the post information entry information, the resume feature code, the post feature code and the feature score are stored in the post database, when a new reviewer resume and the post information are received, whether the same feature code exists in the database can be firstly searched, if the same feature code exists, the feature score is directly called, so that the feature score of the new reviewer resume does not need to be calculated, the calculation amount of the system is greatly reduced, the speed of service response is improved, the post information issued by each province and county can be quickly retrieved, different matching degrees are set for different posts based on the reviewer's individual resume, the examinee can intuitively know the post information with higher matching degree to realize rapid screening; in addition, the newly added post information is retrieved at regular time, the matching degree of the newly added post information and the resume of the examinee is calculated, and the newly added post information and the resume of the examinee can be pushed to the examinee when the matching degree is high, so that the real-time post information is continuously provided for the examinee, and the post retrieval service efficiency is improved.
In a second aspect, the present invention provides a post recommendation apparatus for a public attraction, comprising:
the characteristic code calculating module is used for respectively calculating resume characteristic codes of the resume of the examinee and post characteristic codes of the post information; each resume feature code is a digital code corresponding to each examinee resume, and each post feature code is a digital code corresponding to each post information;
the characteristic code judging module is used for judging whether the identical resume characteristic codes and the identical post characteristic codes exist in the post database, and if so, calling the characteristic resume scores prestored in the post database;
the first score calculating module is used for calculating to obtain a feature resume score by using the feature items of the examinee resume and the feature items of the post information if the examinee resume score is not the same as the feature item of the post information, and storing the feature resume score, the resume feature code and the post feature code into the post database after the feature resume score is bound with the resume feature code and the post feature code;
the second score calculating module is used for calculating a non-characteristic resume score by using a non-characteristic entry in the examinee resume and a non-characteristic entry in the position information, and calculating a position matching degree result according to the non-characteristic resume score and the characteristic resume score;
and the result returning module is used for returning the post matching degree result to the user.
In one possible design, the apparatus further includes:
and the post pushing module is used for periodically retrieving the newly added post information, calculating the post matching degree of the newly added post information and the resume of the examinee, and pushing the newly added post information to the user when the post matching degree is higher than a threshold value.
In one possible design, when calculating the resume feature code of the resume of the examinee, the feature code calculation module is specifically configured to:
extracting a plurality of resume items key and a value corresponding to each resume item from the examinee resume, and constructing a key-value pair array;
sorting the key value pair arrays according to the resume entry key, and serializing the sorted key value pair arrays;
and converting the serialized data into the resume feature codes by using an MD5 message digest algorithm.
In a possible design, when the characteristic resume score is calculated by using the characteristic entry of the examinee resume and the characteristic entry of the position information, the first score calculating module is specifically configured to:
sequentially extracting first post items with cardinality lower than a threshold value from the post information, and respectively calculating scores Ki of the resume of the examinee under each first post item;
calculating to obtain a characteristic resume score S1 according to the score Ki of the resume of the examinee under each first post item and the weight value Mi of the item, wherein the calculation formula is as follows:
where n represents the number of first position entries and i represents the ith first position entry in n.
In one possible design, in calculating the score Ki of the examinee's resume under each first position entry, the first score calculation module is specifically configured to:
judging whether the current first post item is set as a hidden item in the post information, if so, judging that the resume is not matched, and judging that the resume of the examinee is 0, otherwise, judging whether the resume of the examinee is filled with a value corresponding to the current first post item;
if the examinee resume is filled with a Value corresponding to the current first position entry, judging that the current position requirement is set to be unlimited, if the current position requirement is set to be unlimited, considering that the resume is matched, and judging that the examinee resume is 1, and if the current position requirement is not set to be unlimited, judging that the Value filled in the examinee resume belongs to the Value Values of the current first position entry;
and if the Value filled in the resume of the examinee belongs to the Value corresponding to the current first position entry, the resume is considered to be matched, the score of the resume of the examinee is 1, and if the Value filled in the resume of the examinee does not belong to the Value corresponding to the current first position entry, the resume is considered to be unmatched, and the score of the resume of the examinee is 0.
In one possible design, when the non-feature entry in the test taker resume and the non-feature entry in the position information are used to calculate a non-feature resume score, the second score calculation module is specifically configured to:
sequentially extracting second position items with cardinality larger than or equal to a threshold value from the position information, and respectively calculating scores Gj of the examinees under each second position item;
and calculating to obtain a non-characteristic resume score S2 according to the score Gj of the examinee under each second position item and the weight value Mj of the item, wherein the calculation formula is as follows:
where m represents the number of second position entries and j represents the jth second position entry in m.
In a possible design, when a result of the post matching degree is obtained by calculating according to the non-feature resume score and the feature resume score, the second score calculating module is specifically configured to:
according to the non-feature resume score S2 and the feature resume score S1, a post matching degree result S is obtained through calculation, and the calculation formula is as follows:
wherein, w represents the total number of entries of the position information, w is m + n, d represents the d-th entry in w, Md represents the weight value of the d-th entry, and a represents the set highest threshold of the matching degree.
In a third aspect, the present invention provides a computer device, comprising a memory, a processor and a transceiver, which are communicatively connected in sequence, wherein the memory is used for storing a computer program, the transceiver is used for sending and receiving messages, and the processor is used for reading the computer program and executing the position recommendation method for public offering and checking as described in any one of the possible designs of the first aspect.
In a fourth aspect, the present invention provides a computer-readable storage medium having stored thereon instructions for executing the position recommendation method for public advice and consideration as set forth in any one of the possible designs of the first aspect, when the instructions are run on a computer.
In a fifth aspect, the present invention provides a computer program product comprising instructions which, when run on a computer, cause the computer to perform a method for post recommendation for a public post as set forth in any one of the possible designs of the first aspect.
Finally, it should be noted that: the above description is only a preferred embodiment of the present invention, and is not intended to limit the scope of the present invention. Any modification, equivalent replacement, or improvement made within the spirit and principle of the present invention should be included in the protection scope of the present invention.
Claims (10)
1. A post recommendation method for a public recruit for an examination, comprising:
respectively calculating resume feature codes of the resume of the examinee and post feature codes of the post information; each resume feature code is a digital code corresponding to each examinee resume, and each post feature code is a digital code corresponding to each post information;
judging whether the identical resume feature codes and post feature codes exist in the post database, if so, calling feature resume scores prestored in the post database;
if not, calculating to obtain a feature resume score by using the feature items of the examinee resume and the feature items of the post information, and storing the feature resume score, the resume feature codes and the post feature codes into the post database after binding the feature resume score with the resume feature codes and the post feature codes;
calculating by using the non-characteristic items in the examinee resume and the non-characteristic items in the position information to obtain a non-characteristic resume score, and calculating according to the non-characteristic resume score and the characteristic resume score to obtain a position matching degree result;
and returning the post matching degree result to the user.
2. The post recommendation method for a public attraction offer according to claim 1, further comprising:
and retrieving new position information periodically, calculating the position matching degree of the new position information and the resume of the examinee, and pushing the new position information to the user when the position matching degree is higher than a threshold value.
3. The post recommendation method for public recruiting and submitting according to claim 1, wherein calculating resume feature code of examinee's resume comprises:
extracting a plurality of resume items key and a value corresponding to each resume item from the examinee resume, and constructing a key-value pair array;
sorting the key value pair arrays according to the resume entry key, and serializing the sorted key value pair arrays;
and converting the serialized data into the resume feature codes by using an MD5 message digest algorithm.
4. The position recommendation method for public recruiting and submitting according to claim 3, wherein the calculating of the feature resume score using the feature entry of the examinee resume and the feature entry of the position information comprises:
sequentially extracting first post items with cardinality lower than a threshold value from the post information, and respectively calculating scores Ki of the resumes of the examinees under each first post item;
calculating to obtain a characteristic resume score S1 according to the score Ki of the resume of the examinee under each first post item and the weight value Mi of the item, wherein the calculation formula is as follows:
where n represents the number of first position entries and i represents the ith first position entry in n.
5. The post recommendation method for a public recruit and reimbursement according to claim 4, wherein calculating the score Ki of the resumes of the examinee at each first post entry comprises:
judging whether the current first post item is set as a hidden item in the post information, if so, judging that the resume is not matched, and judging that the resume score of the examinee is 0, otherwise, judging whether the resume of the examinee is filled with a value corresponding to the current first post item;
if the examinee resume is filled with a Value corresponding to the current first position entry, judging that the current position requirement is set to be unlimited, if the current position requirement is set to be unlimited, considering that the resume is matched, and judging that the examinee resume is 1, and if the current position requirement is not set to be unlimited, judging that the Value filled in the examinee resume belongs to the Value Values of the current first position entry;
and if the Value filled in the resume of the examinee belongs to the Value corresponding to the current first position item, the resume is considered to be matched, the score of the resume of the examinee is 1, and if the Value filled in the resume of the examinee does not belong to the Value corresponding to the current first position item, the resume is considered to be unmatched, and the score of the resume of the examinee is 0.
6. The post recommendation method for a communal enrollment according to claim 4, wherein the calculating of the non-characteristic resume score using the non-characteristic entries in the examinee's resume and the non-characteristic entries in the post information comprises:
sequentially extracting second post items with cardinality larger than or equal to a threshold value from the post information, and respectively calculating scores Gj of the examinees under each second post item;
and calculating to obtain a non-characteristic resume score S2 according to the score Gj of the examinee under each second position item and the weight value Mj of the item, wherein the calculation formula is as follows:
where m represents the number of second position entries and j represents the jth second position entry in m.
7. The post recommendation method for public recruiting and submitting according to claim 6, wherein the step of calculating the post matching degree result according to the non-feature resume score and the feature resume score comprises:
according to the non-feature resume score S2 and the feature resume score S1, a post matching degree result S is obtained through calculation, and the calculation formula is as follows:
wherein, w represents the total number of entries of the position information, w is m + n, d represents the d-th entry in w, Md represents the weight value of the d-th entry, and a represents the set highest threshold of the matching degree.
8. A post recommendation device for a public post submission comprising:
the characteristic code calculating module is used for respectively calculating resume characteristic codes of the resume of the examinee and post characteristic codes of the post information; each resume feature code is a digital code corresponding to each examinee resume, and each post feature code is a digital code corresponding to each post information;
the characteristic code judging module is used for judging whether the identical resume characteristic codes and the identical post characteristic codes exist in the post database, and if so, calling the characteristic resume scores prestored in the post database;
the first score calculating module is used for calculating to obtain a feature resume score by using the feature items of the examinee resume and the feature items of the post information if the examinee resume score is not the same as the feature item of the post information, and storing the feature resume score, the resume feature code and the post feature code into the post database after the feature resume score is bound with the resume feature code and the post feature code;
the second score calculating module is used for calculating a non-characteristic resume score by using a non-characteristic entry in the examinee resume and a non-characteristic entry in the position information, and calculating a position matching degree result according to the non-characteristic resume score and the characteristic resume score;
and the result returning module is used for returning the post matching degree result to the user.
9. A post recommendation device for a post submission according to claim 8, further comprising:
and the post pushing module is used for periodically retrieving the newly added post information, calculating the post matching degree of the newly added post information and the resume of the examinee, and pushing the newly added post information to the user when the post matching degree is higher than a threshold value.
10. A computer device comprising a memory, a processor and a transceiver communicatively connected in sequence, wherein the memory is used for storing a computer program, the transceiver is used for transmitting and receiving messages, and the processor is used for reading the computer program and executing the position recommendation method for public enrollment and examination according to any one of claims 1 to 7.
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