CN113935616A - Data processing method and device - Google Patents
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Abstract
The embodiment of the specification provides a data processing method and a data processing device, wherein the method is applied to a credit platform and comprises the following steps: receiving a target object search request sent by a first object, wherein the search request carries a search keyword; determining attribute information of the first object according to the search request, and determining at least one second object corresponding to the search keyword; determining attribute information of the at least one second object, and obtaining the matching degree of the first object and the at least one second object according to the attribute information of the first object and the attribute information of the at least one second object; and determining at least one second object from the at least one second object as the target object according to the matching degree.
Description
Technical Field
The embodiment of the specification relates to the technical field of computers, in particular to a data processing method.
Background
With the continuous expansion of blue-collar people in China, the demand of recruitment is also gradually vigorous. However, the blue-collar people find work through various off-line channels (such as recommended by acquaintances and heads and solicited) or by being attached to an on-line platform. When the blue-collar community uses such channels, the problems of high threshold, difficulty in filling data, difficulty in searching and screening, etc. are often encountered. When workers use the channels, the problems that whether the worker data is real or not, whether the capability is enough or not, and the contact way is difficult to obtain are often encountered.
Disclosure of Invention
In view of this, the present specification provides a data processing method. One or more embodiments of the present specification also relate to a data processing apparatus, a computing device, a computer-readable storage medium, and a computer program, so as to solve the technical deficiencies of the prior art.
According to a first aspect of embodiments of the present specification, there is provided a data processing method applied to a credit platform, including:
receiving a target object search request sent by a first object, wherein the search request carries a search keyword;
determining attribute information of the first object according to the search request, and determining at least one second object corresponding to the search keyword;
determining attribute information of the at least one second object, and obtaining the matching degree of the first object and the at least one second object according to the attribute information of the first object and the attribute information of the at least one second object;
determining at least one second object from the at least one second object as the target object according to the matching degree;
wherein the first object and the at least one second object are both objects which complete attribute information registration at the credit platform.
According to a second aspect of the embodiments of the present specification, there is provided a data processing apparatus applied to a credit platform, including:
the device comprises a request receiving module, a searching module and a searching module, wherein the request receiving module is configured to receive a target object searching request sent by a first object, and the searching request carries a searching keyword;
a second object determination module configured to determine attribute information of the first object according to the search request and determine at least one second object corresponding to the search keyword;
the matching module is configured to determine attribute information of the at least one second object and obtain a matching degree of the first object and the at least one second object according to the attribute information of the first object and the attribute information of the at least one second object;
a target object determination module configured to determine at least one second object from the at least one second object as the target object according to the matching degree;
wherein the first object and the at least one second object are both objects which complete attribute information registration at the credit platform.
According to a third aspect of embodiments herein, there is provided a computing device comprising:
a memory and a processor;
the memory is used for storing computer-executable instructions, and the processor is used for executing the computer-executable instructions, and the computer-executable instructions realize the steps of the data processing method when being executed by the processor.
According to a fourth aspect of embodiments herein, there is provided a computer-readable storage medium storing computer-executable instructions that, when executed by a processor, implement the steps of the data processing method described above.
According to a fifth aspect of embodiments herein, there is provided a computer program, wherein the computer program, when executed in a computer, causes the computer to perform the steps of the above-mentioned data processing method.
An embodiment of the present specification implements a data processing method and apparatus, where the data processing method is applied to a credit platform, and includes: receiving a target object search request sent by a first object, wherein the search request carries a search keyword; determining attribute information of the first object according to the search request, and determining at least one second object corresponding to the search keyword; determining attribute information of the at least one second object, and obtaining the matching degree of the first object and the at least one second object according to the attribute information of the first object and the attribute information of the at least one second object; determining at least one second object from the at least one second object as the target object according to the matching degree; wherein the first object and the at least one second object are both objects which complete attribute information registration at the credit platform.
Specifically, the data processing method guarantees authenticity and safety of the first object and the second object based on the credit platform, and then intelligently matches requirements for determining the target object by combining attribute information of the first object and attribute information of the second object, so that the requirements for determining the target object by the first object are met (for example, the requirements for using workers are met or the requirements for finding workers by a worker are met), and user experience is improved.
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FIG. 1 is a flow chart of a data processing method provided by an embodiment of the present description;
FIG. 2 is a flow chart of a data processing method according to an embodiment of the present disclosure;
fig. 3 is a schematic structural diagram of a data processing apparatus according to an embodiment of the present specification;
fig. 4 is a block diagram of a computing device according to an embodiment of the present disclosure.
Detailed Description
In the following description, numerous specific details are set forth in order to provide a thorough understanding of the present description. This description may be embodied in many different forms and should not be construed as limited to the embodiments set forth herein, as those skilled in the art will be able to make and use the present disclosure without departing from the spirit and scope of the present disclosure.
The terminology used in the description of the one or more embodiments is for the purpose of describing the particular embodiments only and is not intended to be limiting of the description of the one or more embodiments. As used in one or more embodiments of the present specification and the appended claims, the singular forms "a," "an," and "the" are intended to include the plural forms as well, unless the context clearly indicates otherwise. It should also be understood that the term "and/or" as used in one or more embodiments of the present specification refers to and encompasses any and all possible combinations of one or more of the associated listed items.
It will be understood that, although the terms first, second, etc. may be used herein in one or more embodiments to describe various information, these information should not be limited by these terms. These terms are only used to distinguish one type of information from another. For example, a first can also be referred to as a second and, similarly, a second can also be referred to as a first without departing from the scope of one or more embodiments of the present description. The word "if" as used herein may be interpreted as "at … …" or "when … …" or "in response to a determination", depending on the context.
First, the noun terms to which one or more embodiments of the present specification relate are explained.
Blue collar: people who mainly do physical labor are referred to; they wear blue tools in labor, so they are called blue collars.
Credit data: refers to the user's profile data of various types (including but not limited to name, age, place of employment, occupation, skill certificate, etc.) and the credit score assessed based thereon.
Intelligent matching: according to the search keywords of workers or finding workers, various credit data are combined and searched, the association degree is scored, and finally a group of personnel lists are given.
In this specification, a data processing method is provided. One or more embodiments of the present specification relate to a data processing apparatus, a computing device, a computer-readable storage medium, and a computer program, which are described in detail in the following embodiments one by one.
Referring to fig. 1, fig. 1 is a flowchart illustrating a data processing method according to an embodiment of the present specification, where the data processing method is applied to a credit platform, and specifically includes the following steps.
Step 102: receiving a target object search request sent by a first object, wherein the search request carries a search keyword.
Specifically, the credit platform may be understood as a platform for supervising credit data of a user, where the user registers on the credit platform, and the credit platform configures a credit score, adds or deletes the credit score for the user based on registration information of the user and other behavior data performed through the credit platform, and then predicts authenticity and security of the user through the credit score of the user on the credit platform.
In practical application, the application scenario of the data processing method includes, but is not limited to, a work finding employment scenario, and may also be applied to other people matching scenarios, such as a relative scenario, a collaboration scenario, and the like. For convenience of understanding, in the embodiments of the present specification, a data processing method is specifically described as an example of applying the data processing method to a work finding employment scenario.
Wherein, the first object can be understood as a work seeking user or a work inviting user; then the second object is the recruiter user in case the first object is the recruiter user and the second object is the recruiter user in case the first object is the recruiter user. And the job seeking user or job recruiting user may be an individual or business, etc.
In specific implementation, the search request is sent by the first object to the credit platform through the first object client, for example, when the first object is a worker seeking user, the target object search request sent by the first object is received, which can be understood as that the credit platform receives a search request for the worker seeking user sent by the worker seeking user through the worker seeking client, and the search request carries search keywords, such as position names of cleaning, couriers and the like, or professional keywords of cleaning, cooking and the like.
In the following embodiments, the data processing method is described in detail by taking the first object as a work-seeking user and the second object as a work-seeking user, and the scheme that the first object is a work-seeking user and the second object is a work-seeking user may refer to the following detailed description of the embodiments.
In practical applications, in order to monitor the security and the authenticity of the first object and the second object, the first object and the second object need to be registered in a credit platform in advance, and the credit platform determines the authenticity and the security of the first object and the second object according to the credit scores of the first object and the second object, so as to ensure the subsequent matching security. The specific implementation mode is as follows:
before receiving a target object search request sent by a first object, the method further includes:
receiving attribute information registered by a first object and attribute information registered by at least one second object;
wherein the attribute information of the first object is registered through a first object information registration page displayed by a first object client,
and the attribute information of the at least one second object is registered through a second object information registration page displayed by the second object client.
Wherein, in the case that the first object is a work finding user, the attribute information of the first object includes, but is not limited to, a name, a certificate number, an age, a scholarly calendar, a professional experience, and the like; in the case where the second object is a recruiter, the attribute information of the second object includes, but is not limited to, a name, a certificate number, a registration date, a size of a business, a number of employees, and the like.
In a specific implementation, the attribute information registered by the first object and the attribute information registered by the at least one second object are received, and it can be understood that the credit platform receives the attribute information input by the job seeking user through the job seeking information registration page displayed by the job seeking client and receives the attribute information input by the job seeking user through the job seeking information registration page displayed by the job seeking client.
In order to facilitate the constraint of the first object and the second object and ensure the authenticity of the first object and the second object, the credit platform may assign corresponding credit scores to the first object and the second object respectively based on the attribute information registered by the first object and the second object, and may subsequently constrain the behavior of the first object and the second object based on the credit scores to ensure the authenticity and the security of the first object and the second object. The specific implementation mode is as follows:
after receiving the attribute information registered by the first object and the attribute information registered by the at least one second object, the method further includes:
and allocating a corresponding credit score to the first object according to the attribute information of the first object, and allocating a corresponding credit score to the at least one second object according to the attribute information of the at least one second object.
The credit score may be understood as a credit score value, for example, 70 score, 80 score, and the like, assigned by the credit platform to the first object and the second object according to the attribute information of the first object and the attribute information of the second object, and the security and the authenticity of the first object and the second object are indicated by the high and low of the credit score.
In practical application, the more detailed and complete the attribute information filled by the first object and the second object on the credit platform, the higher the credit score obtained on the credit platform, and the higher the credit score, the higher the authenticity and the security of the first object and the second object are represented. And the higher the credit score of the first object and the second object is, the higher the authority on the credit platform is.
Step 104: determining attribute information of the first object according to the search request, and determining at least one second object corresponding to the search keyword.
Specifically, after the first object performs attribute information registration on the credit platform, after the credit platform receives a search request sent by the first object, the credit platform determines the attribute information registered on the first object. Meanwhile, at least one second object corresponding to the search keyword is determined according to the search keyword in the search request.
Along the above example, in the case that the search keyword is sanitation, the at least one second object corresponding to the search keyword may then be: individuals or businesses having a position associated with cleaning hygiene, such as a home office, a property of a community having a need for cleaning hygiene, a company, etc.
In practical application, in a case where the credit platform restricts the first object by the credit score, in order to ensure security of subsequent object matching, in a case where the first object issues a search request, the credit platform may determine whether to process a target object search request sent by the first object according to the credit score of the first object. The specific implementation mode is as follows:
the determining attribute information of the first object according to the search request and determining at least one second object corresponding to the search keyword includes:
determining attribute information of the first object and a credit score of the first object according to the search request;
determining at least one second object corresponding to the search keyword if it is determined that the credit score of the first object is greater than or equal to a first score threshold.
Specifically, when receiving a search request for a target object, the credit platform first determines attribute information of the first object and a credit score of the first object according to the search request; and determining at least one second object corresponding to the search keyword under the condition that the credit score of the first object is determined to be larger than or equal to the first score threshold value. The first score threshold may be set according to practical applications, and this specification does not limit this.
In an actual application scenario, if the credit score of the first object is smaller than the first score threshold, it may be considered that the security and the authenticity of the first object are low, and the search request sent by the first object may not be processed, so as to avoid causing bad experience to the target object after the target object is subsequently matched.
For example, if the first object is a worker seeking user, the first score threshold is 60, and the credit score of the first object is 50, the authenticity and security of the worker seeking user may be considered to be low, and the target object search request sent by the worker seeking user is not processed, so as to avoid the worker seeking user from defaulting or making the worker seeking user have a poor employment experience after the worker seeking user is assigned to the worker seeking user.
Therefore, in the case that the credit score of the first object is greater than or equal to the first score threshold, at least one second object corresponding to the search keyword is determined; and under the condition that the credit score of the first object is smaller than the first score threshold value, the whole data processing flow is ended, and the search request is not processed any other way, so that the resource waste is avoided.
Step 106: determining attribute information of the at least one second object, and obtaining the matching degree of the first object and the at least one second object according to the attribute information of the first object and the attribute information of the at least one second object.
Specifically, after determining at least one second object corresponding to the search keyword, the credit platform obtains attribute information of the at least one second object based on the attribute information registered by the second object, and obtains a matching degree between the first object and the at least one second object according to the attribute information of the first object and the attribute information of the at least one second object. The at least one second object may be understood as one second object, two second objects or a plurality of second objects.
In the case that the at least one second object is a plurality of second objects, determining the attribute information of each second object at the credit platform, and obtaining the matching degree of the first object and each second object according to the attribute information of the first object and the attribute information of each second object.
In practical applications, in a case that the credit platform restricts the second object by the credit score, in order to ensure security of subsequent object matching, after determining the attribute information of the second object, the credit platform may determine whether the second object is an object that can be matched with the first object according to the credit score of the second object. The specific implementation mode is as follows:
the determining the attribute information of the at least one second object and obtaining the matching degree of the first object and the at least one second object according to the attribute information of the first object and the attribute information of the at least one second object includes:
determining attribute information of the at least one second object and a credit score of the at least one second object;
under the condition that the credit score of the at least one second object is determined to be larger than or equal to a second score threshold value, the matching degree of the first object and the at least one second object is obtained according to the attribute information of the first object and the attribute information of the at least one second object.
Specifically, after determining at least one second object corresponding to the search keyword, the credit platform determines attribute information of each second object and a credit score of each second object from the platform thereof; and under the condition that the credit score of the second object is determined to be greater than or equal to the second score threshold value, obtaining the matching degree of the first object and each second object according to the attribute information of the first object and the attribute information of each second object. The second score threshold may be set according to practical applications, and this specification does not limit this. And the first score threshold and the second score threshold may be the same or different.
In an actual application scenario, if the credit score of the second object is smaller than the second score threshold, it may be considered that the security and the authenticity of the second object are low, and it may be considered that the second object may not be an object matched with the first object, so as to avoid causing a bad experience to the first object after being subsequently matched with the first object as a target object.
For example, if the second object is a job seeker, the second score threshold is 60, and the credit score of the second object is 50, it can be considered that the authenticity and the security of the job seeker are low, and then the job seeker and the job seeker (i.e., the first object) are not matched, thereby avoiding the situations that the job seeker is fraudulent and the job seeker is squeezed, and causing a bad job seeker experience in the process that the job seeker performs job hunting through the credit platform.
Therefore, when the credit score of the second object is greater than or equal to the second score threshold, the matching degree between the first object and the at least one second object is obtained according to the attribute information of the first object and the attribute information of the at least one second object; and under the condition that the credit score of the second object is smaller than the second score threshold, the whole data processing flow is ended, the following flow processing is not carried out, and the resource waste is avoided. That is, only the second object having the credit score equal to or greater than the second score threshold is matched with the first object in the above manner.
And after the first object and the second object pass the credit score and pass the initial examination of the credit platform, the matching degree of the first object and the at least one second object can be obtained according to the attribute information of the first object and the attribute information of the at least one second object passing the examination. The specific implementation mode is as follows:
the determining the attribute information of the at least one second object and obtaining the matching degree of the first object and the at least one second object according to the attribute information of the first object and the attribute information of the at least one second object includes:
determining attribute information of each of the at least one second object;
and matching the attribute information of the first object with the attribute information of each second object to obtain the matching degree of the first object and each second object.
Specifically, the credit platform matches the attribute information of the first object with the attribute information of each second object to obtain a matching degree of the first object and each second object.
Along the above example, if the first object is the job seeking user a, the second objects are the job seeking user b1, the job seeking user b2 and the job seeking user b3, during the matching degree calculation, the attribute information of the job seeking user a is matched with the attribute information of the job seeking user b1, and the matching degree c1 between the job seeking user a and the job seeking user b1 is obtained; matching the attribute information of the worker searching user a with the attribute information of the worker searching user b2 to obtain the matching degree c2 of the worker searching user a and the worker searching user b 2; and matching the attribute information of the worker searching user a with the attribute information of the worker searching user b3 to obtain the matching degree c3 of the worker searching user a and the worker searching user b 3.
In the embodiment of the specification, after the attribute information of the first object and the attribute information of the second object are determined, the attribute information of the first object and the attribute information of the second object are matched, so that the matching degree of the first object and the second object is obtained, a suitable target object is determined for the first object through the matching degree, and the work finding experience of the first object is improved.
Step 108: and determining at least one second object from the at least one second object as the target object according to the matching degree.
Wherein the first object and the at least one second object are both objects which complete attribute information registration at the credit platform.
Specifically, after the matching degree of the first object and each second object is obtained, a suitable target object may be determined for the first object from the at least one second object according to the matching degree. The specific implementation mode is as follows:
the determining at least one second object from the at least one second object as the target object according to the matching degree includes:
and performing descending order arrangement on the at least one second object according to the matching degree, and selecting a preset number of second objects as the target objects according to the sequence from large to small.
In one implementation, all the second objects may be sorted in a descending order according to the matching degree, and the first second objects in a preset number may be selected as the target objects in a descending order. The preset number may be set according to practical applications, for example, 5, 10, and the like. Namely, the first few second objects with higher matching degrees are selected as target objects and recommended to the first object according to the matching degrees.
Of course, in practical application, a suitable second object may also be selected as a target object according to the matching degree through another selection strategy, which is not limited in this embodiment of the present specification, for example, every other second object is extracted as a target object through an interval extraction method.
After the target object is determined, the target object is displayed to the first object through the first object client of the first object, so that the first object can be selected and viewed at the first object client, namely, a job seeking user can select and view the target object through a job inviting user displayed by the client of the job seeking user. The specific implementation mode is as follows:
after determining at least one second object from the at least one second object as the target object according to the matching degree, the method further includes:
and displaying the target object to the first object through the first object client, and controlling the first object client to display an interactive interface for information interaction with the target object for the first object under the condition of receiving a selection instruction of the first object for the target object.
Wherein the interactive interface can be understood as a chat interface.
In practical application, the credit platform displays a target object to a first object through a first object client, the first object views and selects the target object at the client, and the credit platform controls the first object client to display an interactive interface for information interaction with the target object for the first object under the condition that a selection instruction of the first object for a certain target object is received.
In a specific scenario, the credit platform displays the determined invitation user at the client of the invitation user, the invitation user views the invitation user at the client (for example, views the invitation condition of the invitation user), and selects a suitable invitation user from the results to click. At the moment, under the condition that the credit platform receives a click instruction of a worker seeking user to a certain worker seeking user, the client of the worker seeking user is controlled to jump to a chat interface capable of chatting with the worker seeking user, so that the worker seeking user and the worker seeking user can know about each other more deeply through chatting, and the reasonability and the amount of successful work of the worker seeking user are increased.
After the first object and the target object are communicated or a real matching relationship is established (for example, a legal labor relationship is established between the job seeking user and the job seeking user), the first object and the target object can be evaluated for the other party according to the communication experience and the job seeking experience, for example, the job seeking user can evaluate the job seeking user, and the job seeking user can evaluate the job seeking user. The credit platform may increase or decrease the credit score of the first object or the target object on the credit platform according to the rating information of the first object and the target object. The specific implementation mode is as follows:
after determining at least one second object from the at least one second object as the target object according to the matching degree, the method further includes:
in the case of receiving evaluation information of the first object for the target object, increasing or decreasing a credit score of the target object according to the type of the evaluation information; or
And in the case of receiving the evaluation information of the target object for the first object, increasing or decreasing the credit score of the target object according to the type of the evaluation information.
In practical application, the evaluation information of the first object for the target object is divided into a positive evaluation (namely, a good evaluation) and a negative evaluation (namely, a bad evaluation), and in the case that the evaluation information of the first object for the target object is the positive evaluation, the credit score of the target object on a credit platform can be increased based on a preset scoring rule; and in the case that the evaluation information of the first object for the target object is negative evaluation, the credit score of the target object on the credit platform can be reduced for the target object based on the preset score reduction rule. The preset adding rule and the preset subtracting rule may be set according to practical application, and this specification does not limit this.
The evaluation information of the target object for the first object is divided into a positive evaluation (i.e. good evaluation) and a negative evaluation (i.e. bad evaluation), and in the case that the evaluation information of the target object for the first object is the positive evaluation, the credit score of the first object on the credit platform can be increased based on a preset adding rule; and in the case that the evaluation information of the target object for the first object is negative evaluation, the credit score of the first object on the credit platform can be reduced for the first object based on the preset score reduction rule. The preset adding rule and the preset subtracting rule may be set according to practical application, and this specification does not limit this.
In addition, during the specific implementation, the matching policy of the first object and the at least one second object may be updated according to the matching condition of the first object and the at least one second object, and then a more appropriate second object may be matched for the first object. The specific implementation mode is as follows:
and updating the matching strategy of the first object and the at least one second object according to the matching condition of the first object and the at least one second object.
Specifically, the matching condition of the first object and the at least one second object includes, but is not limited to, a matching degree, a matching number, evaluation information, and the like of the first object and each second object.
In practical application, the matching policy between the first object and at least one second object may be updated according to the matching degree between the first object and each second object. If the first object is a worker seeking user, the second object is a worker seeking user, and the worker seeking users with higher matching degree with the worker seeking users comprise a worker seeking user b1, wherein the attribute information of the worker seeking user is female, 45 years old and month-old certificate, the home address is a certain area in city A, the attribute information of the worker seeking user b1 is an enterprise, the company size is about 50, and the place is city A. At this time, it may be determined that the attribute information of the first object is the same as or similar to the attribute information of the aforementioned job finding user, and the matching success probability of the job finding user b1 is high, so that the second object that is the same as or similar to the attribute information of the job finding user b1 may be recommended to the first object when the first object performs the target object matching next time.
Through the mode, when the matching demand is more and more, the intelligent matching optimization upgrading can be realized, the occupation data can be accumulated by the blue collar, so that the recruitment user can better recruit people and the work seeking user can better find work, the matching between the recruitment user and the work seeking user is more and more appropriate, and the experience of both parties is improved.
The data processing method provided by the embodiment of the specification guarantees the authenticity and the safety of the first object and the second object based on the credit platform, and then intelligently matches the requirement for determining the target object by combining the attribute information of the first object and the attribute information of the second object, so that the requirement for determining the target object by the first object (for example, the requirement for a worker or the requirement for a worker) is met, and the user experience is improved.
The following will further describe the data processing method with reference to fig. 2 by taking an application of the data processing method provided in this specification in a job finding and recruitment scenario as an example. Fig. 2 shows a flowchart of a processing procedure of a data processing method according to an embodiment of the present specification, which specifically includes the following steps.
In particular, the data processing method applied to the job finding and recruitment scenario is applied to a credit platform, and the credit platform comprises a product side (namely a client) and an algorithm side (namely a server). The data processing method will be described in detail below.
Step 202: the client of the work seeking user receives the personal attribute information filled in by the work seeking user on the personal homepage of the client of the work seeking user to generate a data page, and the data page is uploaded to the server of the credit platform through the client of the work seeking user.
Step 204: the client of the inviting user receives the inviting user to fill in the enterprise attribute information on the inviting homepage of the client of the inviting user to generate a data page, and the data page is uploaded to the server of the credit platform through the client of the inviting user.
In specific implementation, the execution sequence between step 202 and step 204 is not limited at all.
Step 206: and the service end of the credit platform generates credit data according to the data pages uploaded by the work seeking user and the work inviting user.
The credit data includes, but is not limited to, personal data, professional information, behavioral data, and the like.
Step 208: the client side of the work seeking user or the work seeking user receives the keyword input by the work seeking user or the work seeking user in the search box of the search page of the client side of the work seeking user or the work seeking user, and uploads the keyword to the server side of the credit platform through the client side of the work seeking user or the work seeking user.
Step 210: and the server side of the credit platform recommends the worker seeking user to be matched with a proper worker seeking user to the matching square or recommends the worker seeking user to be matched with the proper worker seeking user to the matching square according to the keyword and the stored credit data of the worker seeking user and the worker seeking user.
Step 212: the matching square sends the worker seeking user matched with the worker seeking user to the client of the worker seeking user and displays the worker seeking user in a search list of a search page of the client; or sending the work seeking user matched with the work seeking user to the client of the work seeking user and displaying the work seeking user in a search list of a search page of the client.
Step 214: the client side of the worker seeking user jumps to a chat interface with the worker seeking user under the condition that the worker seeking user receives a control clicking instruction in a searching page of the client side of the worker seeking user; or the client of the job inviting user jumps to the chat interface with the job seeking user when receiving the click instruction of the job seeking user for accepting the control in the search page of the client.
Step 216: and the client of the work seeking user or the client of the work seeking user deposits the matching data which is successfully matched to the service end of the credit platform through the matching square.
The deposit data deposited to the service end of the credit platform includes, but is not limited to, matching times, evaluation of both parties, and the like.
Step 218: and the service end of the credit platform adjusts the matching strategy of the work seeking user and the work inviting user according to the precipitation data.
In the embodiment of the specification, a credit platform is adopted, and credit data and corresponding credit share guarantee are combined, so that high credibility of information can be achieved, and punishment can be performed on related illegal behaviors in a combined manner, so that behaviors of both an employee seeking user and an employee inviting user can be effectively restricted; the intelligent matching is carried out by combining the algorithm technology, and the high-efficiency matching and the deep fit of the requirements of the worker seeking user and the worker inviting user are carried out according to the requirements of the worker seeking user and the worker inviting user; the algorithm is combined with data, the high-growth performance is achieved, when the matching requirements are more and more, intelligent matching optimization upgrading can be realized, and the professional data can be accumulated by the blue collar. The workers are better and better to use, and the workers are better and better to find work.
Corresponding to the above method embodiment, this specification further provides a data processing apparatus embodiment, and fig. 3 shows a schematic structural diagram of a data processing apparatus provided in an embodiment of this specification. As shown in fig. 3, the apparatus is applied to a credit platform, and includes:
a request receiving module 302, configured to receive a target object search request sent by a first object, where the search request carries a search keyword;
a second object determination module 304 configured to determine attribute information of the first object according to the search request and determine at least one second object corresponding to the search keyword;
a matching module 306 configured to determine attribute information of the at least one second object, and obtain a matching degree between the first object and the at least one second object according to the attribute information of the first object and the attribute information of the at least one second object;
a target object determination module 308 configured to determine at least one second object from the at least one second object as the target object according to the matching degree;
wherein the first object and the at least one second object are both objects which complete attribute information registration at the credit platform.
Optionally, the matching module 306 is further configured to:
determining attribute information of each of the at least one second object;
and matching the attribute information of the first object with the attribute information of each second object to obtain the matching degree of the first object and each second object.
Optionally, the target object determination module 308 is configured to:
and performing descending order arrangement on the at least one second object according to the matching degree, and selecting a preset number of second objects as the target objects according to the sequence from large to small.
Optionally, the apparatus further comprises:
a registration module configured to:
receiving attribute information registered by a first object and attribute information registered by at least one second object;
wherein the attribute information of the first object is registered through a first object information registration page displayed by a first object client,
and the attribute information of the at least one second object is registered through a second object information registration page displayed by the second object client.
Optionally, the apparatus further comprises:
a credit score determination module configured to:
and allocating a corresponding credit score to the first object according to the attribute information of the first object, and allocating a corresponding credit score to the at least one second object according to the attribute information of the at least one second object.
Optionally, the second object determination module 304 is further configured to:
determining attribute information of the first object and a credit score of the first object according to the search request;
determining at least one second object corresponding to the search keyword if it is determined that the credit score of the first object is greater than or equal to a first score threshold.
Optionally, the matching module 306 is further configured to:
determining attribute information of the at least one second object and a credit score of the at least one second object;
under the condition that the credit score of the at least one second object is determined to be larger than or equal to a second score threshold value, the matching degree of the first object and the at least one second object is obtained according to the attribute information of the first object and the attribute information of the at least one second object.
Optionally, the apparatus further comprises:
a presentation module configured to:
and displaying the target object to the first object through the first object client, and controlling the first object client to display an interactive interface for information interaction with the target object for the first object under the condition of receiving a selection instruction of the first object for the target object.
Optionally, the apparatus further comprises:
a credit score adjustment module configured to:
in the case of receiving evaluation information of the first object for the target object, increasing or decreasing a credit score of the target object according to the type of the evaluation information; or
And in the case of receiving the evaluation information of the target object for the first object, increasing or decreasing the credit score of the target object according to the type of the evaluation information.
Optionally, the apparatus further comprises:
a policy adjustment module configured to:
and updating the matching strategy of the first object and the at least one second object according to the matching condition of the first object and the at least one second object.
The data processing device provided by the embodiment of the specification guarantees the authenticity and the safety of the first object and the second object based on the credit platform, and then intelligently matches the requirement for determining the target object by combining the attribute information of the first object and the attribute information of the second object, so that the requirement for determining the target object by the first object is met (for example, the requirement for a worker is met or the requirement for a worker is found), and the user experience is improved.
The above is a schematic configuration of a data processing apparatus of the present embodiment. It should be noted that the technical solution of the data processing apparatus and the technical solution of the data processing method belong to the same concept, and details that are not described in detail in the technical solution of the data processing apparatus can be referred to the description of the technical solution of the data processing method.
FIG. 4 illustrates a block diagram of a computing device 400 provided in accordance with one embodiment of the present description. The components of the computing device 400 include, but are not limited to, a memory 410 and a processor 420. Processor 420 is coupled to memory 410 via bus 430 and database 450 is used to store data.
Computing device 400 also includes access device 440, access device 440 enabling computing device 400 to communicate via one or more networks 460. Examples of such networks include the Public Switched Telephone Network (PSTN), a Local Area Network (LAN), a Wide Area Network (WAN), a Personal Area Network (PAN), or a combination of communication networks such as the internet. The access device 440 may include one or more of any type of network interface (e.g., a Network Interface Card (NIC)) whether wired or wireless, such as an IEEE802.11 Wireless Local Area Network (WLAN) wireless interface, a worldwide interoperability for microwave access (Wi-MAX) interface, an ethernet interface, a Universal Serial Bus (USB) interface, a cellular network interface, a bluetooth interface, a Near Field Communication (NFC) interface, and so forth.
In one embodiment of the present description, the above-described components of computing device 400, as well as other components not shown in FIG. 4, may also be connected to each other, such as by a bus. It should be understood that the block diagram of the computing device architecture shown in FIG. 4 is for purposes of example only and is not limiting as to the scope of the present description. Those skilled in the art may add or replace other components as desired.
Computing device 400 may be any type of stationary or mobile computing device, including a mobile computer or mobile computing device (e.g., tablet, personal digital assistant, laptop, notebook, netbook, etc.), mobile phone (e.g., smartphone), wearable computing device (e.g., smartwatch, smartglasses, etc.), or other type of mobile device, or a stationary computing device such as a desktop computer or PC. Computing device 400 may also be a mobile or stationary server.
Wherein the processor 420 is configured to execute computer-executable instructions that, when executed by the processor, implement the steps of the data processing method described above.
The above is an illustrative scheme of a computing device of the present embodiment. It should be noted that the technical solution of the computing device and the technical solution of the data processing method belong to the same concept, and details that are not described in detail in the technical solution of the computing device can be referred to the description of the technical solution of the data processing method.
An embodiment of the present specification also provides a computer-readable storage medium storing computer-executable instructions that, when executed by a processor, implement the steps of the data processing method described above.
The above is an illustrative scheme of a computer-readable storage medium of the present embodiment. It should be noted that the technical solution of the storage medium belongs to the same concept as the technical solution of the data processing method, and details that are not described in detail in the technical solution of the storage medium can be referred to the description of the technical solution of the data processing method.
An embodiment of the present specification further provides a computer program, wherein when the computer program is executed in a computer, the computer is caused to execute the steps of the data processing method.
The above is an illustrative scheme of a computer program of the present embodiment. It should be noted that the technical solution of the computer program and the technical solution of the data processing method belong to the same concept, and details that are not described in detail in the technical solution of the computer program can be referred to the description of the technical solution of the data processing method.
The foregoing description has been directed to specific embodiments of this disclosure. Other embodiments are within the scope of the following claims. In some cases, the actions or steps recited in the claims may be performed in a different order than in the embodiments and still achieve desirable results. In addition, the processes depicted in the accompanying figures do not necessarily require the particular order shown, or sequential order, to achieve desirable results. In some embodiments, multitasking and parallel processing may also be possible or may be advantageous.
The computer instructions comprise computer program code which may be in the form of source code, object code, an executable file or some intermediate form, or the like. The computer-readable medium may include: any entity or device capable of carrying the computer program code, recording medium, usb disk, removable hard disk, magnetic disk, optical disk, computer memory, Read-only memory (ROM), Random Access Memory (RAM), electrical carrier wave signals, telecommunications signals, software distribution medium, etc. It should be noted that the computer readable medium may contain content that is subject to appropriate increase or decrease as required by legislation and patent practice in jurisdictions, for example, in some jurisdictions, computer readable media does not include electrical carrier signals and telecommunications signals as is required by legislation and patent practice.
It should be noted that, for the sake of simplicity, the foregoing method embodiments are described as a series of acts, but those skilled in the art should understand that the present embodiment is not limited by the described acts, because some steps may be performed in other sequences or simultaneously according to the present embodiment. Further, those skilled in the art should also appreciate that the embodiments described in this specification are preferred embodiments and that acts and modules referred to are not necessarily required for an embodiment of the specification.
In the above embodiments, the descriptions of the respective embodiments have respective emphasis, and for parts that are not described in detail in a certain embodiment, reference may be made to related descriptions of other embodiments.
The preferred embodiments of the present specification disclosed above are intended only to aid in the description of the specification. Alternative embodiments are not exhaustive and do not limit the invention to the precise embodiments described. Obviously, many modifications and variations are possible in light of the above teaching. The embodiments were chosen and described in order to best explain the principles of the embodiments and the practical application, to thereby enable others skilled in the art to best understand and utilize the embodiments. The specification is limited only by the claims and their full scope and equivalents.
Claims (14)
1. A data processing method applied to a credit platform comprises the following steps:
receiving a target object search request sent by a first object, wherein the search request carries a search keyword;
determining attribute information of the first object according to the search request, and determining at least one second object corresponding to the search keyword;
determining attribute information of the at least one second object, and obtaining the matching degree of the first object and the at least one second object according to the attribute information of the first object and the attribute information of the at least one second object;
determining at least one second object from the at least one second object as the target object according to the matching degree;
wherein the first object and the at least one second object are both objects which complete attribute information registration at the credit platform.
2. The data processing method according to claim 1, wherein the determining attribute information of the at least one second object and obtaining a matching degree between the first object and the at least one second object according to the attribute information of the first object and the attribute information of the at least one second object comprises:
determining attribute information of each of the at least one second object;
and matching the attribute information of the first object with the attribute information of each second object to obtain the matching degree of the first object and each second object.
3. The data processing method according to claim 1 or 2, wherein the determining at least one second object from the at least one second object as the target object according to the matching degree comprises:
and performing descending order arrangement on the at least one second object according to the matching degree, and selecting a preset number of second objects as the target objects according to the sequence from large to small.
4. The data processing method according to claim 1, before receiving the target object search request sent by the first object, further comprising:
receiving attribute information registered by a first object and attribute information registered by at least one second object;
wherein the attribute information of the first object is registered through a first object information registration page displayed by a first object client,
and the attribute information of the at least one second object is registered through a second object information registration page displayed by the second object client.
5. The data processing method of claim 4, after receiving the attribute information of the first object registration and the attribute information of the at least one second object registration, further comprising:
and allocating a corresponding credit score to the first object according to the attribute information of the first object, and allocating a corresponding credit score to the at least one second object according to the attribute information of the at least one second object.
6. The data processing method of claim 5, the determining attribute information of the first object according to the search request and determining at least one second object corresponding to the search keyword, comprising:
determining attribute information of the first object and a credit score of the first object according to the search request;
determining at least one second object corresponding to the search keyword if it is determined that the credit score of the first object is greater than or equal to a first score threshold.
7. The data processing method according to claim 6, wherein the determining attribute information of the at least one second object and obtaining a matching degree between the first object and the at least one second object according to the attribute information of the first object and the attribute information of the at least one second object comprises:
determining attribute information of the at least one second object and a credit score of the at least one second object;
under the condition that the credit score of the at least one second object is determined to be larger than or equal to a second score threshold value, the matching degree of the first object and the at least one second object is obtained according to the attribute information of the first object and the attribute information of the at least one second object.
8. The data processing method according to claim 1, after determining at least one second object from the at least one second object as the target object according to the matching degree, further comprising:
and displaying the target object to the first object through the first object client, and controlling the first object client to display an interactive interface for information interaction with the target object for the first object under the condition of receiving a selection instruction of the first object for the target object.
9. The data processing method of claim 5, after determining at least one second object from the at least one second object as the target object according to the matching degree, further comprising:
in the case of receiving evaluation information of the first object for the target object, increasing or decreasing a credit score of the target object according to the type of the evaluation information; or
And in the case of receiving the evaluation information of the target object for the first object, increasing or decreasing the credit score of the target object according to the type of the evaluation information.
10. The data processing method of claim 1, further comprising:
and updating the matching strategy of the first object and the at least one second object according to the matching condition of the first object and the at least one second object.
11. A data processing device applied to a credit platform comprises:
the device comprises a request receiving module, a searching module and a searching module, wherein the request receiving module is configured to receive a target object searching request sent by a first object, and the searching request carries a searching keyword;
a second object determination module configured to determine attribute information of the first object according to the search request and determine at least one second object corresponding to the search keyword;
the matching module is configured to determine attribute information of the at least one second object and obtain a matching degree of the first object and the at least one second object according to the attribute information of the first object and the attribute information of the at least one second object;
a target object determination module configured to determine at least one second object from the at least one second object as the target object according to the matching degree;
wherein the first object and the at least one second object are both objects which complete attribute information registration at the credit platform.
12. A computing device, comprising:
a memory and a processor;
the memory is for storing computer-executable instructions and the processor is for executing the computer-executable instructions, which when executed by the processor implement the steps of the data processing method of any one of claims 1 to 10.
13. A computer-readable storage medium storing computer-executable instructions which, when executed by a processor, implement the steps of the data processing method of any one of claims 1 to 10.
14. A computer program for causing a computer to carry out the steps of the data processing method according to any one of claims 1 to 10 when the computer program is carried out in the computer.
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Cited By (1)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN116431319A (en) * | 2023-06-14 | 2023-07-14 | 云阵(杭州)互联网技术有限公司 | Task processing method and device |
Citations (5)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN104166893A (en) * | 2014-07-22 | 2014-11-26 | 钱存稳 | Cloud integrated talent management system and method |
| CN109993442A (en) * | 2019-04-03 | 2019-07-09 | 四川隧唐科技股份有限公司 | A kind of outstanding labor service selection artificial intelligence system |
| CN111553788A (en) * | 2020-04-28 | 2020-08-18 | 好活（昆山）网络科技有限公司 | Capital business processing method and device based on big data, electronic equipment and medium |
| CN111985992A (en) * | 2019-07-31 | 2020-11-24 | 创新先进技术有限公司 | Credit contract processing method and device |
| CN113393204A (en) * | 2021-05-26 | 2021-09-14 | 苏州市企淘网络科技有限公司 | Talent sharing platform based on scene |
-
2021
- 2021-10-12 CN CN202111187833.XA patent/CN113935616A/en active Pending
Patent Citations (5)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN104166893A (en) * | 2014-07-22 | 2014-11-26 | 钱存稳 | Cloud integrated talent management system and method |
| CN109993442A (en) * | 2019-04-03 | 2019-07-09 | 四川隧唐科技股份有限公司 | A kind of outstanding labor service selection artificial intelligence system |
| CN111985992A (en) * | 2019-07-31 | 2020-11-24 | 创新先进技术有限公司 | Credit contract processing method and device |
| CN111553788A (en) * | 2020-04-28 | 2020-08-18 | 好活（昆山）网络科技有限公司 | Capital business processing method and device based on big data, electronic equipment and medium |
| CN113393204A (en) * | 2021-05-26 | 2021-09-14 | 苏州市企淘网络科技有限公司 | Talent sharing platform based on scene |
Cited By (2)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN116431319A (en) * | 2023-06-14 | 2023-07-14 | 云阵(杭州)互联网技术有限公司 | Task processing method and device |
| CN116431319B (en) * | 2023-06-14 | 2023-09-12 | 云阵(杭州)互联网技术有限公司 | Task processing method and device |
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