CN110472834B - Course pushing method, course pushing device, storage medium and server - Google Patents
Course pushing method, course pushing device, storage medium and server Download PDFInfo
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- 238000000034 method Methods 0.000 title claims abstract description 36
- 238000011161 development Methods 0.000 claims abstract description 104
- 238000012549 training Methods 0.000 claims abstract description 34
- 230000008569 process Effects 0.000 claims description 7
- 238000003062 neural network model Methods 0.000 claims description 5
- 238000004364 calculation method Methods 0.000 claims description 2
- 230000000694 effects Effects 0.000 abstract description 8
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Classifications
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- G—PHYSICS
- G06—COMPUTING; CALCULATING OR COUNTING
- G06Q—INFORMATION AND COMMUNICATION TECHNOLOGY [ICT] SPECIALLY ADAPTED FOR ADMINISTRATIVE, COMMERCIAL, FINANCIAL, MANAGERIAL OR SUPERVISORY PURPOSES; SYSTEMS OR METHODS SPECIALLY ADAPTED FOR ADMINISTRATIVE, COMMERCIAL, FINANCIAL, MANAGERIAL OR SUPERVISORY PURPOSES, NOT OTHERWISE PROVIDED FOR
- G06Q10/00—Administration; Management
- G06Q10/06—Resources, workflows, human or project management; Enterprise or organisation planning; Enterprise or organisation modelling
- G06Q10/063—Operations research, analysis or management
- G06Q10/0639—Performance analysis of employees; Performance analysis of enterprise or organisation operations
- G06Q10/06393—Score-carding, benchmarking or key performance indicator [KPI] analysis
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- G—PHYSICS
- G06—COMPUTING; CALCULATING OR COUNTING
- G06Q—INFORMATION AND COMMUNICATION TECHNOLOGY [ICT] SPECIALLY ADAPTED FOR ADMINISTRATIVE, COMMERCIAL, FINANCIAL, MANAGERIAL OR SUPERVISORY PURPOSES; SYSTEMS OR METHODS SPECIALLY ADAPTED FOR ADMINISTRATIVE, COMMERCIAL, FINANCIAL, MANAGERIAL OR SUPERVISORY PURPOSES, NOT OTHERWISE PROVIDED FOR
- G06Q10/00—Administration; Management
- G06Q10/06—Resources, workflows, human or project management; Enterprise or organisation planning; Enterprise or organisation modelling
- G06Q10/063—Operations research, analysis or management
- G06Q10/0639—Performance analysis of employees; Performance analysis of enterprise or organisation operations
- G06Q10/06398—Performance of employee with respect to a job function
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- G—PHYSICS
- G06—COMPUTING; CALCULATING OR COUNTING
- G06Q—INFORMATION AND COMMUNICATION TECHNOLOGY [ICT] SPECIALLY ADAPTED FOR ADMINISTRATIVE, COMMERCIAL, FINANCIAL, MANAGERIAL OR SUPERVISORY PURPOSES; SYSTEMS OR METHODS SPECIALLY ADAPTED FOR ADMINISTRATIVE, COMMERCIAL, FINANCIAL, MANAGERIAL OR SUPERVISORY PURPOSES, NOT OTHERWISE PROVIDED FOR
- G06Q50/00—Systems or methods specially adapted for specific business sectors, e.g. utilities or tourism
- G06Q50/10—Services
- G06Q50/20—Education
- G06Q50/205—Education administration or guidance
- G06Q50/2057—Career enhancement or continuing education service
Abstract
The invention relates to the technical field of computers, and provides a method, a device, a storage medium and a server for pushing courses. The invention constructs a plurality of user portrait models in advance, each user portrait model corresponds to one professional development type, and the professional development type of the user can be determined according to the output result of each user portrait model by inputting the personal information of the user into the user portrait models; and then selecting a capacity item scoring model corresponding to the professional development type, calculating the score of each capacity item of the user by using the scoring model, and finding out the capacity item with the lowest score according to the score, namely the capacity item short board of the user, so that courses related to the capacity item short board can be pushed in a targeted manner, and the training effect is improved.
Description
Technical Field
The present invention relates to the field of computer technologies, and in particular, to a method, an apparatus, a storage medium, and a server for pushing courses.
Background
In order to improve the skill level of staff, many enterprises develop training courses from time to time, and the staff are required to participate uniformly or selectively according to own requirements. However, because individual characteristics of each employee are different, and the positioning of the employee to the own capability item long and short board is not clear in many times, the two modes can not accurately push proper courses for the employee, so that the training effect is poor.
Disclosure of Invention
In view of the above, the embodiments of the present invention provide a method, an apparatus, a storage medium, and a server for pushing courses, which can locate capability item short-short boards of each user, so as to push courses in a targeted manner, thereby improving training effects.
In a first aspect of an embodiment of the present invention, a method for pushing a course is provided, including:
acquiring personal information of a user;
the personal information is respectively input into a plurality of pre-constructed user portrait models, the professional development types of the users are determined according to the output results of the user portrait models, each user portrait model corresponds to one professional development type, and the user portrait model is obtained by training personal information of a plurality of sample users corresponding to the professional development types as a training set;
selecting a capacity item scoring model corresponding to the professional development type of the user;
respectively calculating the scores of all the capability items of the user by combining the selected capability item scoring model and the personal information, wherein the capability items refer to all the working capability index items constructed in advance;
determining the capacity items with the lowest scores and the preset quantity as capacity item short plates of the users;
pushing courses associated with the capability item shortboards to the user.
In a second aspect of the embodiment of the present invention, there is provided a device for pushing a course, including:
the personal information acquisition module is used for acquiring personal information of a user;
the professional development type determining module is used for respectively inputting the personal information into a plurality of pre-constructed user portrait models, determining the professional development type of the user according to the output result of each user portrait model, wherein each user portrait model corresponds to one professional development type, and the user portrait model is obtained by training the personal information of a plurality of sample users corresponding to the professional development type as a training set;
the ability item scoring model selecting module is used for selecting an ability item scoring model corresponding to the professional development type of the user;
the capacity item scoring module is used for respectively calculating the scores of all the capacity items of the user by combining the selected capacity item scoring model and the personal information, wherein the capacity items refer to all the working capacity index items constructed in advance;
the capacity item short board determining module is used for determining the capacity items with the lowest scores and the preset quantity as the capacity item short boards of the users;
and the course pushing module is used for pushing courses associated with the capability item short board to the user.
In a third aspect of the embodiments of the present invention, there is provided a computer-readable storage medium storing computer-readable instructions that, when executed by a processor, implement the steps of a method of pushing a lesson as set forth in the first aspect of the embodiments of the present invention.
In a fourth aspect of the embodiments of the present invention, there is provided a server comprising a memory, a processor and computer readable instructions stored in the memory and executable on the processor, the processor implementing the steps of the method for pushing courses as set forth in the first aspect of the embodiments of the present invention when the processor executes the computer readable instructions.
The method comprises the steps that a plurality of user portrait models are built in advance, each user portrait model corresponds to one professional development type, personal information of a user is input into the user portrait models, and the professional development type of the user can be determined according to output results of the user portrait models; and then selecting a capacity item scoring model corresponding to the professional development type, calculating the score of each capacity item of the user by using the scoring model, and finding out the capacity item with the lowest score according to the score, namely the capacity item short board of the user, so that courses related to the capacity item short board can be pushed in a targeted manner, and the training effect is improved.
Drawings
In order to more clearly illustrate the technical solutions of the embodiments of the present invention, the drawings that are needed in the embodiments or the description of the prior art will be briefly described below, it being obvious that the drawings in the following description are only some embodiments of the present invention, and that other drawings may be obtained according to these drawings without inventive effort for a person skilled in the art.
FIG. 1 is a flow chart of a first embodiment of a method for pushing a lesson provided in accordance with an embodiment of the present invention;
FIG. 2 is a flow chart of a second embodiment of a method for pushing a lesson provided in accordance with an embodiment of the present invention;
FIG. 3 is a flow chart of a third embodiment of a method for pushing a lesson provided in accordance with an embodiment of the present invention;
FIG. 4 is a block diagram of one embodiment of an apparatus for pushing lessons provided in accordance with an embodiment of the present invention;
fig. 5 is a schematic diagram of a server according to an embodiment of the present invention.
Detailed Description
The embodiment of the invention provides a method, a device, a storage medium and a server for pushing courses, which can locate the advantages and disadvantages of each user, so that the courses can be pushed in a targeted manner, and the training effect is improved.
In order to make the objects, features and advantages of the present invention more comprehensible, the technical solutions in the embodiments of the present invention are described in detail below with reference to the accompanying drawings, and it is apparent that the embodiments described below are only some embodiments of the present invention, but not all embodiments of the present invention. All other embodiments, which can be made by those skilled in the art based on the embodiments of the invention without making any inventive effort, are intended to be within the scope of the invention.
Referring to fig. 1, a first embodiment of a method for pushing courses according to an embodiment of the present invention includes:
101. acquiring personal information of a user;
first, personal information of the user is acquired, which may include, but is not limited to: basic information (such as name, gender, age, etc.), family information, performance information, attendance information, and customer resource information. Specifically, a course pushing system can be constructed, on one hand, the personal information of the user can be input into the system by related personnel (such as the user or a manager who develops training); on the other hand, the personal information of the user can be called through a human archive system of a docking enterprise.
102. The personal information is respectively input into a plurality of user portrait models constructed in advance, and the professional development type of the user is determined according to the output result of each user portrait model;
after personal information of the user is obtained, the personal information can be respectively input into a plurality of pre-constructed user portrait models, the professional development type of the user is determined according to the output result of each portrait model, each portrait model corresponds to one professional development type, and the user portrait model is obtained by training the personal information of a plurality of sample users corresponding to the professional development type as a training set.
Specifically, each portrait model outputs a similarity result, and the professional development type corresponding to the portrait model with the highest similarity result is determined as the professional development type of the user. For example, for 5 professional development types of the salesmen, a portrait model is respectively constructed for each of the 5 professional development types, personal information of the user is respectively input into the 5 portrait models, each portrait model outputs a result of similarity, and if the result is the resource type-90%, the social type-75%, the service type-60%, the sales type-30% and the comprehensive type-20%, the professional development type of the user can be determined to be the resource type with the highest similarity. Wherein, a certain portrait model is completed by personal information training of a plurality of sample users collected in advance. For example, the resource-type portrait model is trained by using personal information of a plurality of users (for example, 10000 users) defined as resource types, which are collected in advance, as a training set. The social portrait model is trained by using personal information of a plurality of users (for example, 10000 users) defined as social users collected in advance as a training set.
103. Selecting a capacity item scoring model corresponding to the professional development type of the user;
after determining the type of professional development of the user, a competence scoring model corresponding to the type of professional development is selected. The capability items refer to various pre-constructed capability index items, such as capability of making targets, capability of executing plans, capability of making books, capability of product combination sales, and the like. The capability item scoring model can be used for calculating by combining personal information of the user to obtain scores of all the capability items of the user. And aiming at users with different professional development types, respectively adopting different ability item scoring models to calculate scoring values.
104. Respectively calculating the scores of all the capability items of the user by combining the selected capability item scoring model and the personal information, wherein the capability items refer to all the working capability index items constructed in advance;
and then, respectively calculating the scores of the individual capability items of the user by combining the selected capability item scoring model and the personal information.
Further, if the capability item scoring model corresponding to the professional development type of the user is not selected, the score of any target capability item of the user can be determined by the following steps:
(1) Extracting a target value of partial information related to the target capability item from the personal information;
(2) And comparing the target value with each grading reference value corresponding to the target capacity item, and determining the grading of the target capacity item according to the comparison result.
For example, for a certain capability item-product combination sales capability, the sales performance amount of the product is extracted from the personal information of the user as a target value; and comparing the target value with each preset scoring reference value, for example, 100 scores correspond to 30 ten thousand achievements, 90 scores correspond to 20 ten thousand achievements, 60 scores correspond to 5 ten thousand achievements, and if the target value is 20 ten thousand, the score of the capability item is 90.
Specifically, the score of any one target capability item of the user may be determined by the following steps:
(1) Selecting a target scoring model corresponding to the target capability item, wherein the target scoring model is a neural network model obtained by training a training set by using personal information of a plurality of sample users with scores of the target capability item as reference values;
(2) And inputting the personal information of the user into the target scoring model, and determining the score of the target ability item according to the output result of the target scoring model.
For example, for the capability of a certain capability item-product combination sales, personal information of a plurality of sample users with the capability item as a certain scoring standard (such as 100 minutes) can be obtained as a training set, and a neural network model is constructed; and inputting the personal information of the user into the neural network model to obtain an output result of the matching degree, and finally determining the score of the ability item according to the matching degree. For example, a score of 100 is greater than or equal to 90%, a score of 90 is greater than or equal to 80%, a score of 70 is greater than or equal to 60%, and so on.
105. Determining the capacity items with the lowest scores and the preset quantity as capacity item short plates of the users;
106. pushing courses associated with the capability item shortboards to the user.
And finally, searching the capacity items with the lowest scores of the users and a preset number (such as 2 items) as capacity item shortboards of the users, pushing courses associated with the capacity shortboards for the users, and constructing corresponding relations between each capacity item and each course in advance by a system.
According to the embodiment of the invention, a plurality of user portrait models are pre-built, each user portrait model corresponds to one professional development type, personal information of a user is input into the user portrait models, and the professional development type of the user can be determined according to the output result of each user portrait model; and then selecting a capacity item scoring model corresponding to the professional development type, calculating the score of each capacity item of the user by using the scoring model, and finding out the capacity item with the lowest score according to the score, namely the capacity item short board of the user, so that courses related to the capacity item short board can be pushed in a targeted manner, and the training effect is improved.
Referring to fig. 2, a second embodiment of a method for pushing courses according to the embodiments of the present invention includes:
201. acquiring personal information of a user;
step 210 is the same as step 101, and reference is specifically made to the description related to step 101.
202. Querying a working team on which the user is located;
203. respectively counting the professional development types corresponding to the personnel with the determined professional development types in the working team;
204. respectively counting the number ratio of the number of people in the working team corresponding to each occupational development type relative to the total number of people in the working team;
205. sequentially arranging the user portrait models corresponding to the professional development types according to the order of the number proportion of the corresponding professional development types from high to low;
206. sequentially inputting the personal information into the arranged user portrait models;
in addition, in the process of sequentially inputting the personal information into each user portrait model after arrangement, if the matching degree output by any one user portrait model exceeds a preset threshold (for example, 90%), the personal information is stopped from being input into the next user portrait model, and the professional development type corresponding to the portrait model is determined as the professional development type of the user.
For steps 202-206, the following is illustrated: suppose that the user is in sales team A, which contains 130 users, 100 of whom have completed the category of professional development types. If 60 users belonging to the resource type, 30 users belonging to the social type and 10 users belonging to the diligence type are classified into 100 classified users, when personal information of the users is input into each portrait model, the 3 portrait models are arranged in order of the resource type-the social type-the diligence type, namely, the portrait model of the priority input resource type is arranged. Users in the same working team have a certain assimilation property and more or less similar professional development types, and the portrait model which is matched with the maximum probability can be preferentially matched in the mode, so that classification of the users is completed rapidly.
207. Determining the professional development type of the user according to the output result of each user portrait model;
208. selecting a capacity item scoring model corresponding to the professional development type of the user;
209. respectively calculating the scores of all the capability items of the user by combining the selected capability item scoring model and the personal information, wherein the capability items refer to all the working capability index items constructed in advance;
210. determining the capacity items with the lowest scores and the preset quantity as capacity item short plates of the users;
211. pushing courses associated with the capability item shortboards to the user.
Steps 207-211 are identical to steps 102-106 and reference is made specifically to the description of steps 102-106.
According to the embodiment of the invention, a plurality of user portrait models are pre-built, each user portrait model corresponds to one professional development type, personal information of a user is input into the user portrait models, and the professional development type of the user can be determined according to the output result of each user portrait model; and then selecting a capacity item scoring model corresponding to the professional development type, calculating the score of each capacity item of the user by using the scoring model, and finding out the capacity item with the lowest score according to the score, namely the capacity item short board of the user, so that courses related to the capacity item short board can be pushed in a targeted manner, and the training effect is improved. In addition, the embodiment also counts the occupational development types of all the staff of the working team where the user is located, counts the number proportion of the staff in the working team of each occupational development type respectively, sequentially arranges all the user portrait models according to the order of the number proportion of the corresponding occupational development types from high to low, and sequentially inputs the personal information into all the arranged user portrait models. By the arrangement, portrait models which are matched with the maximum probability can be matched with each other preferentially, so that classification of users can be completed rapidly.
Referring to fig. 3, a second embodiment of a method for pushing courses according to the embodiments of the present invention includes:
301. acquiring personal information of a user;
302. the personal information is respectively input into a plurality of user portrait models constructed in advance, and the professional development type of the user is determined according to the output result of each user portrait model;
303. selecting a capacity item scoring model corresponding to the professional development type of the user;
304. respectively calculating the scores of all the capability items of the user by combining the selected capability item scoring model and the personal information, wherein the capability items refer to all the working capability index items constructed in advance;
305. determining the capacity items with the lowest scores and the preset quantity as capacity item short plates of the users;
306. pushing courses associated with the capability item shortboards to the user;
steps 301-306 are identical to steps 101-106, and reference is made specifically to the description of steps 101-106.
307. Updating the personal information of the user every first period, and then recalculating the scores of all the capability items of the user by combining the capability item scoring model and the updated personal information;
because the personal information of the user is continuously updated, in order to improve the accuracy of the capability item score, the personal information of the user can be updated every other first period, then the score of each capability item of the user is recalculated by combining the capability item score model and the updated personal information, and further the capability item short board of the user is redetermined, and the corresponding course is pushed. In practical applications, the first period may be set to 1 month or 1 quarter.
308. And updating the personal information of the user every second period, then respectively inputting the updated personal information into the plurality of user portrait models, and redefining the occupational development type of the user, wherein the second period is larger than the first period.
Similarly, the type of professional development of the user may also change over time, so that the personal information of the user may be updated every second period, and then the updated personal information is respectively input into the plurality of user portrait models to redetermine the type of professional development of the user. If the professional development type is changed, calculating the score of each capability item of the user again by adopting a capability item scoring model corresponding to the changed professional development type, and then determining a capability item short board and pushing a corresponding course. In practical applications, the second period may be set to half a year or 1 year.
According to the embodiment of the invention, a plurality of user portrait models are pre-built, each user portrait model corresponds to one professional development type, personal information of a user is input into the user portrait models, and the professional development type of the user can be determined according to the output result of each user portrait model; and then selecting a capacity item scoring model corresponding to the professional development type, calculating the score of each capacity item of the user by using the scoring model, and finding out the capacity item with the lowest score according to the score, namely the capacity item short board of the user, so that courses related to the capacity item short board can be pushed in a targeted manner, and the training effect is improved. In addition, the personal information of the user is updated regularly, and the professional development type of the user is re-estimated and the capability items of the user are re-scored by combining the updated personal information, so that the accuracy of course pushing is further improved.
It should be understood that the sequence number of each step in the foregoing embodiment does not mean that the execution sequence of each process should be determined by the function and the internal logic, and should not limit the implementation process of the embodiment of the present invention.
The foregoing generally describes a method for pushing a lesson, and a detailed description of an apparatus for pushing a lesson will be provided.
Referring to fig. 4, an embodiment of an apparatus for pushing courses according to the present invention includes:
a personal information acquisition module 401, configured to acquire personal information of a user;
the professional development type determining module 402 is configured to input the personal information into a plurality of pre-constructed user portrait models respectively, determine the professional development type of the user according to the output result of each user portrait model, where each user portrait model corresponds to one professional development type, and the user portrait model is obtained by training personal information of a plurality of sample users corresponding to the professional development type as a training set;
a capability item scoring model selection module 403, configured to select a capability item scoring model corresponding to a professional development type of the user;
the capability item scoring module 404 is configured to calculate scores of each capability item of the user respectively in combination with the selected capability item scoring model and the personal information, where the capability item refers to each pre-constructed working capability index item;
a capability item short board determination module 405, configured to determine a preset number of capability items with the lowest scores as capability item short boards of the user;
and a course pushing module 406, configured to push, to the user, a course associated with the capability item shortboard.
Further, the job development type determining module may include:
the work team inquiring unit is used for inquiring the work team where the user is located;
the personnel type determining unit is used for respectively counting the professional development types corresponding to the personnel with the determined professional development types in the working team;
the staff number counting unit is used for counting the number ratio of the staff number in the working team corresponding to each professional development type relative to the total number of staff in the working team respectively;
the model ordering unit is used for sequentially ordering the user portrait models corresponding to the professional development types according to the order of the number proportion of the corresponding professional development types from high to low;
a personal information input unit for inputting the personal information into each of the user portrait models after being arranged in sequence;
and the calculation stopping unit is used for stopping inputting the personal information into the next user portrait model if the matching degree output by any user portrait model exceeds a preset threshold value in the process of inputting the personal information into the arranged user portrait models in sequence.
Further, the capability item scoring module may include:
a target value extraction unit configured to extract a target value of partial information related to the target capability item from the personal information;
and the target value comparison unit is used for comparing the target value with each score reference value corresponding to the target capacity item and determining the score of the target capacity item according to the comparison result.
Further, the capability item scoring module may include:
a model selecting unit, configured to select a target scoring model corresponding to the target capability item, where the target scoring model is a neural network model obtained by training a training set by using personal information of a plurality of sample users whose scores of the target capability item are reference values;
and the scoring unit is used for inputting the personal information of the user into the target scoring model and determining the score of the target capability item according to the output result of the target scoring model.
Further, the device for pushing courses may further include:
the first updating module is used for updating the personal information of the user at intervals of a first period, and then recalculating the scores of all the capability items of the user by combining the capability item scoring model and the updated personal information;
and the second updating module is used for updating the personal information of the user at intervals of a second period, then respectively inputting the updated personal information into the plurality of user portrait models, and redefining the occupational development type of the user, wherein the second period is larger than the first period.
Embodiments of the present invention also provide a computer-readable storage medium storing computer-readable instructions that, when executed by a processor, implement the steps of any one of the methods of pushing lessons as represented in fig. 1-3.
The embodiment of the invention also provides a server, which comprises a memory, a processor and computer readable instructions stored in the memory and capable of running on the processor, wherein the steps of any one of the methods for pushing courses shown in fig. 1 to 3 are realized when the processor executes the computer readable instructions.
Fig. 5 is a schematic diagram of a server according to an embodiment of the present invention. As shown in fig. 5, the server 5 of this embodiment includes: a processor 50, a memory 51, and computer readable instructions 52 stored in the memory 51 and executable on the processor 50. The processor 50, when executing the computer readable instructions 52, implements the steps of the method embodiments of the push lessons described above, such as steps 101 through 106 shown in fig. 1. Alternatively, the processor 50, when executing the computer readable instructions 52, performs the functions of the modules/units of the apparatus embodiments described above, such as the functions of modules 401 through 406 shown in fig. 4.
Illustratively, the computer readable instructions 52 may be partitioned into one or more modules/units that are stored in the memory 51 and executed by the processor 50 to accomplish the present invention. The one or more modules/units may be a series of computer readable instruction segments capable of performing a specific function describing the execution of the computer readable instructions 52 in the server 5.
The server 5 may be a computing device such as a smart phone, a notebook, a palm computer, a cloud server, etc. The server 5 may include, but is not limited to, a processor 50, a memory 51. It will be appreciated by those skilled in the art that fig. 5 is merely an example of the server 5 and is not meant to be limiting of the server 5, and may include more or fewer components than shown, or may combine certain components, or different components, e.g., the server 5 may also include input and output devices, network access devices, buses, etc.
The processor 50 may be a central processing unit (CentraL Processing Unit, CPU), but may also be other general purpose processors, digital signal processors (DigitaL SignaL Processor, DSP), application specific integrated circuits (AppLication Specific Integrated Circuit, ASIC), off-the-shelf programmable gate arrays (fierld-ProgrammabLe Gate Array, FPGA) or other programmable logic devices, discrete gate or transistor logic devices, discrete hardware components, or the like. A general purpose processor may be a microprocessor or the processor may be any conventional processor or the like.
The storage 51 may be an internal storage unit of the server 5, for example, a hard disk or a memory of the server 5. The memory 51 may be an external storage device of the server 4, such as a plug-in hard disk, a Smart Media Card (SMC), a Secure DigitaL (SD) Card, a FLash Card (FLash Card) or the like, which are provided on the server 5. Further, the memory 51 may also include both an internal storage unit and an external storage device of the server 5. The memory 51 is used to store the computer readable instructions and other programs and data required by the server. The memory 51 may also be used to temporarily store data that has been output or is to be output.
It will be clear to those skilled in the art that, for convenience and brevity of description, specific working procedures of the above-described systems, apparatuses and units may refer to corresponding procedures in the foregoing method embodiments, which are not repeated herein.
In addition, each functional unit in the embodiments of the present invention may be integrated in one processing unit, or each unit may exist alone physically, or two or more units may be integrated in one unit. The integrated units may be implemented in hardware or in software functional units.
The integrated units, if implemented in the form of software functional units and sold or used as stand-alone products, may be stored in a computer readable storage medium. Based on such understanding, the technical solution of the present invention may be embodied essentially or in part or all of the technical solution or in part in the form of a software product stored in a storage medium, including instructions for causing a computer device (which may be a personal computer, a server, or a network device, etc.) to perform all or part of the steps of the method according to the embodiments of the present invention. And the aforementioned storage medium includes: a usb disk, a removable hard disk, a Read-OnLy Memory (ROM), a random access Memory (RAM, random Access Memory), a magnetic disk, or an optical disk, or other various media capable of storing program codes.
The above embodiments are only for illustrating the technical solution of the present invention, and not for limiting the same; although the invention has been described in detail with reference to the foregoing embodiments, it will be understood by those of ordinary skill in the art that: the technical scheme described in the foregoing embodiments can be modified or some technical features thereof can be replaced by equivalents; such modifications and substitutions do not depart from the spirit and scope of the technical solutions of the embodiments of the present invention.
Claims (8)
1. A method of pushing a lesson, comprising:
acquiring personal information of a user;
the personal information is respectively input into a plurality of pre-constructed user portrait models, the professional development types of the users are determined according to the output results of the user portrait models, each user portrait model corresponds to one professional development type, and the user portrait model is obtained by training personal information of a plurality of sample users corresponding to the professional development types as a training set;
selecting a capacity item scoring model corresponding to the professional development type of the user;
respectively calculating the scores of all the capability items of the user by combining the selected capability item scoring model and the personal information, wherein the capability items refer to all the working capability index items constructed in advance;
determining the capacity items with the lowest scores and the preset quantity as capacity item short plates of the users;
pushing courses associated with the capability item shortboards to the user;
wherein the step of inputting the personal information into a plurality of user portrait models constructed in advance includes:
querying a working team on which the user is located;
respectively counting the professional development types corresponding to the personnel with the determined professional development types in the working team;
respectively counting the number ratio of the number of people in the working team corresponding to each occupational development type relative to the total number of people in the working team;
sequentially arranging the user portrait models corresponding to the professional development types according to the order of the number proportion of the corresponding professional development types from high to low;
sequentially inputting the personal information into the arranged user portrait models;
and in the process of sequentially inputting the personal information into the arranged user portrait models, if the matching degree output by any user portrait model exceeds a preset threshold value, stopping inputting the personal information into the next user portrait model.
2. The method for pushing courses according to claim 1, wherein if a capability item scoring model corresponding to a professional development type of the user is not selected, a score of any one of the target capability items of the user is calculated by:
extracting a target value of partial information related to the target capability item from the personal information;
and comparing the target value with each grading reference value corresponding to the target capacity item, and determining the grading of the target capacity item according to the comparison result.
3. The method of pushing lessons according to claim 1, wherein the score of any one of the individual capability items of the user is calculated by:
selecting a target scoring model corresponding to the target capability item, wherein the target scoring model is a neural network model obtained by training a training set by using personal information of a plurality of sample users with scores of the target capability item as reference values;
and inputting the personal information of the user into the target scoring model, and determining the score of the target ability item according to the output result of the target scoring model.
4. A method of pushing a lesson as claimed in any one of claims 1 to 3, further comprising:
updating the personal information of the user every first period, and then recalculating the scores of all the capability items of the user by combining the capability item scoring model and the updated personal information;
and updating the personal information of the user every second period, then respectively inputting the updated personal information into the plurality of user portrait models, and redefining the occupational development type of the user, wherein the second period is larger than the first period.
5. An apparatus for pushing a lesson, comprising:
the personal information acquisition module is used for acquiring personal information of a user;
the professional development type determining module is used for respectively inputting the personal information into a plurality of pre-constructed user portrait models, determining the professional development type of the user according to the output result of each user portrait model, wherein each user portrait model corresponds to one professional development type, and the user portrait model is obtained by training the personal information of a plurality of sample users corresponding to the professional development type as a training set;
the ability item scoring model selecting module is used for selecting an ability item scoring model corresponding to the professional development type of the user;
the capacity item scoring module is used for respectively calculating the scores of all the capacity items of the user by combining the selected capacity item scoring model and the personal information, wherein the capacity items refer to all the working capacity index items constructed in advance;
the capacity item short board determining module is used for determining the capacity items with the lowest scores and the preset quantity as the capacity item short boards of the users;
the course pushing module is used for pushing courses associated with the capability item short boards to the user;
wherein the job development type determination module includes:
the work team inquiring unit is used for inquiring the work team where the user is located;
the personnel type determining unit is used for respectively counting the professional development types corresponding to the personnel with the determined professional development types in the working team;
the staff number counting unit is used for counting the number ratio of the staff number in the working team corresponding to each professional development type relative to the total number of staff in the working team respectively;
the model ordering unit is used for sequentially ordering the user portrait models corresponding to the professional development types according to the order of the number proportion of the corresponding professional development types from high to low;
a personal information input unit for inputting the personal information into each of the user portrait models after being arranged in sequence;
and the calculation stopping unit is used for stopping inputting the personal information into the next user portrait model if the matching degree output by any user portrait model exceeds a preset threshold value in the process of inputting the personal information into the arranged user portrait models in sequence.
6. A computer readable storage medium storing computer readable instructions which, when executed by a processor, implement the steps of the method of pushing lessons as claimed in any one of claims 1 to 4.
7. A server comprising a memory, a processor, and computer readable instructions stored in the memory and executable on the processor, wherein the processor, when executing the computer readable instructions, performs the steps of:
acquiring personal information of a user;
the personal information is respectively input into a plurality of pre-constructed user portrait models, the professional development types of the users are determined according to the output results of the user portrait models, each user portrait model corresponds to one professional development type, and the user portrait model is obtained by training personal information of a plurality of sample users corresponding to the professional development types as a training set;
selecting a capacity item scoring model corresponding to the professional development type of the user;
respectively calculating the scores of all the capability items of the user by combining the selected capability item scoring model and the personal information, wherein the capability items refer to all the working capability index items constructed in advance;
determining the capacity items with the lowest scores and the preset quantity as capacity item short plates of the users;
pushing courses associated with the capability item shortboards to the user;
wherein the step of inputting the personal information into a plurality of user portrait models constructed in advance includes:
querying a working team on which the user is located;
respectively counting the professional development types corresponding to the personnel with the determined professional development types in the working team;
respectively counting the number ratio of the number of people in the working team corresponding to each occupational development type relative to the total number of people in the working team;
sequentially arranging the user portrait models corresponding to the professional development types according to the order of the number proportion of the corresponding professional development types from high to low;
sequentially inputting the personal information into the arranged user portrait models;
and in the process of sequentially inputting the personal information into the arranged user portrait models, if the matching degree output by any user portrait model exceeds a preset threshold value, stopping inputting the personal information into the next user portrait model.
8. The server of claim 7, wherein the processor when executing the computer readable instructions further performs the steps of:
updating the personal information of the user every first period, and then recalculating the scores of all the capability items of the user by combining the capability item scoring model and the updated personal information;
and updating the personal information of the user every second period, then respectively inputting the updated personal information into the plurality of user portrait models, and redefining the occupational development type of the user, wherein the second period is larger than the first period.
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