CN113240563B - Course pushing method, course pushing device and server - Google Patents
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Abstract
The embodiment of the invention provides a course pushing method, a course pushing device and a server, wherein the method comprises the following steps: extracting learning attribute parameters of all students from a database of a learning platform, determining a target student according to the learning attribute parameters of all the students, and determining a target terminal according to the learning attribute parameters of the target student; inquiring a sub-organization corresponding to the target student, and determining a popular course according to learning attribute parameters of all students contained in the sub-organization and the target terminal; and sending the popular courses to the target terminal for display so as to prompt the target students to learn the popular courses, so that the recommended courses are more in line with the business direction and learning interest of the target students, and the learning quality and learning efficiency of the target students are improved.
Description
Technical Field
The embodiment of the invention relates to the technical field of Internet, in particular to a course pushing method, device and server.
Background
With the continuous popularization and application of the Internet and mobile terminals, more and more enterprises adopt an online learning mode, an online learning platform is provided for staff by constructing an enterprise internal training ecosystem, and the training requirements of the enterprise on the staff are met.
Currently, in order to meet the learning requirements of all employees, the existing online learning platform generally displays all training contents, such as employee attendance training, welfare training and business related training contents, on the online learning platform.
However, the learning interests for different courses are different due to the different work content and business direction of different employees. The current online learning platform recommended courses cannot be recommended in a targeted mode, and the online learning efficiency of staff is affected.
Disclosure of Invention
The embodiment of the invention provides a course pushing method, a course pushing device and a server, which improve the online learning efficiency of staff.
In a first aspect, an embodiment of the present invention provides a course pushing method, including:
extracting learning attribute parameters of all students from a database of a learning platform, determining a target student according to the learning attribute parameters of all students, and determining a target terminal according to the learning attribute parameters of the target student;
inquiring a sub-organization corresponding to the target student, and determining a popular course according to learning attribute parameters of all students contained in the sub-organization and the target terminal;
and sending the hot course to the target terminal for display so as to prompt a target student to learn the hot course.
In one possible design, the determining the target learner according to the learning attribute parameters of all the learners includes:
determining a login index, a learning frequency index and a learning duration index of each student according to the learning attribute parameters of all students, and determining the learning conversion rate of each student according to the login index, the learning frequency index and the learning duration index of each student;
and taking the student with the learning conversion rate smaller than the preset conversion rate threshold as a target student.
In one possible design, the determining a popular course according to learning attribute parameters of all the students contained in the sub-organization and the target terminal includes:
determining a target contact attribute according to the attribute of the target terminal;
screening learning attribute parameters of all students contained in the sub-organization according to the target contact attribute, and determining a learning time index and a learning duration index of each student in the target contact attribute;
and determining recommended students according to the learning time index and the learning time index of each student on the target contact attribute, and determining popular courses according to the learning courses of the recommended students.
In one possible design, the learning attribute parameter includes at least one of a login time, a login time period, a login time preference value, a contact learning time, a contact login time period, a learning time period, and a learning time period.
In one possible design, the learning attribute parameter further includes a login period, and the sending the popular course to the target terminal for display includes:
and determining an optimal time period according to the login time period in the learning attribute parameters of the target students, and sending the trending course to the target terminal for display in the optimal time period.
In a second aspect, an embodiment of the present invention provides a course pushing device, including:
the extraction module is used for extracting learning attribute parameters of all students from a database of the learning platform, determining a target student according to the learning attribute parameters of all the students, and determining a target terminal according to the learning attribute parameters of the target student;
the determining module is used for inquiring the sub-organization corresponding to the target student and determining a popular course according to learning attribute parameters of all students contained in the sub-organization and the target terminal;
and the sending module is used for sending the popular course to the target terminal for display so as to prompt a target student to learn the popular course.
In a third aspect, an embodiment of the present invention provides a server, including: at least one processor and memory;
the memory stores computer-executable instructions;
the at least one processor executes computer-executable instructions stored in the memory to cause the at least one processor to perform the lesson pushing method as described above in the first aspect and various possible designs of the first aspect.
In a fourth aspect, embodiments of the present invention provide a computer readable storage medium, where computer executable instructions are stored, and when executed by a processor, implement the course pushing method according to the first aspect and the various possible designs of the first aspect.
In a fifth aspect, embodiments of the present invention provide a computer program product, comprising a computer program, which when executed by a processor, implements the course pushing method as described in the first aspect and the various possible designs of the first aspect.
The method comprises the steps of extracting learning attribute parameters of all students from a database of a learning platform, determining a target student according to the learning attribute parameters of all the students, and determining a target terminal according to the learning attribute parameters of the target student; inquiring the sub-organization corresponding to the target student, and determining the popular course according to the learning attribute parameters of all the students contained in the sub-organization and the target terminal, so that the recommended popular course is more in line with the business direction and learning interest of the target student, and the learning quality and learning efficiency of the target student are improved.
Drawings
In order to more clearly illustrate the embodiments of the present invention or the technical solutions of the prior art, the drawings that are needed in the embodiments or the description of the prior art will be briefly described below, it will be obvious that the drawings in the following description are some embodiments of the present invention, and that other drawings can be obtained according to these drawings without inventive effort to a person skilled in the art.
FIG. 1 is an application scenario diagram of a curriculum recommendation method provided by an exemplary embodiment of the present invention;
FIG. 2 is a schematic flow chart of a course pushing method according to an embodiment of the present invention;
FIG. 3 is a second flow chart of a course pushing method according to an embodiment of the present invention;
FIG. 4 is a schematic structural diagram of a course pushing device according to an embodiment of the present invention;
fig. 5 is a schematic hardware structure of a server according to an embodiment of the present invention.
Detailed Description
For the purpose of making the objects, technical solutions and advantages of the embodiments of the present invention more apparent, the technical solutions of the embodiments of the present invention will be clearly and completely described below with reference to the accompanying drawings in the embodiments of the present invention, and it is apparent that the described embodiments are only some embodiments of the present invention, not all embodiments. 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.
The terms "first," "second," "third," "fourth" and the like in the description and in the claims and in the above drawings, if any, are used for distinguishing between similar objects and not necessarily for describing a particular sequential or chronological order. It is to be understood that the data so used may be interchanged where appropriate such that the embodiments of the invention described herein may be implemented, for example, in sequences other than those illustrated or otherwise described herein. Furthermore, the terms "comprises," "comprising," and "having," and any variations thereof, are intended to cover a non-exclusive inclusion, such that a process, method, system, article, or apparatus that comprises a list of steps or elements is not necessarily limited to those steps or elements expressly listed but may include other steps or elements not expressly listed or inherent to such process, method, article, or apparatus.
At present, with the continuous popularization and application of the Internet and mobile terminals, more and more enterprises adopt an online learning mode, an online learning platform is provided for staff by constructing an enterprise internal training ecological system, and the training requirements of the enterprises on the staff are met. In particular, many businesses will conduct online training for different sub-companies or departments, training the learner in a manner that combines a interview course with a network learning course. In order to meet the learning requirements of all employees, the existing online learning platform generally displays all training contents, such as employee attendance training, welfare training and business related training contents, on the online learning platform. However, the learning interests for different courses are different due to the different work content and business direction of different employees. The current online learning platform recommended courses cannot be recommended individually, and the online learning efficiency of staff is affected.
Aiming at the defects, the invention provides a course delivery method, which selects target students with longer online login time but relatively less learning time and low conversion rate through screening, determines hot courses according to other students with high conversion rate in departments where the target students are located or sub-organizations of branch companies, and pushes the hot courses to a terminal where the target students are logged in frequently for display so as to prompt the target students to learn the hot courses. Because the business content of the target student is similar to or the learning interest of the sub-organization of the department or branch company, the recommended popular courses are more in line with the learning interest of the target student, so that the learning enthusiasm and learning efficiency of the target student are improved.
Fig. 1 is an application scenario diagram of a course recommendation method provided in an exemplary embodiment of the present invention. As shown in fig. 1, a server 102 extracts learning attribute parameters of all students from a database 101 of a learning platform, determines a target student according to the learning attribute parameters of all students, and determines a target terminal 103 according to the learning attribute parameters of the target student; the server 102 queries a sub-organization corresponding to the target student and determines a popular course according to learning attribute parameters of all students contained in the sub-organization; finally, the server 102 sends the course information of the popular courses to the display terminal 103 for display, so as to prompt the target students to learn the popular courses.
Fig. 2 is a schematic flow chart of a course pushing method according to an embodiment of the present invention, and an execution body of the embodiment may be the server shown in fig. 1. As shown in fig. 2, the method includes:
s201: and extracting learning attribute parameters of all the students from a database of the learning platform, determining a target student according to the learning attribute parameters of all the students, and determining a target terminal according to the learning attribute parameters of the target student.
In the embodiment of the invention, the database of the learning platform stores learning data of all students, such as login data and learning course data during online learning of the students, and learning attribute parameters of all the students can be extracted from the database of the learning platform. Illustratively, the learning attribute parameter includes at least one of a login number, a login duration, a login number preference value, a contact learning number, a contact login number, a learning number, and a learning duration of the learner on line. Specifically, the contact point is a client used by a student during online learning, and comprises a computer client, a mobile phone application client, an applet and the like.
Illustratively, determining a login index, a learning frequency index and a learning duration index of each student according to learning attribute parameters of all students, and determining a learning conversion rate of each student according to the login index, the learning frequency index and the learning duration index of each student; and taking the student with the learning conversion rate smaller than the preset conversion rate threshold as a target student. Specifically, the learning conversion rate of each learner is related to the login index, the learning frequency index, and the learning duration index.
Illustratively, the login index is related to the number of logins of the learner, the login duration, and the login preference value. Specifically, the registration index X1 k The value of (2) is shown in the formula (1):
wherein ,LNk For login times, LT k For login duration, Q1 k For the login time preference value, k=1, 2,3, …, K is the number of students. The login frequency preference value is the ratio of the total login frequency of the student to the average login frequency of the attribution. For example, the total number of logins of the student is 10 times, the ratio of the number of average logins of the home is 10 times, and the login preference value is 1.5. Exemplary, when logging in the number LN k Greater than a certain value or log-in duration LT k Greater than a certain value, or a login time preference value Q1 k X1 is within a certain value interval k =1, or login time preference value Q1 k X1 is within a certain value interval k =1, otherwise X1 k＝0, wherein T11 、T 14 The preset threshold value can be a system default value or set by an administrator according to needs, and the T is exemplified 11 ＝10。
Exemplary, the number of learning times refers toLabel Y1 k The value of (2) is shown in the formula:
wherein ,QA5i,k For the maximum contact learning number conversion rate of the trainee K, k=1, 2,3, …, K is the trainee number. Maximum contact learning number conversion rate QA5 when learner k i,k When the value is lower than the threshold value, let Y1 k =1, otherwise let Y1 k =0. Wherein the learning frequency conversion rate of each contact point is the ratio of the contact point learning frequency of the learner at the contact point to the contact point login frequency of the learner at the contact point, thereby obtaining the learning frequency conversion rate of the learner at all contact points by determining, and determining the maximum contact point learning frequency conversion rate QA5 i,k . Threshold T 2 Average learning frequency conversion rate T for child organization where students are located 2 Is a real number greater than or equal to zero. The average learning frequency conversion rate is the ratio of the total learning frequency of the sub-organization to the total login frequency of the sub-organization. Exemplary, set T 2 =α×sub-organization average learning number conversion rate, where α∈
[0,1]。
Specifically, the learning duration index Z1 k The value of (2) is shown in the formula (3):
wherein ,QA6i For the student conversion rate during contact learning period, k=1, 2,3, …, K is the number of students. The contact learning duration conversion rate is the ratio of the total learning duration of the student at the contact to the total login duration of the student at the same contact. Conversion rate QA6 when maximum contact learning duration of student k i,k When the value is lower than the threshold value, Z1 is set k =1, otherwise let Z1 k =0, threshold T 3 Is a real number greater than or equal to zero, takes the value and T 2 The same applies.
In the embodiment of the present invention, after determining the login index, the learning frequency index, and the learning duration index, specifically, a method for determining the learning conversion rate of each learner according to the login index, the learning frequency index, and the learning duration index of each learner is shown in formula (4):
F1 k ＝X1 k +Y1 k ×Z1 k (4)
wherein ,F1k To learn the conversion, X1 k Y1 as a registration index k Z1 is the index of the learning times k For learning duration index, k=1, 2,3, …, K is the number of students. The learning conversion rate F1 of each student is determined from this class. Will learn the conversion F1 k And taking the trainees smaller than the preset conversion rate threshold as target trainees, wherein the target trainees are trainees with a certain login amount and lower learning conversion rate. The part of students have learning initiative, but the learning content recommended by the learning platform is not suitable for the students, so that the learning effect of the students is poor, and the learning enthusiasm and the learning efficiency are affected. Thus requiring the part of the learner to make a targeted course recommendation. And determining the target terminal according to the learning attribute parameters of the target trainee. The target terminal is a terminal to which the contact corresponding to the longest login time of the target student belongs.
S202: inquiring the sub-organization corresponding to the target student, and determining the popular course according to the learning attribute parameters of all the students contained in the sub-organization.
In the embodiment of the invention, a department or a sub-company to which the target student belongs, namely a sub-organization corresponding to the target student, is queried according to the position of the target student in the enterprise. For students belonging to the same sub-organization, there is a business or technical commonality, and the learning tendency is the same, so that the popular courses learned by the students in the sub-organization can be determined according to the learning attribute parameters of all the students contained in the sub-organization. By way of example, the total learning duration of each student is determined and ordered according to the learning times and learning durations of all students contained in the sub-organization, a preset number of students before are selected as excellent students, and a popular course is determined according to the courses of learning of the excellent students.
S203: and sending the hot course to the target terminal for display so as to prompt the target student to learn the hot course.
In the embodiment of the invention, the learning attribute parameter further comprises a login period, statistics can be performed according to the login period of the target student, the optimal period with the highest login frequency is determined according to the preset period, and the popular course is sent to the target terminal for display in the login period so as to prompt the target student to learn the popular course.
According to the course pushing method, the students with a certain login amount and low learning conversion rate are used as target students to be recommended, the popular courses are determined according to the learning attribute parameters of all the students contained in the sub-organizations corresponding to the target students, and the popular courses are sent to the target terminals to be displayed, so that the recommended courses are more in line with the business direction and learning interest of the target students, and the learning quality and learning efficiency of the target students are improved.
Fig. 3 is a second schematic flow chart of a course pushing method according to an embodiment of the present invention. In the embodiment of the present invention, the specific implementation process of determining the popular course according to the learning attribute parameters of all the students contained in the sub-organization in S202 is described in detail on the basis of the embodiment of fig. 2. As shown in fig. 3, the method includes:
s301: and determining the target contact attribute according to the attribute of the target terminal.
In the embodiment of the invention, the contact attribute is the type of the client to which the contact belongs. Illustratively, if the contact is a computer client, the contact attribute is computer software; if the contact is a mobile phone client, the contact attribute is mobile terminal application software. And if the target terminal is the terminal to which the contact corresponding to the longest login time of the target student belongs, determining the target contact attribute according to the attribute of the target terminal, namely, the attribute of the target contact is the attribute of the contact corresponding to the longest login time of the target student.
S302: and screening the learning attribute parameters of all the students contained in the sub-organization according to the target contact attribute, and determining the learning time index and the learning duration index of each student in the target contact attribute.
In the implementation of the invention, the learning attribute parameters of all students contained in the sub-organization are screened according to the target contact attribute, and the learning time index and the learning duration index of each student at the target contact attribute are obtained. Course interfaces displayed by online learning interfaces corresponding to different contact attributes are different, and the different online learning interfaces can influence course learning experience and learning efficiency. In order to ensure that the recommended popular courses conform to learning habits of target students, target contact attributes can be determined according to the attributes of target terminals, and courses more suitable for the target students are screened according to the target contact attributes.
S303: and determining recommended students according to the learning time index and the learning time index of each student on the target contact attribute, and determining a popular course according to the learning course of the recommended students.
In the embodiment of the invention, the recommended trainees are determined according to the learning time index and the learning duration index of each trainee on the target contact attribute. Specifically, according to the method described in S201 in the embodiment of fig. 2, the learning frequency index and the learning duration index of each learner at the target contact attribute are determined, and the learning frequency index and the learning duration index are sequentially ranked from high to low, and all recommended learners are determined according to the preset recommendation percentage. And determining the hot course according to the learning course of the recommended student. Specifically, the learning duration of all recommended students on all courses can be counted and ordered, and a preset number of multi-gate courses are sequentially selected from high to low to be used as popular courses to be recommended.
In the embodiment of the invention, the target contact point attribute is determined according to the attribute of the target terminal, and courses more suitable for the target students are screened according to the target contact point attribute, so that the recommended popular courses more accord with the learning habit of the target students, and the learning quality and learning efficiency of the target students can be further improved.
It should be noted that: in the technical scheme of the invention, the related data such as student information, parameters and the like are acquired, stored and applied under the condition that students in the internal training ecological system of an enterprise allow the data to be acquired, stored and applied, and all meet the requirements of related laws and regulations without violating the popular regulations of the public order.
Fig. 4 is a schematic structural diagram of a course pushing device according to an embodiment of the present invention. As shown in fig. 4, the course pushing device includes: an extraction module 401, a determination module 402 and a transmission module 403.
The extracting module 401 is configured to extract learning attribute parameters of all students from a database of a learning platform, determine a target student according to the learning attribute parameters of all students, and determine a target terminal according to the learning attribute parameters of the target student.
And the determining module 402 is configured to query a sub-organization corresponding to the target learner, and determine a popular course according to learning attribute parameters of all the learner included in the sub-organization and the target terminal.
And the sending module 403 is configured to send the popular course to the target terminal for display, so as to prompt a target student to learn the popular course.
The device provided in this embodiment may be used to implement the technical solution of the foregoing method embodiment, and its implementation principle and technical effects are similar, and this embodiment will not be described herein again.
In one possible implementation manner, the extracting module is specifically configured to determine a login index, a learning frequency index, and a learning duration index of each learner according to the learning attribute parameters of all the students, and determine a learning conversion rate of each learner according to the login index, the learning frequency index, and the learning duration index of each learner; and taking the student with the learning conversion rate smaller than the preset conversion rate threshold as a target student.
In one possible implementation manner, the extracting module is specifically configured to determine a target contact attribute according to an attribute of the target terminal; screening learning attribute parameters of all students contained in the sub-organization according to the target contact attribute, and determining a learning time index and a learning duration index of each student in the target contact attribute; and determining recommended students according to the learning time index and the learning time index of each student on the target contact attribute, and determining popular courses according to the learning courses of the recommended students.
In one possible implementation manner, the extracting module is specifically configured to sort the learning courses of the recommended learner according to the learning times and the learning duration in sequence; and taking the previous preset number of courses of the ordered learning courses as hot courses.
The device provided in this embodiment may be used to implement the technical solution of the foregoing method embodiment, and its implementation principle and technical effects are similar, and this embodiment will not be described herein again.
Fig. 5 is a schematic hardware structure of a server according to an embodiment of the present invention. As shown in fig. 5, the server of the present embodiment includes: a processor 501 and a memory 502; wherein the method comprises the steps of
A memory 502 for storing computer-executable instructions;
the processor 501 is configured to execute computer-executable instructions stored in the memory to implement the steps executed by the server in the above embodiment. Reference may be made in particular to the relevant description of the embodiments of the method described above.
Alternatively, the memory 502 may be separate or integrated with the processor 501.
When the memory 502 is provided separately, the voice interaction device further comprises a bus 503 for connecting said memory 502 and the processor 501.
The embodiment of the invention also provides a computer readable storage medium, wherein the computer readable storage medium stores computer execution instructions, and when a processor executes the computer execution instructions, the course pushing method is realized.
The embodiment of the invention also provides a computer program product, which comprises a computer program, wherein the computer program realizes the course pushing method when being executed by a processor.
In the several embodiments provided by the present invention, it should be understood that the disclosed apparatus and method may be implemented in other ways. For example, the above-described embodiments of the apparatus are merely illustrative, and for example, the division of the modules is merely a logical function division, and there may be additional divisions when actually implemented, for example, multiple modules may be combined or integrated into another system, or some features may be omitted or not performed. Alternatively, the coupling or direct coupling or communication connection shown or discussed with each other may be an indirect coupling or communication connection via some interfaces, devices or modules, which may be in electrical, mechanical, or other forms.
The modules described as separate components may or may not be physically separate, and components shown as modules may or may not be physical units, may be located in one place, or may be distributed over multiple network units. Some or all of the modules may be selected according to actual needs to implement the solution of this embodiment.
In addition, each functional module in the embodiments of the present invention may be integrated in one processing unit, or each module may exist alone physically, or two or more modules may be integrated in one unit. The units formed by the modules can be realized in a form of hardware or a form of hardware and software functional units.
The integrated modules, which are implemented in the form of software functional modules, may be stored in a computer readable storage medium. The software functional modules described above are stored in a storage medium and include instructions for causing a computer device (which may be a personal computer, a server, or a network device, etc.) or processor to perform some of the steps of the methods described in various embodiments of the present application.
It should be understood that the above processor may be a central processing unit (Central Processing Unit, abbreviated as CPU), but may also be other general purpose processors, digital signal processors (Digital Signal Processor, abbreviated as DSP), application specific integrated circuits (Application Specific Integrated Circuit, abbreviated as ASIC), etc. A general purpose processor may be a microprocessor or the processor may be any conventional processor or the like. The steps of a method disclosed in connection with the present invention may be embodied directly in a hardware processor for execution, or in a combination of hardware and software modules in a processor for execution.
The memory may comprise a high-speed RAM memory, and may further comprise a non-volatile memory NVM, such as at least one magnetic disk memory, and may also be a U-disk, a removable hard disk, a read-only memory, a magnetic disk or optical disk, etc.
The bus may be an industry standard architecture (Industry Standard Architecture, ISA) bus, an external device interconnect (Peripheral Component Interconnect, PCI) bus, or an extended industry standard architecture (Extended Industry Standard Architecture, EISA) bus, among others. The buses may be divided into address buses, data buses, control buses, etc. For ease of illustration, the buses in the drawings of the present application are not limited to only one bus or one type of bus.
The storage medium may be implemented by any type or combination of volatile or nonvolatile memory devices such as Static Random Access Memory (SRAM), electrically erasable programmable read-only memory (EEPROM), erasable programmable read-only memory (EPROM), programmable read-only memory (PROM), read-only memory (ROM), magnetic memory, flash memory, magnetic or optical disk. A storage media may be any available media that can be accessed by a general purpose or special purpose computer.
An exemplary storage medium is coupled to the processor such the processor can read information from, and write information to, the storage medium. In the alternative, the storage medium may be integral to the processor. The processor and the storage medium may reside in an application specific integrated circuit (Application Specific Integrated Circuits, ASIC for short). It is also possible that the processor and the storage medium reside as discrete components in an electronic device or a master device.
Those of ordinary skill in the art will appreciate that: all or part of the steps for implementing the method embodiments described above may be performed by hardware associated with program instructions. The foregoing program may be stored in a computer readable storage medium. The program, when executed, performs steps including the method embodiments described above; and the aforementioned storage medium includes: various media that can store program code, such as ROM, RAM, magnetic or optical disks.
Finally, it should be noted that: 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 or all of the technical features thereof can be replaced by equivalents; such modifications and substitutions do not depart from the spirit of the invention.
Claims (7)
1. A course pushing method, comprising:
extracting learning attribute parameters of all students from a database of a learning platform, and determining a login index, a learning frequency index and a learning duration index of each student according to the learning attribute parameters of all students;
according to formula F1 k ＝X1 k +Y1 k ×Z1 k Determining a learning conversion rate of each student; wherein the F1 k For the learning conversion, X1 k Y1 as the login index k Z1 is the index of the learning times k K is the number of students for the learning duration index;
taking a student with the learning conversion rate smaller than a preset conversion rate threshold as a target student, and determining a target terminal according to learning attribute parameters of the target student, wherein the target terminal is a terminal to which a contact corresponding to the longest login time of the target student belongs;
inquiring a sub-organization corresponding to the target student, and determining a popular course according to learning attribute parameters of all students contained in the sub-organization and the target terminal;
sending the hot course to the target terminal for display so as to prompt a target student to learn the hot course;
wherein ,
LN k for login times, LT k For login duration, Q1 k The login frequency preference value is the ratio of the total login frequency of a student k to the average login frequency of a home country, T 11 、T 12 、T 13 、T 14 Presetting a threshold value;
QA5 i,k for the conversion rate of the contact learning times of the learner K, the conversion rate of the contact learning times is the ratio of the contact learning times of the learner at the contact to the contact login times of the learner at the contact, T 2 Is a real number greater than or equal to zero;
QA6 i,k for the contact learning duration conversion rate of k students, the contact learning duration conversion rate is the ratio of the total learning duration of the students at the contact to the total logging duration of the students at the contact, T 3 Is a real number greater than or equal to zero.
2. The method according to claim 1, wherein said determining a popular course from learning attribute parameters of all students contained in the sub-organization and the target terminal comprises:
determining a target contact attribute according to the attribute of the target terminal;
screening learning attribute parameters of all students contained in the sub-organization according to the target contact attribute, and determining a learning time index and a learning duration index of each student in the target contact attribute;
and determining recommended students according to the learning time index and the learning time index of each student on the target contact attribute, and determining popular courses according to the learning courses of the recommended students.
3. The method of claim 1 or 2, wherein the learning attribute parameter comprises at least one of a login time, a login time period, a login time preference value, a contact learning time, a contact login time, a learning time, and a learning time period.
4. The method of claim 1, wherein the learning attribute parameters further comprise a login period:
correspondingly, the sending the hot course to the target terminal for display comprises the following steps:
and determining an optimal time period according to the login time period in the learning attribute parameters of the target students, and sending the trending course to the target terminal for display in the optimal time period.
5. A course pushing device, comprising:
the extraction module is used for extracting learning attribute parameters of all students from a database of the learning platform, and determining login indexes, learning frequency indexes and learning duration indexes of each student according to the learning attribute parameters of all students;
according to formula F1 k ＝X1 k +Y1 k ×Z1 k Determining a learning conversion rate of each student; wherein the F1 k For the learning conversion, X1 k Y1 as the login index k Z1 is the index of the learning times k K is the number of students for the learning duration index;
taking a student with the learning conversion rate smaller than a preset conversion rate threshold as a target student, and determining a target terminal according to learning attribute parameters of the target student, wherein the target terminal is a terminal to which a contact corresponding to the longest login time of the target student belongs;
the determining module is used for inquiring the sub-organization corresponding to the target student and determining a popular course according to learning attribute parameters of all students contained in the sub-organization and the target terminal;
the sending module is used for sending the popular courses to the target terminal for display so as to prompt a target student to learn the popular courses;
wherein ,
LN k for login times, LT k For login duration, Q1 k The login frequency preference value is the ratio of the total login frequency of a student k to the average login frequency of a home country, T 11 、T 12 、T 13 、T 14 Presetting a threshold value;
QA5 i,k for the conversion rate of the contact learning times of the learner K, the conversion rate of the contact learning times is the ratio of the contact learning times of the learner at the contact to the contact login times of the learner at the contact, T 2 Is a real number greater than or equal to zero;
QA6 i,k for the contact learning duration conversion rate of k students, the contact learning duration conversion rate is the ratio of the total learning duration of the students at the contact to the total logging duration of the students at the contact, T 3 Is a real number greater than or equal to zero.
6. A server, comprising: at least one processor and memory;
the memory stores computer-executable instructions;
the at least one processor executing computer-executable instructions stored in the memory causing the at least one processor to perform the curriculum pushing method of any of claims 1-4.
7. A computer readable storage medium having stored therein computer executable instructions which, when executed by a processor, implement the course pushing method of any of claims 1 to 4.
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| CN113689315B (en) * | 2021-09-01 | 2024-02-13 | 中国联合网络通信集团有限公司 | Course pushing method, course pushing device and server |
| CN113837322B (en) * | 2021-11-04 | 2023-05-30 | 中国联合网络通信集团有限公司 | Course classification processing method, device, equipment and medium |
| CN117372219A (en) * | 2023-12-05 | 2024-01-09 | 青岛理工大学 | Student course recommendation method and device and electronic equipment |
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