CN110633415A - Network course pushing method, device, system, electronic equipment and storage medium - Google Patents
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Abstract
The disclosure provides a method, a device, a system, an electronic device and a storage medium for pushing network courses. The method comprises the following steps: the method comprises the steps of responding to a network course pushing request sent by a user through a user terminal, obtaining learned historical data of each network course from a preset database, determining attenuation parameters, liveness parameters and total quantity parameters of each network course according to the historical data, determining the network courses of which the sum of the attenuation parameters, the liveness parameters and the total quantity parameters is larger than a preset threshold value, deleting the determined network courses from the database, pushing the deleted network courses in the database to the user terminal, displaying the pushed network courses by the user terminal, timely unloading the network courses, releasing storage space of the database, enabling the user to quickly obtain updating trends of the network courses, and improving the success rate of pushing the network courses.
Description
Technical Field
The present disclosure relates to the field of internet technologies, and in particular, to a method, an apparatus, a system, an electronic device, and a storage medium for pushing network courses.
Background
With the development of internet technology and the popularization of applications, the push of network information becomes a focus of attention of people, such as the push of network courses.
In the prior art, massive resources of network courses on a network platform are integrated, a user is portrayed according to historical data of the user relative to the network courses (such as interests and hobbies of the user), and the network courses are pushed to the user according to the portrayal.
In the course of the inventors' realization of the present disclosure, it was found that at least the following problems exist: because the network course is increased rapidly, and the network course with cold or wrong discussion is also stored in the network platform, the network course with cold or wrong discussion is likely to be pushed, and the success rate of pushing is reduced.
Disclosure of Invention
The disclosure provides a method, a device, a system, an electronic device and a storage medium for pushing network courses, which are used for solving the problem of low success rate of pushing in the prior art.
In one aspect, an embodiment of the present disclosure provides a method for pushing a network course, including: responding to a network course pushing request sent by a user through a user terminal, and acquiring learned historical data of each network course from a preset database;
determining attenuation parameters, activity parameters and total quantity parameters of each network course according to the historical data;
determining the network courses with the sum of the attenuation parameter, the activeness parameter and the total amount parameter larger than a preset threshold value;
deleting the determined network course from the database;
and pushing the network courses in the deleted database to the user terminal so that the user terminal can display the pushed network courses.
In some embodiments, determining the attenuation parameter from the historical data comprises:
extracting first data in a first time period from the historical data, wherein the first data comprises learning duration, learning times and learning number;
determining learning peak data of a unit cycle of the first time period according to the first data, and determining learning average data of the unit cycle of the first time period;
and determining the attenuation parameter according to the learning peak data and the learning average data.
In some embodiments, determining the liveness parameter from the historical data comprises:
extracting second data in a second time period from the historical data, wherein the second time period takes the current moment as an end moment, the second time period is smaller than the first time period, and the second data comprise learning duration and the number of learners in the second time period;
and determining the activity parameter according to the learning duration and the number of the learners in the second time period.
In some embodiments, determining the aggregate parameter from the historical data comprises:
extracting third data in a third time period from historical data, wherein the starting time of the third time period is the time when each network course is stored in the database, the ending time of the third time period is the current time, the third time period is greater than the first time period, and the third data comprise the learning duration and the number of learners in the third time period;
and determining the total amount parameter according to the learning duration and the number of the learners in the third time period.
In some embodiments, after the determining the network lessons for which the sum of the decay parameter, the liveness parameter, and the total parameter is greater than a preset threshold, the method further comprises:
judging whether the determined course is contained in a preset reserved course list or not;
and if not, executing the deletion processing of the determined network course from the database.
On the other hand, the embodiment of the present disclosure further provides a device for pushing network courses, including: the acquisition module is used for responding to a network course pushing request sent by a user through a user terminal and acquiring learned historical data of each network course from a preset database;
the first determining module is used for determining the attenuation parameter, the activeness parameter and the total amount parameter of each network course according to the historical data;
the second determination module is used for determining the network courses of which the sum of the attenuation parameter, the activity parameter and the total quantity parameter is greater than a preset threshold value;
the processing module is used for deleting the determined network courses from the database;
and the pushing module is used for pushing the network courses in the deleted database to the user terminal so that the user terminal can display the pushed network courses.
In some embodiments, the first determining module is specifically configured to extract first data in a first time period from the historical data, the first data including a learning duration, a learning population and a learning population, determine learning peak data of a unit cycle of the first time period according to the first data, determine learning average data of the unit cycle of the first time period, and determine the attenuation parameter according to the learning peak data and the learning average data.
In some embodiments, the first determining module is specifically configured to extract, from the historical data, second data in a second time period, where the second time period takes a current time as an end time, the second time period is smaller than the first time period, and the second data includes a learning duration and a learning population number in the second time period;
and determining the activity parameter according to the learning duration and the number of the learners in the second time period.
In some embodiments, the first determining module is specifically configured to extract third data in a third time period from historical data, where a starting time of the third time period is a time when each network course is stored in the database, an ending time of the third time period is a current time, the third time period is greater than the first time period, and the third data includes a learning duration and a learning number in the third time period;
and determining the total amount parameter according to the learning duration and the number of the learners in the third time period.
In some embodiments, the apparatus further comprises:
the judging module is used for judging whether the determined courses are contained in a preset reserved course list or not;
if not, the processing module executes the deletion processing of the determined network course from the database.
On the other hand, the embodiment of the present disclosure further provides a network course pushing system, where the system includes: the user terminal and the network course pushing device according to any of the above embodiments, wherein,
and the user terminal is used for sending a network course pushing request to the network course pushing device and displaying the network course pushed by the network course pushing device.
On the other hand, the embodiment of the present disclosure further provides an electronic device, including: a memory, a processor;
a memory for storing the processor-executable instructions;
wherein the processor, when executing the instructions in the memory, is configured to implement a method as in any of the embodiments above.
In another aspect, this disclosed embodiment also provides a computer-readable storage medium, in which computer-executable instructions are stored, and when executed by a processor, the computer-executable instructions are used to implement the method according to any one of the above embodiments.
The method comprises the steps of responding to a network course pushing request sent by a user through a user terminal, obtaining learned historical data of each network course from a preset database, determining attenuation parameters, activity parameters and total quantity parameters of each network course according to the historical data, determining the network courses of which the sum of the attenuation parameters, the activity parameters and the total quantity parameters is larger than a preset threshold value, deleting the determined network courses from the database, pushing the network courses in the deleted database to the user terminal so that the user terminal can display the pushed network courses, determining the network courses to be deleted by determining the parameters of three dimensions of each network course, deleting the courses, timely setting off the network courses, releasing the storage space of the database, the method saves storage resources, and pushes other network courses to the user terminal, so that the user can quickly acquire the updating dynamic state of the network courses, and further learn the network courses interested in or having requirements, and the success rate of pushing the network courses is improved.
Drawings
The accompanying drawings, which are incorporated in and constitute a part of this specification, illustrate embodiments consistent with the present disclosure and together with the description, serve to explain the principles of the disclosure.
Fig. 1 is a schematic diagram of an application scenario of a method for pushing a network course according to an embodiment of the present disclosure;
fig. 2 is a schematic view of a display interface of a user terminal according to an embodiment of the disclosure;
fig. 3 is a flowchart illustrating a method for pushing network courses according to an embodiment of the disclosure;
fig. 4 is a schematic view of a display interface of a user terminal according to another embodiment of the present disclosure;
FIG. 5 is a schematic flow chart diagram of a method of determining an attenuation parameter from historical data according to an embodiment of the present disclosure;
FIG. 6 is a schematic flow chart diagram illustrating a method for determining an activity parameter from historical data according to an embodiment of the present disclosure;
FIG. 7 is a schematic flow chart diagram illustrating a method for determining a total quantity parameter from historical data according to an embodiment of the present disclosure;
fig. 8 is a flowchart illustrating a method for pushing a network course according to another embodiment of the disclosure;
fig. 9 is a block diagram of an apparatus for network course pushing according to an embodiment of the disclosure;
fig. 10 is a block diagram of an apparatus for network course pushing according to another embodiment of the disclosure;
fig. 11 is a schematic structural diagram of an electronic device according to an embodiment of the disclosure;
reference numerals: 10. the system comprises a user, 20, a user terminal, 30, a pushing platform, 1, an obtaining module, 2, a first determining module, 3, a second determining module, 4, a processing module, 5, a pushing module, 6 and a judging module.
With the foregoing drawings in mind, certain embodiments of the disclosure have been shown and described in more detail below. These drawings and written description are not intended to limit the scope of the disclosed concepts in any way, but rather to illustrate the concepts of the disclosure to those skilled in the art by reference to specific embodiments.
Detailed Description
Reference will now be made in detail to the exemplary embodiments, examples of which are illustrated in the accompanying drawings. When the following description refers to the accompanying drawings, like numbers in different drawings represent the same or similar elements unless otherwise indicated. The implementations described in the exemplary embodiments below are not intended to represent all implementations consistent with the present disclosure. Rather, they are merely examples of apparatus and methods consistent with certain aspects of the present disclosure, as detailed in the appended claims.
The method for pushing the network course provided by the embodiment of the disclosure can be applied to the scene shown in fig. 1.
In the application scenario shown in fig. 1, the user 10 may download the APP corresponding to the push platform 30 through the user terminal 20, and may push the APP icon corresponding to the push platform 30 on the user terminal 20 after the downloading is completed.
The pushing platform can be a platform designed by enterprises based on enterprise culture, and can also be a video player such as Youkou video and Tengchong video.
In some embodiments, when the user 10 has a need to learn a network course, the user 10 may trigger a network course push request by clicking an icon of the APP on the user terminal 20. The pushing platform 30, upon receiving the network course pushing request, pushes the network course to the user terminal 20. The user terminal 20 displays the network course pushed by the push platform 30, as shown in fig. 2. When the user 10 starts playing the network lesson by clicking the network lesson displayed on the user terminal 20. Of course, the user 10 may also select the network course by voice.
In other embodiments, the pushing platform 30 may perform the network course pushing process offline according to a preset time interval to obtain the network course to be pushed, and store the network course to be pushed, so as to push the network course to be pushed to the user terminal 20 when the user 10 clicks the APP icon on the user terminal 20 to trigger the network course pushing request. Similarly, the user terminal 20 displays the to-be-pushed network course.
The following describes the technical solutions of the present disclosure and how to solve the above technical problems with specific embodiments. The following several specific embodiments may be combined with each other, and details of the same or similar concepts or processes may not be repeated in some embodiments. Embodiments of the present disclosure will be described below with reference to the accompanying drawings.
In one aspect, the embodiment of the present disclosure provides a method for pushing a network course, which is suitable for the foregoing scenario.
Referring to fig. 3, fig. 3 is a flowchart illustrating a network course pushing method according to an embodiment of the disclosure.
As shown in fig. 3, the method includes:
s101: and responding to a network course pushing request sent by a user through a user terminal, and acquiring learned historical data of each network course from a preset database.
In some embodiments, a main body performing the network course pushing method of the present disclosure may be a network course pushing device, and the network course pushing device may specifically be a pushing platform (as shown in fig. 1), a server, or the like.
In connection with the application scenario shown in fig. 1, in this step, the user 10 triggers a network course push request by clicking an APP icon of the push platform 30 on the user terminal 20. Of course, the user 10 may also trigger the user terminal 20 to send a network course push request to the push platform 30 by means of a voice instruction.
The push platform 30 includes a database, in which each network course and historical data of each network course learned by each user (including the user 10 and other users) are stored, including learning time, learning times, and the like.
S102: and determining the attenuation parameter, the activity parameter and the total quantity parameter of each network course according to the historical data.
Exemplarily, if each network course is n network courses, the attenuation parameter, the activity parameter and the total amount parameter of each network course in the n network courses are respectively determined according to the historical data.
That is, through this step, three-dimensional parameters of each network course are determined, and the three-dimensional parameters are respectively an attenuation parameter, an activity parameter and a total amount parameter.
S103: and determining the network courses with the sum of the attenuation parameter, the activity parameter and the total quantity parameter larger than a preset threshold value.
Wherein the threshold value can be set based on the requirement.
In some embodiments, different thresholds may be set for different network classes. For example, a first threshold value is set for the network course of basic knowledge or the network course with higher practicability, a second threshold value is set for the network course of net reds, and the first threshold value is smaller than the second threshold value, so that diversity and flexibility of course pushing are realized, and the technical effect of improving the pushing success rate is realized.
S104: and deleting the determined network course from the database.
S105: and pushing the network courses in the deleted database to the user terminal so that the user terminal can display the pushed network courses.
With reference to the application scenario shown in fig. 1, when the determined network course is the course 2 shown in fig. 2, the pushing platform 30 deletes the course 2 from the database, and pushes the network course from which the course 2 is deleted to the user terminal 20, so that the user terminal 20 displays the network course, which can be referred to specifically in fig. 4.
In an embodiment of the present disclosure, a new network course pushing method is provided, where the method includes: responding to a network course pushing request sent by a user through a user terminal, acquiring learned historical data of each network course from a preset database, determining an attenuation parameter, an activity parameter and a total quantity parameter of each network course according to the historical data, determining the network course of which the sum of the attenuation parameter, the activity parameter and the total quantity parameter is greater than a preset threshold value, deleting the determined network course from the database, pushing the network course in the deleted database to the user terminal so that the user terminal can display the pushed network course, determining the parameters of three dimensions of each network course to determine the network course to be deleted and delete the course to realize off-shelf processing of the network course in time, releasing the storage space of the database and saving the storage resources, and other network courses are pushed to the user terminal, so that the user can quickly acquire the updating dynamic state of the network courses, and further learn the network courses which are interested in or have requirements, and the success rate of pushing the network courses is improved.
Referring to fig. 5, fig. 5 is a flowchart illustrating a method for determining an attenuation parameter according to historical data according to an embodiment of the disclosure.
As shown in fig. 5, the method includes:
s51: first data in a first time period are extracted from historical data, and the first data comprise learning duration, learning number of people and learning number of people.
Wherein the first time period can be set as required, such as one year.
S52: learning peak data of a unit cycle of the first period is determined from the first data, and learning average data of the unit cycle of the first period is determined.
The unit period may be monthly or weekly.
S53: and determining the attenuation parameters according to the learning peak data and the learning average data.
In some embodiments, because the number of network lessons is large, and the online time of different network lessons is different, in order to accurately determine the attenuation parameter, different network lessons can be classified based on the online time, and the attenuation parameter can be calculated based on the classification, and the attenuation parameter is labeled as K1.
Exemplarily, the online course with the online time length more than one year and less than two years is determined as the first class course, and the attenuation parameter corresponding to the first class course is marked as K11; and determining the network courses with the duration more than two years as a second class of courses, and marking the attenuation parameter corresponding to the second class of courses as K12, wherein the attenuation parameter K1 is K11+ K12.
Aiming at the first class of courses, determining a monthly learning comprehensive value (which can be calculated by weighted sum after normalization) MSV of the first class of courses according to the learning duration, the number of learners and the number of learners corresponding to the first class of coursesiI1, 2,3 …, monthly peak learning volume PeakMSV for class i lesson,
Similarly, for the second class of courses, the order
Since the online duration of the second class of lessons is greater than the online duration of the first class of lessons, the value of I2 may be set to be greater than the value of I1, for example, let I2 be 2 × I1. And, the value of a2 may be set to be greater than that of a1, for example, let a2 be 1.5 × a 1.
Referring to fig. 6, fig. 6 is a flowchart illustrating a method for determining an activity parameter according to historical data according to an embodiment of the disclosure.
As shown in fig. 6, the method includes:
s61: and extracting second data in a second time period from the historical data, wherein the second time period takes the current moment as an end moment, the second time period is smaller than the first time period, and the second data comprises the learning duration and the number of the learners in the second time period.
The second time period can be set as required, and the second time period is shorter than the first time. If the first time period is one year, the second time period may be a half year, or a value less than one year, such as 8 months.
S62: and determining the activity parameter according to the learning time length and the number of the learners in the second time period.
Exemplarily, the activity parameter is marked as K2, second data of the network lessons in the last N months is obtained, and the average learning time length PMeanLTj and the average learning population PMeanLNj, J being 1,2,3 … … J are determined according to the second data, wherein J is the number of the network lessons.
Order to
Referring to fig. 7, fig. 7 is a flowchart illustrating a method for determining a total amount parameter according to historical data according to an embodiment of the disclosure.
As shown in fig. 7, the method includes:
s71: and extracting third data in a third time period from the historical data, wherein the starting time of the third time period is the time when each network course is stored in the database, the ending time of the third time period is the current time, the third time period is greater than the first time period, and the third data comprises the learning duration and the number of the learners in the third time period.
S72: and determining a total amount parameter according to the learning time length and the number of the learners in the third time period.
Exemplarily, the total learning time length in the third time period is determined according to the learning time length of the third data, and is marked as LTj, the total learning population in the third time period is determined according to the learning population of the third data, and is marked as LNj, J is 1,2, … … J, and J is the number of the network courses. Total amount parameter
Referring to fig. 8, fig. 8 is a flowchart illustrating a network course pushing method according to another embodiment of the disclosure.
As shown in fig. 8, the method includes:
s201: and responding to a network course pushing request sent by a user through a user terminal, and acquiring learned historical data of each network course from a preset database.
For the description of S201, reference may be made to S101, which is not described herein again.
S202: and determining the attenuation parameter, the activity parameter and the total quantity parameter of each network course according to the historical data.
For the description of S202, reference may be made to S102, which is not described herein again.
S203: and determining the network courses with the sum of the attenuation parameter, the activity parameter and the total quantity parameter larger than a preset threshold value.
For the description of S203, reference may be made to S103, which is not described herein again.
S203': and judging whether the determined course is contained in a preset reserved course list, if not, executing S204, and if so, ending the process.
The list of retained courses includes, but is not limited to, series class courses and basic knowledge class courses. In this step, the determined course is matched with the retained course list to determine whether the retained course list includes the determined course, if so, the determined course is the course that should be retained, and the process is ended, if not, S204 is executed.
S204: and deleting the determined network course from the database.
S205: and pushing the network courses in the deleted database to the user terminal so that the user terminal can display the pushed network courses.
For the description of S205, reference may be made to S105, which is not described herein again.
According to another aspect of the embodiment of the present disclosure, an apparatus for pushing network courses is further provided.
Referring to fig. 9, fig. 9 is a block diagram of an apparatus for pushing network courses according to an embodiment of the present disclosure.
As shown in fig. 9, the apparatus includes:
the acquisition module 1 is used for responding to a network course pushing request sent by a user through a user terminal and acquiring learned historical data of each network course from a preset database;
the first determining module 2 is used for determining the attenuation parameter, the activity parameter and the total quantity parameter of each network course according to the historical data;
a second determining module 3, configured to determine a network course in which a sum of the attenuation parameter, the activity parameter, and the total amount parameter is greater than a preset threshold;
the processing module 4 is used for deleting the determined network courses from the database;
and the pushing module 5 is configured to push the network course in the database subjected to the deletion processing to the user terminal, so that the user terminal displays the pushed network course.
In some embodiments, the first determining module 2 is specifically configured to extract first data in a first time period from the historical data, where the first data includes a learning duration, a learning number of people, and a learning population, determine learning peak data of a unit cycle of the first time period according to the first data, determine learning average data of the unit cycle of the first time period, and determine the attenuation parameter according to the learning peak data and the learning average data.
In some embodiments, the first determining module 2 is specifically configured to extract, from the historical data, second data in a second time period, where the second time period takes a current time as an end time, and the second time period is smaller than the first time period, and the second data includes a learning duration and a learning population number in the second time period;
and determining the activity parameter according to the learning duration and the number of the learners in the second time period.
In some embodiments, the first determining module 2 is specifically configured to extract third data in a third time period from historical data, where a starting time of the third time period is a time when each network course is stored in the database, an ending time of the third time period is a current time, the third time period is greater than the first time period, and the third data includes a learning duration and a learning number in the third time period;
and determining the total amount parameter according to the learning duration and the number of the learners in the third time period.
As can be seen in fig. 10, in some embodiments, the apparatus further comprises:
the judging module 6 is used for judging whether the determined courses are contained in a preset reserved course list or not;
if not, the processing module 4 executes the deletion processing of the determined network course from the database.
According to another aspect of the embodiments of the present disclosure, there is also provided a network course pushing system, including: the user terminal and the network course pushing device according to any of the above embodiments, wherein,
the user terminal is used for sending a network course pushing request to the network course pushing device and displaying the network course pushed by the network course pushing device.
According to another aspect of the embodiments of the present disclosure, there is also provided an electronic device, including: a memory, a processor;
a memory for storing processor-executable instructions;
wherein, when executing the instructions in the memory, the processor is configured to implement the method of any of the embodiments above.
Referring to fig. 11, fig. 11 is a schematic structural diagram of an electronic device according to an embodiment of the disclosure.
As shown in fig. 11, the electronic device includes a memory and a processor, and the electronic device may further include a communication interface and a bus, wherein the processor, the communication interface, and the memory are connected by the bus; the processor is used to execute executable modules, such as computer programs, stored in the memory.
The Memory may include a high-speed Random Access Memory (RAM) and may also include a non-volatile Memory (non-volatile Memory), such as at least one disk Memory. Via at least one communication interface, which may be wired or wireless), the communication connection between the network element of the system and at least one other network element may be implemented using the internet, a wide area network, a local network, a metropolitan area network, etc.
The bus may be an ISA bus, PCI bus, EISA bus, or the like. The bus may be divided into an address bus, a data bus, a control bus, etc.
The memory is used for storing a program, and the processor executes the program after receiving an execution instruction.
The processor may be an integrated circuit chip having signal processing capabilities. In implementation, the steps of the above method may be performed by integrated logic circuits of hardware in a processor or instructions in the form of software. The Processor may be a general-purpose Processor, and includes a Central Processing Unit (CPU), a Network Processor (NP), and the like; the device can also be a Digital Signal Processor (DSP), an Application Specific Integrated Circuit (ASIC), a Field-Programmable Gate Array (FPGA) or other Programmable logic device, a discrete Gate or transistor logic device, or a discrete hardware component. The steps of the method disclosed in connection with the embodiments of the present disclosure may be directly implemented by a hardware decoding processor, or implemented by a combination of hardware and software modules in the decoding processor. The software module may be located in ram, flash memory, rom, prom, or eprom, registers, etc. storage media as is well known in the art. The storage medium is located in a memory, and a processor reads information in the memory and completes the steps of the method in combination with hardware of the processor.
According to another aspect of the embodiments of the present disclosure, there is also provided a computer-readable storage medium having stored therein computer-executable instructions, which when executed by a processor, are configured to implement the method according to any one of the embodiments.
The reader should understand that in the description of this specification, reference to the description of the terms "one embodiment," "some embodiments," "an example," "a specific example," or "some examples," etc., means that a particular feature, structure, or characteristic described in connection with the embodiment or example is included in at least one embodiment or example of the present disclosure. In this specification, the schematic representations of the terms used above are not necessarily intended to refer to the same embodiment or example. Furthermore, the particular features, structures, or characteristics described may be combined in any suitable manner in any one or more embodiments or examples. Furthermore, various embodiments or examples and features of different embodiments or examples described in this specification can be combined and combined by one skilled in the art without contradiction.
It is clear to those skilled in the art that, for convenience and brevity of description, the specific working processes of the above-described apparatuses and units may refer to the corresponding processes in the foregoing method embodiments, and are not described herein again.
In the several embodiments provided in the present application, it should be understood that the disclosed apparatus and method may be implemented in other ways. For example, the above-described apparatus embodiments are merely illustrative, and for example, a division of a unit is merely a logical division, and an actual implementation may have another division, for example, a plurality of units or components may be combined or integrated into another system, or some features may be omitted, or not executed.
Units described as separate parts may or may not be physically separate, and parts displayed as units may or may not be physical units, may be located in one place, or may be distributed on a plurality of network units. Some or all of the units can be selected according to actual needs to achieve the purpose of the solution of the embodiments of the present disclosure.
In addition, functional units in the embodiments of the present disclosure may be integrated into one processing unit, or each unit may exist alone physically, or two or more units are integrated into one unit. The integrated unit can be realized in a form of hardware, and can also be realized in a form of a software functional unit.
The integrated unit, if implemented in the form of a software functional unit and sold or used as a stand-alone product, may be stored in a computer readable storage medium. Based on such understanding, the technical solution of the present disclosure may be substantially or partially contributed by the prior art, or all or part of the technical solution may be embodied in a software product, which is stored in a storage medium and includes instructions for causing a computer device (which may be a personal computer, a server, or a network device) to execute all or part of the steps of the method of the embodiments of the present disclosure. And the aforementioned storage medium includes: a U-disk, a removable hard disk, a Read-Only Memory (ROM), a Random Access Memory (RAM), a magnetic disk or an optical disk, and other various media capable of storing program codes.
It should also be understood that, in the embodiments of the present disclosure, the sequence numbers of the above-mentioned processes do not mean the execution sequence, and the execution sequence of each process should be determined by its function and inherent logic, and should not constitute any limitation on the implementation process of the embodiments of the present disclosure.
While the present disclosure has been described with reference to specific embodiments, it will be understood by those skilled in the art that various changes and modifications may be made without departing from the spirit and scope of the disclosure. Therefore, the protection scope of the present disclosure shall be subject to the protection scope of the claims.
Claims (13)
1. A method for network course pushing, the method comprising:
responding to a network course pushing request sent by a user through a user terminal, and acquiring learned historical data of each network course from a preset database;
determining attenuation parameters, activity parameters and total quantity parameters of each network course according to the historical data;
determining the network courses with the sum of the attenuation parameter, the activeness parameter and the total amount parameter larger than a preset threshold value;
deleting the determined network course from the database;
and pushing the network courses in the deleted database to the user terminal so that the user terminal can display the pushed network courses.
2. The method of claim 1, wherein determining the attenuation parameter from the historical data comprises:
extracting first data in a first time period from the historical data, wherein the first data comprises learning duration, learning times and learning number;
determining learning peak data of a unit cycle of the first time period according to the first data, and determining learning average data of the unit cycle of the first time period;
and determining the attenuation parameter according to the learning peak data and the learning average data.
3. The method of claim 2, wherein determining the liveness parameter from the historical data comprises:
extracting second data in a second time period from the historical data, wherein the second time period takes the current moment as an end moment, the second time period is smaller than the first time period, and the second data comprise learning duration and the number of learners in the second time period;
and determining the activity parameter according to the learning duration and the number of the learners in the second time period.
4. The method of claim 3, wherein determining the aggregate parameter from the historical data comprises:
extracting third data in a third time period from historical data, wherein the starting time of the third time period is the time when each network course is stored in the database, the ending time of the third time period is the current time, the third time period is greater than the first time period, and the third data comprise the learning duration and the number of learners in the third time period;
and determining the total amount parameter according to the learning duration and the number of the learners in the third time period.
5. The method of any of claims 1-4, wherein after said determining network lessons for which a sum of said decay parameter, said liveness parameter, and said total parameter is greater than a preset threshold, the method further comprises:
judging whether the determined course is contained in a preset reserved course list or not;
and if not, executing the deletion processing of the determined network course from the database.
6. An apparatus for pushing network courses, the apparatus comprising:
the acquisition module is used for responding to a network course pushing request sent by a user through a user terminal and acquiring learned historical data of each network course from a preset database;
the first determining module is used for determining the attenuation parameter, the activeness parameter and the total amount parameter of each network course according to the historical data;
the second determination module is used for determining the network courses of which the sum of the attenuation parameter, the activity parameter and the total quantity parameter is greater than a preset threshold value;
the processing module is used for deleting the determined network courses from the database;
and the pushing module is used for pushing the network courses in the deleted database to the user terminal so that the user terminal can display the pushed network courses.
7. The apparatus of claim 6,
the first determining module is specifically configured to extract first data in a first time period from the historical data, where the first data includes a learning duration, a number of learning people, and a number of learning people, determine learning peak data of a unit cycle of the first time period according to the first data, determine learning average data of the unit cycle of the first time period, and determine the attenuation parameter according to the learning peak data and the learning average data.
8. The apparatus of claim 7,
the first determining module is specifically configured to extract second data in a second time period from the historical data, where the second time period takes the current time as an end time, the second time period is smaller than the first time period, and the second data includes a learning duration and a learning number in the second time period;
and determining the activity parameter according to the learning duration and the number of the learners in the second time period.
9. The apparatus of claim 8,
the first determining module is specifically configured to extract third data in a third time period from historical data, where a starting time of the third time period is a time when each network course is stored in the database, an ending time of the third time period is a current time, the third time period is greater than the first time period, and the third data includes a learning duration and a learning population number in the third time period;
and determining the total amount parameter according to the learning duration and the number of the learners in the third time period.
10. The apparatus of any one of claims 6 to 9, further comprising:
the judging module is used for judging whether the determined courses are contained in a preset reserved course list or not;
if not, the processing module executes the deletion processing of the determined network course from the database.
11. A network course pushing system, said system comprising: the user terminal and the network course pushing device according to any one of claims 6 to 10, wherein,
and the user terminal is used for sending a network course pushing request to the network course pushing device and displaying the network course pushed by the network course pushing device.
12. An electronic device, comprising: a memory, a processor;
a memory for storing the processor-executable instructions;
wherein the processor, when executing the instructions in the memory, is configured to implement the method of any of claims 1 to 5.
13. A computer-readable storage medium having computer-executable instructions stored therein, which when executed by a processor, are configured to implement the method of any one of claims 1 to 5.
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