A lifelong learning system based on resource co-construction and sharing

Abstract

The present invention provides a lifelong learning system based on a resource co-construction and sharing method, which belongs to the field of learning management technology. The system specifically includes: a type assessment module responsible for determining the resource type of a third-party platform, a demand type assessment module responsible for determining the update demand type of the third-party platform in a training site, and a push processing module responsible for determining the course push processing strategy of the third-party platform, and pushing the course push processing strategy to the corresponding associated site in the lifelong learning system, thereby improving the real-time performance and reliability of the push processing.

Description

Technical Field

[0001] The present invention belongs to the technical field of learning management, and in particular relates to a lifelong learning system based on a resource co-construction and sharing method. Background Art

[0002] With the acceleration of the pace of technological updates and iterations, corporate personnel often need to engage in lifelong learning to meet the company's development needs and technological updates and iterations. Therefore, many companies have built personalized online learning systems to meet the learning needs of corporate personnel. Specifically, similar technical solutions are given in invention patent applications CN202410187416.2 "A method and system for cultivating integrated engineering and science talents based on a digital platform" and CN202411358009.X "A method for learning enterprise employee safety knowledge based on AI intelligence and incentive mechanism".

[0003] In the process of building a lifelong learning system, the course resource middle platform is used to access multiple third-party course resources through the API data interface to form a total course resource library, and the courses in the course resource middle platform are distributed on demand to the lifelong learning systems of different training sites through authorization. This makes it a technical problem that needs to be solved urgently to generate differentiated distribution and processing strategies for third-party course resources based on the online course data of training sites with third-party course resources, so as to improve the efficiency of course distribution processing while ensuring the timeliness of update processing for training sites with a small number of online courses.

[0004] In order to solve the above technical problems, this application provides a lifelong learning system based on resource co-construction and sharing method. Summary of the Invention

[0005] To achieve the purpose of the present invention, the present invention adopts the following technical solutions:

[0006] Specifically, this application provides a lifelong learning system based on a resource co-construction and sharing method, which specifically includes:

[0007] The type assessment module is responsible for determining the associated sites of the third-party platform in the training site based on the course resources of the third-party platform, and determining the resource type of the third-party platform based on the online course data in different associated sites and the online course data of the third-party platform in different associated sites;

[0008] The demand type evaluation module is responsible for determining the update demand type of the third-party platform in the training site based on the online course data of different training sites in different third-party platforms and the resource types of different third-party platforms when the resource type of the third-party platform does not belong to the target resource type;

[0009] The push processing module is responsible for determining that the update demand coefficient of the third-party platform is within a preset range based on the update demand type in different training sites, and determining the course push processing strategy of the third-party platform based on the update data of the course resources in the third-party platform and the update data of the online course data of different associated sites of the third-party platform, and pushing it to the corresponding associated sites in the lifelong learning system based on the course push processing strategy.

[0010] The beneficial effects of the present invention are:

[0011] The update demand coefficient of the third-party platform is determined based on the update demand types in different training sites, so that not only a single training site is taken into consideration, but the update demand of the third-party platform in all training sites that have an associated relationship with the third-party platform is taken into consideration, thereby improving the comprehensiveness and accuracy of the update demand evaluation and processing, and laying the foundation for further determining differentiated course push processing strategies.

[0012] The course push processing strategy of the third-party platform is determined based on the update data of the course resources in the third-party platform and the update data of the online course data of different associated sites of the third-party platform. Not only the update timeliness of the course resources of the third-party platform is taken into consideration, but also the differences in the push processing timeliness requirements of the third-party platform caused by the differences in the update timeliness of the online course data of the associated sites are taken into consideration. This realizes the determination of the course push processing strategy of the third-party platform from multiple dimensions, which not only ensures the timeliness of the course push processing, but also further reduces the pressure of push processing.

[0013] A further technical solution is that the course resources of the third-party platform include the number of courses on the third-party platform and the types of different courses.

[0014] A further technical solution is that the associated site is a training site for courses on the third-party platform.

[0015] A further technical solution is that the online course data in the associated site includes the number of online courses in the associated site and the number of online courses of the third-party platform in the associated site.

[0016] A further technical solution is that the method for determining the resource type of the third-party platform is:

[0017] Determining the number of online courses in different associated sites using the online course data of the associated sites of the third-party platform;

[0018] Determine resource-influencing sites in the associated sites based on the number of online courses and the proportion of online courses offered by the third-party platform in the associated sites;

[0019] The course resources of the type in the third-party platform that exist in the resource influencing site are regarded as resource matching sites of the type, and the resource type of the third-party platform is determined according to the number of the resource influencing sites and the number of resource matching sites of different types of courses.

[0020] A further technical solution is that the resource-influencing site is an associated site whose number of online courses after excluding the online courses of the third-party platform in the associated site is less than a preset course number threshold.

[0021] A further technical solution is that the types of courses are divided according to subjects.

[0022] A further technical solution is to determine the resource type of the third-party platform based on the number of resource-affected sites, specifically including: when the number of resource-affected sites is greater than a preset resource-affected site number threshold, further determining whether there is a type of course with a number of resource-matching sites less than a preset matching site number threshold; if so, determining that the resource type of the third-party platform belongs to the second-category resource type; if not, determining that the resource type of the third-party platform is the target resource type;

[0023] When the number of the resource-affected sites is not greater than a preset resource-affected site number threshold, it is determined that the resource type of the third-party platform belongs to the second resource type.

[0024] A further technical solution is that the method for determining the course push processing strategy of the third-party platform is:

[0025] Perform push processing of the course resources of the third-party platform according to the second push processing strategy, use the time period between different adjacent push processing moments of the third-party platform as the push analysis period, and determine the duration of different push analysis periods of the third-party platform based on the updated data of the course resources in the third-party platform;

[0026] Determine the number of course updates of different associated sites in the push analysis period using the update data of online course data of different associated sites on the third-party platform, and determine the sites with abnormal updates among the associated sites in different push analysis periods using the number of course updates;

[0027] The push analysis period with update delay is determined by the duration of the different push analysis periods and the number of update abnormal sites, and the course push processing strategy of the third-party platform is determined based on the number of push analysis periods with update delay.

[0028] A further technical solution is that the abnormal update site is an associated site whose number of course updates is less than a preset threshold value of the number of updated courses.

[0029] A further technical solution is that the push analysis period with update delay is a push analysis period whose duration is greater than a preset update duration threshold or the number of update abnormal sites is greater than a preset update abnormal site number threshold.

[0030] A further technical solution is to determine the course push processing strategy of the third-party platform based on the number of push analysis periods with update delays, specifically including:

[0031] When the number of push analysis periods with update delays is greater than a preset delay period number threshold, a preset push processing strategy is adopted to determine the course push processing strategy of the third-party platform;

[0032] When the number of push analysis periods with update delays is not greater than the preset delay period number threshold, the second preset push processing strategy is adopted to determine the course push processing strategy of the third-party platform.

[0033] Other features and advantages will be described in the following description. The objectives and other advantages of the present invention are realized and obtained by the structures particularly pointed out in the description and drawings.

[0034] In order to make the above-mentioned objects, features and advantages of the present invention more obvious and easy to understand, preferred embodiments are given below and described in detail with reference to the accompanying drawings. BRIEF DESCRIPTION OF THE DRAWINGS

[0035] The above and other features and advantages of the present invention will become more apparent by describing in detail example embodiments thereof with reference to the accompanying drawings;

[0036] Figure 1 It is a flowchart of a lifelong learning system based on a resource co-construction and sharing approach;

[0037] Figure 2 It is a flowchart of a method for determining a resource type of a third-party platform;

[0038] Figure 3 is a flow chart of a method for determining an update requirement type of the third-party platform in the training site;

[0039] Figure 4is a flow chart of a method for determining an update demand coefficient of a third-party platform;

[0040] Figure 5 It is a flowchart of a method for determining a course push processing strategy on a third-party platform. DETAILED DESCRIPTION

[0041] To help those skilled in the art better understand the technical solutions in this specification, the following will provide a clear and complete description of the technical solutions in the embodiments of this specification, in conjunction with the accompanying drawings. Obviously, the described embodiments are only part of the embodiments of this specification, not all of them. All other embodiments obtained by those skilled in the art based on the embodiments of this specification without creative work should fall within the scope of protection of this specification.

[0042] In this application, by considering the constituent data of online courses in different related platforms of third-party platforms with course resources, an assessment of the degree of update demand in different related platforms of the third-party platform is achieved, and then differentiated push processing strategies are determined. On the basis of reducing the data processing pressure of push processing, the timeliness of push processing is improved.

[0043] The resource type of the third-party platform is determined based on the number of associated sites whose online courses account for more than 0.2. When the number of associated sites whose online courses account for more than 0.2 is more than 10, the resource type is determined to be the target resource type. Otherwise, it is the second-class resource type.

[0044] Update demand type of third-party platforms in training sites: The update value is determined based on the average of the proportion of online courses of the third-party platform in the associated sites and the proportion of online courses of third-party platforms of the second-category resource type in the associated sites. When the update value is above 0.2, it is determined that its update demand type belongs to the first-category demand site. When the update value is not above 0.2, it is determined that its update demand type belongs to the second-category demand site.

[0045] Update demand coefficient of the third-party platform: The training sites belonging to the first type of update demand and the training sites belonging to the second type of update demand are distributed as the first type of demand sites and the second type of demand sites. The update demand coefficient of the third-party platform is determined based on the preset update demand coefficients corresponding to the number of the first type of demand sites and the number of the second type of demand sites.

[0046] Course push processing strategy: Push processing of the course resources of the third-party platform is performed according to the second push processing strategy, and the time period between different adjacent push processing moments of the third-party platform is used as the push analysis period. The duration of different push analysis periods of the third-party platform is determined by the update data of the course resources in the third-party platform. The number of course updates is used to determine the update abnormality sites in the associated sites in different push analysis periods. Push analysis periods with a duration greater than a preset update duration threshold or a number of update abnormality sites greater than a preset update abnormality site number threshold are regarded as push analysis periods with update delays.

[0047] When the number of push analysis periods with update delays is greater than a preset delay period number threshold, a preset push processing strategy is adopted to determine the course push processing strategy of the third-party platform;

[0048] When the number of push analysis periods with update delays is not greater than the preset delay period number threshold, the second preset push processing strategy is adopted to determine the course push processing strategy of the third-party platform.

[0049] Example 1

[0050] like Figure 1 As shown, this application provides a lifelong learning system based on a resource co-construction and sharing method, specifically including:

[0051] The type assessment module is responsible for determining the associated sites of the third-party platform in the training site based on the course resources of the third-party platform, and determining the resource type of the third-party platform based on the online course data in different associated sites and the online course data of the third-party platform in different associated sites;

[0052] Furthermore, the course resources of the third-party platform include the number of courses on the third-party platform and the types of different courses.

[0053] Specifically, the associated site is a training site where courses on the third-party platform exist.

[0054] It can be understood that the online course data in the associated site includes the number of online courses in the associated site and the number of online courses of the third-party platform in the associated site.

[0055] It should be noted that if Figure 2 As shown, the method for determining the resource type of the third-party platform is:

[0056] Determining the number of online courses in different associated sites using the online course data of the associated sites of the third-party platform;

[0057] Determine resource-influencing sites in the associated sites based on the number of online courses and the proportion of online courses offered by the third-party platform in the associated sites;

[0058] The course resources of the type in the third-party platform that exist in the resource influencing site are regarded as resource matching sites of the type, and the resource type of the third-party platform is determined according to the number of the resource influencing sites and the number of resource matching sites of different types of courses.

[0059] Furthermore, the resource-affecting site is an associated site whose number of online courses after excluding the online courses of the third-party platform in the associated site is less than a preset course number threshold.

[0060] It will be appreciated that the types of courses are divided according to subject.

[0061] Specifically, determining the resource type of the third-party platform according to the number of sites affected by the resource includes:

[0062] When the number of resource-affected sites is greater than a preset threshold number of resource-affected sites, it is further determined whether there is a type of course whose number of resource-matching sites is less than a preset threshold number of matching sites. If so, it is determined that the resource type of the third-party platform belongs to the second-category resource type. If not, it is determined that the resource type of the third-party platform is the target resource type.

[0063] When the number of the resource-affected sites is not greater than a preset resource-affected site number threshold, it is determined that the resource type of the third-party platform belongs to the second resource type.

[0064] In another possible embodiment, the method for determining the resource type of the third-party platform is:

[0065] Determining the number of online courses in different associated sites using the online course data of the associated sites of the third-party platform;

[0066] Determining resource impact coefficients of different associated sites based on the proportion of online courses offered by the third-party platform in the associated sites;

[0067] The course resources of the type in the third-party platform that exist in the resource impact site are regarded as resource matching sites of the type, and the resource type of the third-party platform is determined according to the resource impact coefficients of different associated sites and the number of resource matching sites of different types of courses.

[0068] Furthermore, the resource type of the third-party platform is determined based on the resource impact coefficients of different associated sites and the number of resource matching sites for different types of courses, specifically including:

[0069] When the sum of the resource impact coefficients of different associated sites is greater than a preset impact coefficient threshold, it is further determined whether there is a type of course whose number of resource matching sites is less than a preset matching site number threshold. If so, it is determined that the resource type of the third-party platform belongs to the second type of resource type. If not, it is determined that the resource type of the third-party platform is the target resource type.

[0070] When the sum of the resource impact coefficients of different associated sites is not greater than a preset impact coefficient threshold, it is determined that the resource type of the third-party platform belongs to the second resource type.

[0071] The demand type evaluation module is responsible for determining the update demand type of the third-party platform in the training site based on the online course data of different training sites in different third-party platforms and the resource types of different third-party platforms when the resource type of the third-party platform does not belong to the target resource type;

[0072] Specifically, such as Figure 3 As shown, the method for determining the update requirement type of the third-party platform in the training site is:

[0073] Using the online course data of the training site on different third-party platforms and combining it with the resource types of different third-party platforms, determine the proportion of the number of courses of the target resource type on the training site, and use it as the real-time updated proportion;

[0074] Using the online course data of the training site on different third-party platforms and combining the resource types of different third-party platforms, determine the proportion of the number of courses on the training site on the third-party platform, and use this as the course proportion of the third-party platform;

[0075] According to the real-time update ratio and the number of online courses at the training site, the number of courses of the second type of resources in the training site is determined; based on the ratio of the third-party platform in the number of courses of the second type of resources at the training site and the ratio of the courses of the third-party platform, the update demand type of the third-party platform in the training site is determined.

[0076] Furthermore, based on the proportion of the number of courses of the third-party platform in the second resource type at the training site and the proportion of the courses of the third-party platform, determining the update demand type of the third-party platform at the training site specifically includes:

[0077] Determine an update impact coefficient based on the average of the proportion of the number of courses on the training site provided by the third-party platform for the second resource type and the proportion of courses on the third-party platform;

[0078] Determine whether the update impact coefficient is greater than a preset impact coefficient threshold. If so, determine that the update demand type of the third-party platform in the training site is a first-class update demand type; if not, determine that the update demand type of the third-party platform in the training site is a second-class update demand type.

[0079] It can be understood that the update requirement degree of the first type of update requirement is greater than that of the second type of update requirement.

[0080] In another possible embodiment, the method for determining the update requirement type of the third-party platform in the training site is:

[0081] Using the online course data of the training site on different third-party platforms and combining it with the resource types of different third-party platforms, determine the proportion of the number of courses of the target resource type on the training site, and use it as the real-time updated proportion;

[0082] Using the online course data of the training site on different third-party platforms and combining the resource types of different third-party platforms, determine the proportion of the number of courses on the training site on the third-party platform, and use this as the course proportion of the third-party platform;

[0083] The update requirement type of the third-party platform in the training site is determined according to the real-time update ratio, the number of online courses at the training site, and the course ratio of the third-party platform.

[0084] Furthermore, based on the real-time update ratio, the number of online courses at the training site, and the ratio of courses at the third-party platform, the update demand type of the third-party platform at the training site is determined, specifically including:

[0085] When the real-time update ratio is greater than a preset update ratio threshold, it is determined that the update demand type of the third-party platform in the training site is a second-class update demand type;

[0086] When the real-time update ratio is not greater than the preset update ratio threshold, the number of online courses of the second type of resource is determined based on the number of online courses of the training site and the real-time update ratio, and whether the number of online courses of the second type of resource is greater than the preset online course number threshold is judged. If so, it is determined that the update demand type of the third-party platform in the training site is a first type of update demand type. If not, the course ratio of the third-party platform is used to determine the update demand type of the third-party platform in the training site.

[0087] It should be noted that the type of update demand of the third-party platform in the training site is determined by utilizing the course proportion of the third-party platform, specifically including:

[0088] Determine the course update influence coefficient of the third-party platform in the training site by multiplying the course proportion of the third-party platform by the proportion of the number of online courses of the second resource type in the training site;

[0089] Determine whether the course update impact coefficient is greater than a preset update impact coefficient threshold. If so, determine that the update demand type of the third-party platform in the training site is a first-class update demand type; if not, determine that the update demand type of the third-party platform in the training site is a second-class update demand type.

[0090] The push processing module is responsible for determining that the update demand coefficient of the third-party platform is within a preset range based on the update demand type in different training sites, and determining the course push processing strategy of the third-party platform based on the update data of the course resources in the third-party platform and the update data of the online course data of different associated sites of the third-party platform, and pushing it to the corresponding associated sites in the lifelong learning system based on the course push processing strategy.

[0091] Specifically, such as Figure 4 As shown, the method for determining the update requirement coefficient of the third-party platform is:

[0092] Determining, based on the types of update requirements in different training sites, whether the third-party platform belongs to a training site with a first update requirement type or a training site with a second update requirement type;

[0093] The training sites that belong to the first type of update demand and the training sites that belong to the second type of update demand are respectively regarded as the first type of demand sites and the second type of demand sites;

[0094] Based on the number of the first-category demand sites and the number of the second-category demand sites, an update demand coefficient of the third-party platform is determined.

[0095] Furthermore, based on the number of the first-category demand sites and the number of the second-category demand sites, determining the update demand coefficient of the third-party platform specifically includes:

[0096] The third-party platform determines a matching preset platform type of the third-party platform by using a table lookup method based on the number of the first-category demand sites and the number of the second-category demand sites;

[0097] An update requirement coefficient of the third-party platform is determined according to a preset platform type matched by the third-party platform.

[0098] It can be understood that the matched preset platform type is determined by the preset platform type of the third-party platform when the number of the first-class demand sites and the number of the second-class demand sites are both matched with the corresponding number interval of the first-class demand sites and the number interval of the second-class demand sites.

[0099] Furthermore, the update requirement coefficient of the third-party platform is determined according to the preset requirement coefficient corresponding to the matched preset platform type.

[0100] Specifically, the update demand coefficient of the third-party platform ranges from 0 to 1. When the update demand coefficient of the third-party platform is not within the preset range, it is necessary to further determine whether the update demand coefficient of the third-party platform is greater than the preset value of the demand coefficient. If so, as long as there is data update of the course resources on the third-party platform, the type of course with data update will be immediately pushed to its corresponding training site. If not, the second preset push processing strategy is adopted to determine the course push processing strategy of the third-party platform.

[0101] Furthermore, the second preset push processing strategy is to push the updated data of the course resources of the third-party platform to the training site when the number of course updates on the third-party platform in the push analysis period is greater than a preset update number threshold.

[0102] Specifically, such as Figure 5 As shown, the method for determining the course push processing strategy of the third-party platform is:

[0103] Perform push processing of the course resources of the third-party platform according to the second push processing strategy, use the time period between different adjacent push processing moments of the third-party platform as the push analysis period, and determine the duration of different push analysis periods of the third-party platform based on the updated data of the course resources in the third-party platform;

[0104] Determine the number of course updates of different associated sites in the push analysis period using the update data of online course data of different associated sites on the third-party platform, and determine the sites with abnormal updates among the associated sites in different push analysis periods using the number of course updates;

[0105] The push analysis period with update delay is determined by the duration of the different push analysis periods and the number of update abnormal sites, and the course push processing strategy of the third-party platform is determined based on the number of push analysis periods with update delay.

[0106] Furthermore, the abnormal update site is an associated site whose number of updated courses is less than a preset threshold value of the number of updated courses.

[0107] It can be understood that the push analysis period with update delay is a push analysis period in which the duration is greater than a preset update duration threshold or the number of update abnormal sites is greater than a preset update abnormal site number threshold.

[0108] It should be noted that the course push processing strategy of the third-party platform is determined based on the number of push analysis periods with update delays, specifically including:

[0109] When the number of push analysis periods with update delays is greater than a preset delay period number threshold, a preset push processing strategy is adopted to determine the course push processing strategy of the third-party platform;

[0110] When the number of push analysis periods with update delays is not greater than the preset delay period number threshold, the second preset push processing strategy is adopted to determine the course push processing strategy of the third-party platform.

[0111] In another embodiment, the method for determining the course push processing strategy of the third-party platform is:

[0112] S41: Push processing of the course resources of the third-party platform is performed according to the second push processing strategy, and the time period between different adjacent push processing moments of the third-party platform is used as a push analysis period. The duration corresponding to the different push analysis periods of the third-party platform is determined based on the updated data of the course resources in the third-party platform;

[0113] S42: determining the number of course updates of different associated sites in the push analysis period based on the update data of online course data of different associated sites on the third-party platform, and determining the sites with abnormal updates among the associated sites in different push analysis periods using the number of course updates;

[0114] S43: Determine the update strategy matching coefficients of different push analysis periods based on the duration of the different push analysis periods, the number of update exception sites, and the number of course updates of the update exception sites; determine the strategy matching values ​​of the third-party platform based on the update strategy matching coefficients of the different push analysis periods; and determine the course push processing strategy of the third-party platform according to the strategy matching values.

[0115] Furthermore, the course push processing strategy of the third-party platform is determined according to the strategy matching value, specifically including:

[0116] When the strategy matching value is greater than the preset matching threshold, the second preset push processing strategy is adopted to determine the course push processing strategy of the third-party platform;

[0117] When the strategy matching value is not greater than the preset matching threshold, the preset push processing strategy is adopted to determine the course push processing strategy of the third-party platform.

[0118] Specifically, the preset push processing strategy is to determine whether to push the course resources updated by the third-party platform according to the corresponding preset update abnormality site number threshold and the monitoring data of the update abnormality site within different update time intervals.

[0119] It should be noted that the update duration interval is divided according to a preset duration.

[0120] Furthermore, when the number of update abnormality sites within the update time interval is greater than the corresponding preset update abnormality site number threshold, the course resources updated by the third-party platform are immediately pushed.

[0121] It should be further explained that in the above step S41, it is necessary to further determine whether there is a push analysis period whose duration does not meet the requirements, and whether the average duration of different push analysis periods is less than the preset duration threshold. When there is a push analysis period whose duration does not meet the requirements, due to the long duration, it may cause the update timeliness in the training site to be difficult to meet the requirements. Therefore, its course push processing strategy can be directly determined as the preset push processing strategy.

[0122] At the same time, when there is no push analysis period whose duration does not meet the requirements, if the average duration of different push analysis periods is less than the preset duration threshold, it can be said that the course update timeliness of the third-party platform at this time is fast. Therefore, the second preset push processing strategy can be used to meet the update timeliness requirements in the training site. Therefore, its course push processing strategy can be directly determined as the preset push processing strategy.

[0123] If and only if the average duration of different push analysis periods is not less than the preset duration threshold, it is necessary to further combine the updated data of the online course data of the associated site, and therefore it is necessary to proceed to step S42 for further judgment and processing.

[0124] For example, before proceeding to step S43, it is also necessary to determine in sequence the number of course updates of different associated sites in different push analysis periods in the push analysis period, whether there is a push analysis period in which the number of update abnormal sites does not meet the requirements, and whether the number of different sites identified as update abnormal sites in different push analysis periods meets the requirements, so as to improve the determination and processing efficiency of the course push processing strategy.

[0125] Specifically, when there is an associated site whose average number of course updates in different push analysis periods does not meet the requirements, a fixed threshold can be used for determination. This indicates that there are associated sites that do not update in a timely manner. Therefore, in order to ensure the timeliness of the update processing, its course push processing strategy can be directly determined as the preset push processing strategy.

[0126] In addition, for associated sites that do not have an average number of course updates in different push analysis periods that does not meet the requirements, if there is a push analysis period in which the number of updated abnormal sites is relatively large, that is, there is a push analysis period in which the number of updated abnormal sites does not meet the requirements, the specific determination is made using a threshold method, and it can still be directly determined without a doubt that the timeliness of the update processing at this time is difficult to meet the requirements. Therefore, in order to improve the timeliness of the update processing, its course push processing strategy can be directly determined as the preset push processing strategy.

[0127] Furthermore, when there is no push analysis period in which the number of update abnormal sites does not meet the requirements, the number of different associated sites identified as update abnormal sites in different push analysis periods is used as the number of abnormal updates. When there are associated sites with an abnormal update number greater than a fixed threshold, in order to improve the timeliness of the update processing, its course push processing strategy can be directly determined as the preset push processing strategy. If and only if the above conditions all meet the requirements, proceed to step S43.

[0128] It should be further explained that before determining the strategy matching value, it is necessary to further determine whether there are multiple push analysis periods in which the update strategy matching coefficient does not meet the requirements. Specifically, when there are multiple push analysis periods in which the update strategy matching coefficient is less than a certain threshold, it can be directly determined that the timeliness of the push processing using the current push processing strategy is difficult to meet the requirements. Therefore, in order to improve the timeliness of the update processing, the course push processing strategy can be directly determined as the preset push processing strategy.

[0129] Specifically, based on the course push processing strategy, it is pushed to the corresponding related sites in the lifelong learning system, including:

[0130] When it is determined by the course push processing strategy of the third-party platform that there are updated course resources on the third-party platform that need to be pushed, the updated course resources are directly pushed to the associated site corresponding to the updated course resources in the lifelong learning system.

[0131] Furthermore, the associated site corresponding to the updated course resource is an associated site having the course corresponding to the updated course resource.

[0132] Example 2

[0133] In another possible embodiment, the method for determining the resource type of the third-party platform is:

[0134] S11: Determine the number of associated sites for different types of courses on the third-party platform, and determine the site demand value for different types of courses based on historical update data of different types of courses on the third-party platform;

[0135] S12: Determine the number of online courses in different associated sites based on the online course data of the associated sites of the third-party platform, and determine the resource impact value of different associated sites based on the proportion of the number of online courses of the third-party platform in the associated sites and the number of online courses in different associated sites;

[0136] S13: Determine the resource matching coefficient of the third-party platform according to the resource impact values ​​of different associated sites and the site demand values ​​of different types of courses, and use the resource matching coefficient to determine the resource type of the third-party platform.

[0137] A further technical solution is that the resource matching coefficient of the third-party platform is determined according to the product of the resource impact values ​​of different associated sites and the site demand values ​​of different types of courses.

[0138] Optionally, before entering step S11, it is necessary to further determine the number of associated sites of the third-party platform in sequence. Specifically, when the number of associated sites of the third-party platform is less than the preset threshold value of the number of associated sites, it is directly determined that it belongs to the second type of resource. If and only if the number of associated sites of the third-party platform is not less than the preset threshold value of the number of associated sites, then proceed to step S11.

[0139] It should be further explained that in the above step S11, it is necessary to further evaluate and process the number of associated sites of different types of courses, the historical update data of different types of courses in the third-party platform, and the site demand values ​​of different types of courses in turn, and determine whether it is necessary to proceed to step S12 based on the results of the evaluation.

[0140] It can be understood that when there is a type of course whose number of associated sites does not meet the requirements, there is a type of course whose number of associated sites meets the requirements but the average historical update time does not meet the requirements, or there is a type of course whose site demand value is less than the preset site demand threshold, then the resource type of the third-party platform can be directly determined as a second-class resource type.

[0141] Specifically, whether the requirements are met can be determined by means of a fixed threshold. Specifically, when the number of associated sites is less than the preset fixed threshold, or the number of course types whose average historical update time is greater than the preset fixed threshold is greater than the preset delayed update course number threshold, it can be determined that there are course types whose number of associated sites does not meet the requirements, and the number of course types whose number of associated sites meets the requirements but the average historical update time does not meet the requirements does not meet the requirements.

[0142] Optionally, before entering step S13 , it is necessary to further determine the number of associated sites, the number of online courses in different associated sites, and the resource impact value of the associated sites, so as to improve the processing efficiency of resource type evaluation and analysis.

[0143] It should be further explained that when the number of associated sites is within the preset range of associated sites, that is, the number of associated sites is too large; when the number of associated sites is not within the preset range of associated sites, but the number of online courses is less than the preset course number threshold and the number of associated sites does not meet the requirements; when the resource impact value is greater than the preset impact threshold and the number of associated sites does not meet the requirements, it can be directly determined that the resource type of the third-party platform is a Class II resource type.

[0144] It can be understood that when the number of online courses is less than the preset course number threshold, the number of associated sites is relatively large, that is, when it is greater than a certain fixed set threshold or although it is not less than the preset course abnormal site number threshold, the number of associated sites with resource impact values ​​greater than the preset impact threshold is relatively small, that is, less than a certain threshold, then it can be directly determined that it belongs to the second category of resource type.

[0145] Furthermore, when the resource type of the third-party platform belongs to the target resource type, as long as there is data update of the course resource on the third-party platform, the type of the course with data update will be immediately pushed to its corresponding training site.

[0146] Specifically, the corresponding training site is a training site of the type having the course for which the data update exists.

[0147] The various embodiments in this specification are described in a progressive manner, and the same or similar parts between the various embodiments can be referred to each other. Each embodiment focuses on the differences from other embodiments. The above describes specific embodiments of this specification. Other embodiments are within the scope of the appended claims. In some cases, the actions or steps described in the claims can be performed in an order different from that in the embodiments and still achieve the desired results. In addition, the processes depicted in the accompanying drawings do not necessarily require the specific order or continuous order shown to achieve the desired results. In some embodiments, multitasking and parallel processing are also possible or may be advantageous.

[0148] The foregoing description is merely one or more embodiments of this specification and is not intended to limit this specification. It will be apparent to those skilled in the art that various modifications and variations may be made to one or more embodiments of this specification. Any modifications, equivalent substitutions, or improvements made within the spirit and principles of one or more embodiments of this specification are intended to be within the scope of the claims of this specification.

Claims

1. A lifelong learning system based on resource co-construction and sharing method, characterized in that: Specifically include: The type assessment module is responsible for determining the associated sites of the third-party platform in the training site based on the course resources of the third-party platform, and determining the resource type of the third-party platform based on the online course data in different associated sites and the online course data of the third-party platform in different associated sites; The demand type evaluation module is responsible for determining the update demand type of the third-party platform in the training site based on the online course data of different training sites in different third-party platforms and the resource types of different third-party platforms when the resource type of the third-party platform does not belong to the target resource type; The push processing module is responsible for determining that the update demand coefficient of the third-party platform is within a preset range based on the update demand types in different training sites, and determining the course push processing strategy of the third-party platform based on the update data of the course resources in the third-party platform and the update data of the online course data of different associated sites of the third-party platform, and pushing the course push processing strategy to the corresponding associated sites in the lifelong learning system based on the course push processing strategy; The method for determining the resource type of the third-party platform is: Determining the number of online courses in different associated sites using the online course data of the associated sites of the third-party platform; Determine resource-influencing sites in the associated sites based on the number of online courses and the proportion of online courses offered by the third-party platform in the associated sites; Taking the course resources of the type on the third-party platform that exist in the resource-influencing site as the resource matching site of the type, and determining the resource type of the third-party platform according to the number of the resource-influencing sites and the number of resource matching sites of different types of courses; Determining the resource type of the third-party platform based on the number of sites affected by the resource, specifically including: When the number of resource-affected sites is greater than a preset threshold number of resource-affected sites, it is further determined whether there is a type of course whose number of resource-matching sites is less than a preset threshold number of matching sites. If so, it is determined that the resource type of the third-party platform belongs to the second-category resource type. If not, it is determined that the resource type of the third-party platform is the target resource type. When the number of the resource-affected sites is not greater than a preset resource-affected site number threshold, it is determined that the resource type of the third-party platform belongs to the second resource type.

2. The lifelong learning system based on the resource co-construction and sharing method according to claim 1 is characterized in that: The course resources of the third-party platform include the number of courses on the third-party platform and the types of different courses.

3. The lifelong learning system based on the resource co-construction and sharing method according to claim 1 is characterized in that: The associated site is a training site where courses on the third-party platform exist.

4. The lifelong learning system based on the resource co-construction and sharing method according to claim 1 is characterized in that: The online course data in the associated site includes the number of online courses in the associated site and the number of online courses of the third-party platform in the associated site.

5. The lifelong learning system based on resource co-construction and sharing method according to claim 1 is characterized in that: The method for determining the course push processing strategy of the third-party platform is: Perform push processing of the course resources of the third-party platform according to the second push processing strategy, use the time period between different adjacent push processing moments of the third-party platform as the push analysis period, and determine the duration of different push analysis periods of the third-party platform based on the updated data of the course resources in the third-party platform; Determine the number of course updates of different associated sites in the push analysis period using the update data of online course data of different associated sites on the third-party platform, and determine the sites with abnormal updates among the associated sites in different push analysis periods using the number of course updates; The push analysis period with update delay is determined by the duration of the different push analysis periods and the number of update abnormal sites, and the course push processing strategy of the third-party platform is determined based on the number of push analysis periods with update delay.

6. The lifelong learning system based on the resource co-construction and sharing method according to claim 5 is characterized in that: The course push processing strategy of the third-party platform is determined based on the number of push analysis periods with update delays, specifically including: When the number of push analysis periods with update delays is greater than a preset delay period number threshold, a preset push processing strategy is adopted to determine the course push processing strategy of the third-party platform; When the number of push analysis periods with update delays is not greater than the preset delay period number threshold, the second preset push processing strategy is adopted to determine the course push processing strategy of the third-party platform.

7. The lifelong learning system based on resource co-construction and sharing method according to claim 1 is characterized in that: Based on the course push processing strategy, the course is pushed to the corresponding related sites in the lifelong learning system, including: When it is determined by the course push processing strategy of the third-party platform that there are updated course resources on the third-party platform that need to be pushed, the updated course resources are directly pushed to the associated site corresponding to the updated course resources in the lifelong learning system.

8. The lifelong learning system based on the resource co-construction and sharing method according to claim 7 is characterized in that: The associated site corresponding to the updated course resource is an associated site having the course corresponding to the updated course resource.

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