Binding sales and course flexible configuration method and system based on hosting service

Abstract

The invention relates to the technical field of service management, in particular to a bundled sales and course flexible configuration method and system based on hosting service, and the method comprises the following steps: extracting courses and service time sections, analyzing the calling frequency and resource occupation, judging whether the courses are overloaded and pre-judging conflicts, constructing mutually exclusive course paths, and screening high-coherence low-conflict combinations. And generating a synchronous scheduling table. According to the method, the intersection between the course teaching period and the service starting time window is detected, the course level label and the resource configuration density are combined, the resource mutual exclusion relationship between course paths is distinguished, and a clear exclusive priority rule is established, so that path interference caused by resource scrambling is effectively avoided; according to the method, path coherence scores and service stability parameters are combined, logic coherence and operation stability of overall configuration are guaranteed, a synchronous scheduling structure is generated through comparison of service triggering offset duration and the period lower limit of a resource opening time period, and linkage cooperation of service calling and course content is achieved.

Description

Technical Field

[0001] The present invention relates to the technical field of service management, and in particular to a method and system based on hosting service bundling sales and flexible course configuration. Background Art

[0002] The technical field of service management involves the planning, design, implementation, and control of service products throughout their lifecycle, aiming to improve service quality, user satisfaction, and operational efficiency. This area encompasses service portfolio management, pricing models, configuration rules, resource scheduling strategies, service level agreement design, and service process automation. Particularly in the context of cloud computing, SaaS platforms, and managed hosting models, service management is evolving toward intelligent, modular, and platform-based approaches. This emphasizes the flexible configuration and dynamic combination of service components, as well as mechanisms for matching them to user needs. It also supports efficient cross-business and cross-platform management through standardized interfaces, policy engines, and service catalogs.

[0003] The approach, based on managed service bundling and flexible course configuration, focuses on building a solution that can combine multiple managed service projects with course content and support on-demand configuration of teaching resources and service content. This approach can be used in scenarios such as online education platforms, enterprise training systems, and educational SaaS services. By binding service modules to course units, it aims to support diverse configurations tailored to different customer needs, enabling personalized service delivery and resource reuse, thereby improving the service provider's operational efficiency and customer satisfaction.

[0004] Traditional configuration methods lack a precise matching mechanism for service activation timing and course planning cycles, which can easily lead to situations where resource release time does not match the course execution node, resulting in resource vacancy or delayed delivery. When multiple courses are bound to the same service item at the same time, traditional methods have not established a concurrent request identification and resource conflict judgment mechanism, making it difficult to promptly detect resource preemption problems caused by high-intensity service loads. In addition, the traditional configuration process does not consider the mutual exclusivity of resource allocation between course paths, resulting in the parallel allocation of mutually exclusive resources and increasing the risk of service anomalies. For example, in an enterprise training platform, when multiple high-level courses are bound to the same service node, an overload bottleneck is easily formed, affecting the stability of the platform service and customer experience. Summary of the Invention

[0005] The purpose of the present invention is to solve the shortcomings of the prior art and to propose a method and system based on bundling sales of hosting services and flexible configuration of courses.

[0006] To achieve the above objectives, the present invention adopts the following technical solution: a method based on bundled sales of hosting services and flexible course configuration, comprising the following steps:

[0007] S1: Obtain a preset course bundling combination list, compare the time interval intersection between the planned teaching period and the service activation time window, establish the effective coordination time structure between the course and the supporting service, and obtain a supporting time linkage section set;

[0008] S2: Based on the supporting time linkage section set, extract the concurrent occupancy of the course nodes calling the same service in the same section and compare the time period overlap rate, judge whether the difference between the concurrent occupancy and the maximum carrying value of the resource is lower than the resource utilization warning threshold, mark as a conflict detection state, and establish a service conflict prediction node list;

[0009] S3: Based on the service conflict prediction node list, obtain the course level label and resource use density in the course content, divide the mutual exclusion priority level between the course paths, construct the course path logic under the resource mutual exclusion constraint, and obtain a mutual exclusion course path set;

[0010] S4: Call the mutual exclusion course path set, filter the course combination with the path coherence score value higher than the path coherence reference value and the resource mutual exclusion level lower than the threshold, list the corresponding service items in the combination sales item binding list, and generate a sales path binding service list.

[0011] The application improves that the supporting time linkage section set includes a course teaching period matching section, a service activation time period boundary value and a time overlap coefficient of course and service, the service conflict prediction node list includes a high concurrency service node identifier, a resource load difference calculation value and a conflict state flag bit, the mutual exclusion course path set includes a course mutual exclusion priority label, a resource coverage intersection identifier between paths and a mutual exclusion rule matching record, and the sales path binding service list includes a path score sorting result, a resource exclusivity filtering identifier and a service function range matching value.

[0012] The application improves that the acquisition step of the supporting time linkage section set is specifically:

[0013] S111: Obtain a preset course bundling combination list, call the teaching stage number field and the planned teaching period field of the course unit in the combination list, extract the teaching sequence information corresponding to the teaching period start and end time and the stage number of each course unit, establish the time mapping index of the course in the teaching structure, and obtain a teaching period structure table;

[0014] S112: Based on the teaching period structure table, detect the service activation time window and the course resource opening time field in the hosting service supporting item bound by the course unit, perform intersection calculation on the teaching period interval and the service activation time window interval of each course unit, filter the course service pairs with time interval intersection, and obtain a time overlap interval set;

[0015] S113: Based on the time overlapping interval set, according to the time intersection range of the course service pair, combined with the course node number and time segment identification field in the teaching cycle structure table, a binding mapping between the course and the hosting service on the resource usage timeline is established to obtain a matching time linkage segment set.

[0016] The present invention is improved in that the steps of obtaining the service conflict prediction node list are specifically as follows:

[0017] S211: Based on the matching time linkage segment set, extract the course service time linkage interval field and the corresponding course unit identifier in each linkage record, collect service call records of the course unit-bound managed service item in each linkage segment, extract the call count field per unit time from the record, summarize and measure the service call frequency values ​​within the same linkage segment, and obtain the segment service call frequency value;

[0018] S212: Based on the segment service call frequency value, the resource allocation identification field and the resource scheduling priority field in the course unit data structure are called to extract a list of course units bound to the same service node, locate the interval value between the service call time and the resource binding time, calculate and obtain the resource remaining risk, and determine whether the resource remaining risk is greater than the resource utilization warning threshold. If so, the service node is marked as a conflict pending node, and a resource conflict risk interval is generated;

[0019] S213: Based on the resource conflict risk interval and according to the marked service node numbers, establish a course service pair relationship in which the nodes are judged to be in a high-risk conflict state in the time linkage section, organize the course coverage, time positioning information and resource risk values ​​of the conflicting nodes, summarize and organize the conflicting course service node groups, and establish a service conflict prediction node list.

[0020] The present invention is improved in that the steps of obtaining the mutually exclusive course path set are specifically as follows:

[0021] S311: Based on the service conflict prediction node list, according to the marked hosting service node number, extract the course unit path bound to the node in the corresponding time period, collect the path sequence number and bound service time period field of each course unit in the course path, classify the course path structure in chronological order, and obtain a course service path index table;

[0022] S312: Call the course service path index table, collect the course grade label and resource usage density value in each course unit, screen the course pairs that exist under the conflicting service node and have adjacent path numbers, calculate and obtain the resource mutual exclusion degree value between the course pairs, use the degree value as the course path mutual exclusion grade scoring indicator, sort by degree value and set the grade boundary, and generate the course path mutual exclusion grade sequence;

[0023] S313: Based on the course path mutual exclusion level sequence, according to the mutual exclusion score value and path order mapping relationship of the marked course path, a course path mutual exclusion level corresponding table is constructed, the resource sharing boundary, time sequence logical relationship and mutual exclusion level classification label between the path groups are sorted, and a mutual exclusion relationship course path set is established.

[0024] The application improves that the obtaining step of the sales path binding service list is specifically:

[0025] S411: The mutual exclusion relationship course path set is called, according to the course path node, the service function range identification field in the binding hosting service item corresponding to the path node is extracted, the course path and service function corresponding structure are established combined with the course path order record and path node unique identification value, and the service function mapping table is obtained;

[0026] S412: Based on the service function mapping table, according to the service function path relationship, the path coherence score value of the course path node and the resource load stability coefficient field of the service item are extracted, the course service binding pair whose course path score value is greater than the path coherence reference value and whose resource mutual exclusion level is lower than the threshold value is screened, the binding service fitness score of the course path pair is obtained by operation, the binding service fitness score is sorted from high to low according to the score result and numbered, and the service fitness sorting information is generated;

[0027] S413: Based on the service fitness sorting information, according to the course path and service binding record located in the screening priority section, the structure serial number, function range label and path matching relationship of the binding service item are extracted, the sales recommendation item combination structure between the course path and the configurable service is constructed, and the sales path binding service list is obtained.

[0028] The application improves that the method further comprises the following steps:

[0029] S5: Based on the sales path binding service list, the resource opening time period and service trigger offset time length in each course unit are extracted, the intersection period length is compared with the configured service activation cycle lower limit value, if greater than the cycle lower limit value, the course node and the service item are written into the joint scheduling structure synchronously, and the combined service synchronization scheduling table is obtained;

[0030] The combined service synchronization scheduling table is specifically a course and service joint activation signal, a synchronizable activation time section and a course service linkage scheduling index.

[0031] The application improves that the obtaining step of the combined service synchronization scheduling table is specifically:

[0032] S511: Based on the sales path binding service list, according to the filtered service items and course nodes, extract the resource opening start and end time fields and the service trigger offset duration fields recorded in each course unit, establish a time period correspondence table based on the course and service binding relationship, establish a time period set for each course service pair, and generate a course service time period comparison table;

[0033] S512: Based on the course service time period comparison table, the intersection intervals between the course resource open time period and the service trigger offset correction time period are calculated, the start and end times of the intersection intervals are extracted, and the interval lengths are measured. The measured interval lengths are compared with the configured service activation period lower limit to obtain a course service activation determination result.

[0034] S513: Based on the course service activation judgment result, according to the course service pairs whose intersection time period length is greater than the lower limit of the service activation cycle, mark the synchronization activation status, write the corresponding course node number and service item structure number into the joint scheduling table record, and establish a combined service synchronization scheduling table.

[0035] A system based on bundled sales of managed services and flexible configuration of courses, the system based on bundled sales of managed services and flexible configuration of courses is used to implement the above-mentioned method based on bundled sales of managed services and flexible configuration of courses, the system comprising:

[0036] The time linkage analysis module obtains a list of preset course bundles, compares the time interval intersection between the planned teaching cycle and the service activation time window, establishes an effective collaborative time structure between the course and the supporting services, and obtains a set of supporting time linkage segments;

[0037] The conflict status detection module extracts the concurrent occupancy of the course nodes that call the same service in the same segment and compares it with the time period overlap rate based on the supporting time linkage segment set, determines whether the difference between the concurrent occupancy and the maximum resource load value is lower than the resource utilization warning threshold, marks it as a pending conflict detection state, and establishes a service conflict prediction node list;

[0038] The mutually exclusive relationship identification module obtains the course level label and resource usage density in the course content based on the service conflict prediction node list, divides the mutually exclusive priority levels between course paths, constructs the course path logic under the resource mutual exclusion constraint, and obtains a mutually exclusive relationship course path set;

[0039] The sales service binding module calls the mutually exclusive course path set, screens course combinations whose path coherence score is higher than the path coherence reference value and whose resource mutual exclusivity level is lower than the threshold, lists the corresponding service items in the combined sales item bindable list, and generates a sales path binding service list;

[0040] The service synchronization combination module extracts the resource opening time period and service trigger offset duration in each course unit based on the sales path binding service list, compares the intersection time period length with the configured service activation cycle lower limit, and if it is greater than the cycle lower limit, the course node and service item are synchronously written into the joint scheduling structure to obtain a combined service synchronization schedule.

[0041] Compared with the prior art, the advantages and positive effects of the present invention are:

[0042] In the present invention, by detecting the intersection between the course teaching cycle and the service activation time window, the temporal consistency of the course and service resources is ensured, the risk of resource mismatch is avoided, and the resource utilization warning threshold and overlap rate comparison mechanism are introduced in the service concurrent use scenario to realize the conflict prediction and intervention of high-frequency resource requests. Combined with the course level label and resource configuration density, the resource mutual exclusion relationship between course paths is distinguished and processed, and a clear exclusive priority rule is established to effectively avoid the path interference caused by resource competition. Combined with the path consistency score and service stability parameters, the course and service paths that can be compatible and combined for sale are screened to ensure the logical consistency and operational stability of the overall configuration. By comparing the service trigger offset time with the cycle lower limit of the resource open period, a synchronous scheduling structure is generated to realize the linkage and coordination of service call and course content, thereby improving the service resource scheduling efficiency and personalized delivery accuracy. BRIEF DESCRIPTION OF THE DRAWINGS

[0043] Figure 1 is a flow chart of the method of the present invention;

[0044] Figure 2 A flowchart for obtaining a matching time linkage segment set for the present invention;

[0045] Figure 3 A flowchart of the present invention for obtaining a service conflict prediction node list;

[0046] Figure 4 A flowchart of obtaining a mutually exclusive course path set for the present invention;

[0047] Figure 5 A flowchart for obtaining a sales path binding service list for the present invention;

[0048] Figure 6 This is a flowchart of the present invention for obtaining a combined service synchronization schedule. DETAILED DESCRIPTION

[0049] In order to make the purpose, technical solutions and advantages of the present invention more clearly understood, the present invention will be further described in detail below with reference to the accompanying drawings and embodiments. It should be understood that the specific embodiments described herein are only used to explain the present invention and are not intended to limit the present invention.

[0050] In the description of the present invention, it should be understood that the terms "length", "width", "up", "down", "front", "back", "left", "right", "vertical", "horizontal", "top", "bottom", "inside", "outside", etc., indicating directions or positional relationships, are based on the directions or positional relationships shown in the accompanying drawings and are only for the convenience of describing the present invention and simplifying the description. They do not indicate or imply that the devices or elements referred to must have a specific direction, be constructed and operate in a specific direction, and therefore should not be understood as limiting the present invention. In addition, in the description of the present invention, the meaning of "plurality" is two or more, unless otherwise clearly and specifically defined.

[0051] See also Figure 1 The present invention provides a technical solution: a method based on bundled sales of hosting services and flexible configuration of courses, comprising the following steps:

[0052] S1: Obtain a list of preset course bundles, call the teaching phase number field and the planned teaching cycle field for each course unit in the list, detect the service activation time window and teaching resource open time field in the hosting service supporting item bound to each course node, compare the time interval intersection between the planned teaching cycle and the service activation time window, establish an effective collaborative time structure between the course and the supporting services, and obtain the supporting time linkage segment set;

[0053] S2: Based on the matching time linkage segment set and the recorded time linkage intervals between courses and service items, the service call frequency, resource allocation identifiers in the course units, and resource scheduling priorities within each time segment are obtained. The concurrent occupancy of course nodes that call the same service within the same segment is extracted and compared with the time period overlap rate. It is determined whether the difference between the concurrent occupancy and the maximum resource load value is lower than the resource utilization warning threshold. If so, the managed service node is marked as pending conflict detection state, and a service conflict prediction node list is established.

[0054] S3: Based on the service conflict prediction node list and the managed service nodes with risk tags, the course unit paths bound to the nodes within the corresponding time period are extracted. The course level labels and resource usage density in the course content are obtained. The course level label differences and resource allocation overlap rates between course units are compared. The mutually exclusive priority levels between course paths are divided, and the course path logic with resource mutual exclusion constraints is constructed to obtain a set of mutually exclusive course paths.

[0055] S4: Call the mutually exclusive course path set, obtain the service function scope identifier, path coherence score, and service load stability coefficient of the corresponding bound managed service item based on the course path node, select the course combinations with path coherence scores higher than the path coherence reference value and resource mutual exclusivity levels lower than the threshold, add the corresponding service items to the list of combo sales items that can be bound, and generate a sales path bound service list;

[0056] S5: Based on the sales path-bound service list, according to the selected service items and course nodes, extract the resource open time period and service trigger offset duration in each course unit, calculate the intersection of the two intervals, and compare the intersection time period with the configured service activation cycle lower limit. If the intersection time period is greater than the cycle lower limit, generate a synchronous activation status flag, synchronize the course node and service item into the joint scheduling structure, and obtain the combined service synchronization schedule.

[0057] The supporting time linkage segment set includes the course teaching cycle matching segment, the service activation period boundary value and the time overlap coefficient of the course and service. The service conflict prediction node list includes the high-concurrency service node identifier, the resource load difference calculation value and the conflict status flag. The mutually exclusive relationship course path set includes the course mutual exclusion priority label, the resource coverage intersection identifier between paths and the mutually exclusive rule matching record. The sales path binding service list includes the path scoring sorting results, the resource exclusivity filtering identifier and the service function range matching value. The combined service synchronization scheduling table specifically includes the joint activation signal of the course and service, the synchronously activated time segment and the course service linkage scheduling index.

[0058] See also Figure 2 The specific steps for obtaining the matching time linkage segment set are as follows:

[0059] S111: Obtain a preset course bundle combination list, call the teaching stage number field and the planned teaching cycle field of the course unit in the combination list, extract the teaching sequence information corresponding to the teaching cycle start and end time and stage number of each course unit, establish a time mapping index of the course in the teaching structure, and obtain a teaching cycle structure table;

[0060] Get the preset course bundle combination list, call the teaching stage number field and planned teaching cycle field of each course unit in the combination list, first need to establish an index structure by mapping the course unit number and the teaching stage number one by one, and parse the teaching module sequence and logical relationship corresponding to the stage number. In a typical implementation of an education platform, for example, course unit C101 belongs to teaching stage T01, corresponding to the basic module, and the teaching cycle is set from day 0 to day 4. The corresponding system configuration start and end fields are A start =0, A end=4, and so on. The phase numbers and teaching intervals of all course units in the combined list are extracted and summarized, and then a mapping set from course phases to specific time axes is established. It is necessary to consider whether there is a serial dependency relationship between courses. For example, if phase T02 needs to start 2 days after the end of T01, a time offset value ΔA = 2 days needs to be introduced into the mapping structure to adjust the cycle. After integrating the time interval information in sequence, a unified timeline index is formed. In this process, each course unit will have a one-to-one corresponding start and end time period, so that time overlap analysis can be performed when judging the service matching relationship later. As shown in Table 1, the teaching start and end intervals and service activation time intervals of course units C101–C104 correspond to 0-4 days, 5-9 days, 10-14 days, and 15-19 days, respectively. The established mapping structure uses course units as indexes, configures phase logical relationships and time labels, and finally obtains a teaching cycle structure table.

[0061] Table 1 Course service time matching table:

[0062]

[0063] As shown in Table 1, there is a correlation between course nodes and service activation cycles.

[0064] S112: Based on the teaching cycle structure table, detect the service activation time window and course resource open time fields in the hosting service supporting items bound to the course unit, calculate the intersection of the teaching cycle interval and the service activation time window interval of each course unit, and select course service pairs with overlapping time intervals to obtain a set of overlapping time intervals;

[0065] Based on the teaching cycle structure table, detect the service activation time window and course resource opening time fields in the hosting service supporting items bound to the course unit. It is necessary to compare the course teaching cycle and the service activation window time period one by one to see if there is an overlap. The specific operation is to extract the starting value of the teaching interval corresponding to each course unit and compare it with the service starting value. If the service activation start time is earlier than the teaching cycle end time and the service activation end time is later than the teaching cycle start time, there is a valid intersection. The starting point and end point of the intersection need to be recorded and saved in the time overlap pair. For example, the teaching cycle of course C101 is A start =0, A end =4, the service activation start and end time is B start =3, B end=7, the intersection interval is 3-4 days, and the length is 2 days; the teaching period of course C103 is 10-14 days, and the service activation period is 11-16 days, the intersection is 11-14 days, and the length is 4 days. The lower limit of the intersection configured by the system is set to θ=1 day. This value is set based on the minimum resource usage time required for the shortest teaching unit of the course. Considering that the minimum teaching task on the platform takes about 1 day, if the actual service coverage period is less than this time, the call requirement cannot be met. Therefore, 1 day is used as the benchmark threshold. Any record with an intersection length of less than 1 day is considered invalid. For example, the teaching period of course C105 is 1-2 days, the service activation period is 2-3 days, the intersection is 2 days, and only 1 hour is considered to not meet the threshold requirement and is therefore excluded from the overlapping interval set. Finally, all qualified course service pairs and their intersection time records are numbered to obtain the time overlapping interval set.

[0066] S113: Based on the time overlapping interval set, according to the time intersection range of the course service pair, combined with the course node number and time segment identification field in the teaching cycle structure table, a binding mapping is established between the course and the hosting service on the resource usage time axis to obtain a matching time linkage segment set;

[0067] Based on the time intersection range of each course service pair in the time overlap interval set, combined with the course node number and time segment identifier fields in the teaching cycle structure table, the above valid intersection time and course node binding structure needs to be integrated into a set of mapping structures. The operation steps include: assigning unique identification codes such as T1, T2, etc. to the intersection segments, writing these identification codes into the corresponding course service pair records, and then establishing a ternary binding between the course node number, its corresponding service number, and the intersection time segment. Further, the course service time linkage structure is constructed. For example, if course C102 is bound to service S102, the intersection segment is 6-9 days, and the corresponding time segment is identified as T3, the record item is (C102, S102, T3). The system uses a mapping storage structure for writing to ensure the efficiency of query and update operations. Finally, all records are integrated to generate a set of matching time linkage segments. The time segment overlap structure configuration in this step does not involve new coefficients, but all course nodes must establish corresponding teaching resource usage time axes to form a complete linkage sequence to support subsequent scheduling calls.

[0068] See also Figure 3 ,The specific steps for obtaining the service conflict prediction node list are:

[0069] S211: Based on the matching time linkage segment set, extract the course service time linkage interval field and the corresponding course unit identifier in each linkage record, collect service call records of the course unit-bound managed service items in each linkage segment, extract the call count field per unit time from the records, summarize and measure the service call frequency values ​​within the same linkage segment, and obtain the segment service call frequency value;

[0070] Get the matching time linkage segment set, extract the course service time linkage interval field and the corresponding course unit identifier in each linkage record, read the time linkage field in the structure one by one according to the course service combination mapping table, and obtain the resource start and end time matched by each course node. If C201 is bound to service node S3, and its linkage interval is from the 6th to the 10th day, then its mapping item should be written as (C201, S3, [6, 10]), then detect the course binding relationship in each linkage segment, and extract the call record of unit time granularity from the corresponding hosting service system call log. Usually, the access frequency field C is extracted with the minimum granularity of hour. ij , the number of calls per hour is accumulated to form the average number of concurrent requests per day. In a typical platform, for example, if the course C201 records the following requests on the S3 node from the 6th to the 10th day: [4, 5, 3, 6, 2], the total number is 20, and the average concurrent call frequency is 4 times / day, that is, C ij =4, organize the statistical value into the mapping structure, and normalize the call frequency of each course under all the same nodes, uniformly define the maximum value of the ratio benchmark as 1, and calculate the normalized ratio of other values ​​according to the actual proportion. If the maximum frequency is 8, then the frequency ratio of the course is 4 / 8=0.5, that is, the normalized value C ij =0.5, as shown in Table 2.

[0071] Table 2 Normalized value table of call frequency of course units in service nodes:

[0072]

[0073] See Table 2. The normalized frequency value has become the input factor for subsequent risk assessment, and the segment service call frequency value is finally generated according to the above process.

[0074] S212: Based on the segment service call frequency value, call the resource allocation identification field and resource scheduling priority field in the course unit data structure, extract the list of course units bound to the same service node, locate the interval value between the service call time and the resource binding time, and use the formula:

[0075]

[0076] Calculate the remaining resource risk and determine whether it is greater than the resource utilization warning threshold. If so, mark the service node as a pending conflict node and generate a resource conflict risk interval.

[0077] Among them, D j represents the remaining risk of resources of service node j, C ij P represents the normalized value of concurrent calls per unit time of course unit i on node j,ij A dimensionless scalar representing the resource scheduling priority of course unit i, S j represents the normalized value of the maximum resource carrying capacity of service node j, F ij represents the normalized value of the resource binding time period length of course unit i on node j, α is the call density adjustment coefficient, and β is the redundancy compensation constant, which is used to prevent the logarithmic denominator from approaching zero;

[0078] Based on the segment service call frequency value, the resource allocation identification field and resource scheduling priority field in the course unit data structure are called to extract all course units bound to the same service node and locate the resource usage segment length F of each course. ij , and extract the course scheduling priority field and convert it into a normalized score P ij Taking the five-level scheduling system as an example, the highest priority can be set to 5, with a corresponding normalized value of 1. The remaining levels are 0.8, 0.6, 0.4, and 0.2, respectively. The information of each course is put into the following formula to calculate the remaining risk of resources:

[0079]

[0080] Among them, D j Indicates the remaining risk of the resources of service node j, reflecting the pressure of the current bound courses of the node on the resource load. represents the traversal and summation operation of all bound course units i at node j;

[0081] C ij is the normalized value of the number of concurrent calls per unit time for course unit i on service node j. After eliminating the dimension, this value represents the relative call density.

[0082] P ij is the dimensionless value of resource scheduling priority of course unit i, reflecting its scheduling sensitivity to resource occupancy, with the highest level set to 1 and the lowest level set to 0.2;

[0083] The purpose of using is to suppress the absolute value inflation effect caused by too high a scheduling priority. By squaring the scheduling level, we can prevent high-priority tasks from dominating the scoring.

[0084] α is the call density adjustment coefficient, which is used to unify the scheduling scoring scale. In this implementation, it is set to 1.5 and adjusted according to the average concurrent pressure of the platform course nodes;

[0085] S j is the normalized value of the maximum resource carrying value of service node j, reflecting its peak processing capacity, and the dimension has been normalized;

[0086] F ijThe normalized value of the resource binding time period length of course unit i on service node j, indicating the duration of resources required for the course on this node;

[0087] β is the redundancy compensation constant, which is set to 2 in this scheme to avoid (S j -F ij ) approaches zero, making the ln function uncomputable.

[0088] Operational Structure: This formula uses a fractional structure. The numerator is the resource pressure imposed by the course on the node, which is the product of the call frequency and the scheduling level. The coefficient is then adjusted to amplify the sensitivity of the node's resources. The denominator is the logarithm of the service node's remaining resource range, indicating the degree of contraction of the node's remaining capacity under the current load. The smaller the value, the greater the resource shortage. By integrating the above structure and performing a weighted summation item by item, the overall remaining resource pressure of a service node, namely the remaining resource risk, is obtained.

[0089] The benefit of the formula is that by The method suppresses the scheduling priority amplification deviation and combines ln(S j -F ij +β) performs logarithmic compression on the resource occupancy intensity. After weighted aggregation, it can refine the description of the node resource allocation risk in the resource bottleneck scenario, thereby improving the system's ability to perceive and distinguish resource conflict risks.

[0090] In the actual example, the service node S j =10, Course Unit C ij =0.5, P ij =0.8, F ij =4, and we can get the following formula:

[0091]

[0092] The system sets the resource utilization warning threshold to θ = 0.25. This value sets the standard fluctuation upper limit of the concurrent scheduling difference of the reference node. It is based on the standard deviation multiple of the node's maximum average call volume. θ = 0.25 is an empirical upper limit setting.

[0093] The result shows that the risk value of service node j under the current course binding structure is 0.322, which is higher than the warning threshold of 0.25. The node needs to be marked as a resource conflict risk and avoidance measures should be taken in subsequent scheduling. This value is the basis for the subsequent calculation of the resource conflict risk interval, which directly drives the screening and structure recording operations of the conflict pending nodes.

[0094] S213: Based on the resource conflict risk interval and the marked service node numbers, establish a course service pair relationship for nodes that are determined to be in a high-risk conflict state in the time linkage section, organize the course coverage, time location information, and resource risk values ​​of the conflicting nodes, summarize and organize the conflicting course service node groups, and establish a service conflict prediction node list;

[0095] According to the service node number marked in the resource conflict risk interval, the corresponding course path in the time linkage structure is traversed in sequence by node, and the course combination path corresponding to the risk node is established. Its path index information, course number and course coverage time period are summarized. For example, after S3 is marked as a risk node, its subordinate courses C201 and C202 both enter the conflict detection process. The time segments are 6-10 days and 9-13 days respectively, and the intersection is 9-10 days, which can be encoded as the conflict segment T c1 , the course paths involving this section are classified into conflict path groups, and then the risk results of each course are extracted, and their risk values ​​and source path labels are recorded respectively. Finally, a structured identification table is formed to obtain a list of service conflict prediction nodes.

[0096] See also Figure 4 , the specific steps for obtaining the mutually exclusive course path set are:

[0097] S311: Based on the service conflict prediction node list, according to the marked hosting service node number, extract the course unit path bound to the node in the corresponding time period, collect the path sequence number and bound service time period field of each course unit in the course path, classify the course path structure in chronological order, and obtain the course service path index table;

[0098] According to the managed service node number marked in the service conflict prediction node list, the course unit path bound to the node in the corresponding period is extracted, the path sequence number and the bound service time period field of each course unit in the course path are collected, the course path structure is classified in chronological order, the path number field and the course unit ID field in the preset course service data structure are called, the course service path records are screened one by one, each bound node number is aggregated and matched with the path number in the associated course unit path, the activation time and expiration time in the service time period field corresponding to the course unit are extracted, and converted into a standard timestamp in minutes, and the time is calculated based on the path sequence number field. The segments are arranged in ascending order, a time series mapping is constructed, and the time series mapping table is correspondingly integrated with the course unit path set to form a course service path record arranged in path order. During the acquisition process, for example, node A contains courses C1, C3, and C5, which have path numbers 1, 2, and 3, respectively, with activation times of 60, 130, and 200 minutes, and expiration times of 120, 180, and 260 minutes. After the path structure is classified, a time series index is formed, such as: [(C1, 60–120), (C3, 130–180), (C5, 200–260)]. This mapping table is the course service path index table, and the course service path index table is obtained.

[0099] S312: Call the course service path index table, collect the course level label and resource usage density value in each course unit, and filter the course pairs that exist under the conflicting service node and have adjacent path numbers, using the formula:

[0100]

[0101] The operation obtains the resource mutual exclusion tensor value between the course pairs, uses the tensor value as the scoring indicator of the course path mutual exclusion level, sets the grading boundary after sorting by the tensor value, and generates the course path mutual exclusion level sequence;

[0102] Among them, M fk Indicates the resource mutual exclusion value between course unit f and course unit k, L f Indicates the course level label value of course unit f, L k Represents the course level label value of course unit k, R f represents the normalized value of resource usage density of course unit f, R k represents the normalized value of resource usage density of course unit k, Tf represents the midpoint of resource usage time of course unit f, and T k represents the midpoint of resource usage time of course unit k, γ represents the density product compensation factor, and δ represents the time interval sensitivity coefficient;

[0103] Call the course service path index table, collect the course level label and resource usage density value in each course unit, filter the course pairs that exist under the conflicting service node and have adjacent path numbers, compare the course level label differences and resource usage density one by one, extract the start and end values ​​of the time period recorded in the resource usage time field, and calculate the time midpoint value For example, if the resource usage time for a course unit is 60–120 minutes, the midpoint is 90 minutes, and the following formula is used:

[0104]

[0105] Perform mutually exclusive tensor value calculations. Here, γ is set to 0.05 to prevent the density multiplication denominator from being too small to affect the stability of the operation. δ is set to 0.02 to map the linear impact of the time midpoint difference on the tensor value. If the levels of courses C1 and C2 are 4 and 2 respectively, the resource usage density is 0.8 and 0.6 respectively, and the usage time midpoint is 90 minutes and 140 minutes respectively, then substitute into the formula:

[0106]

[0107] The mutually exclusive tensor value is 3.693. This tensor value is used as the scoring indicator for the mutually exclusive grade of course paths. All course pairs are sorted from high to low according to their scoring values, and the grading boundaries are set at equal intervals between adjacent intervals. The grade labels are divided (such as high, medium, and low mutually exclusive grades) to generate a mutually exclusive grade sequence for course paths.

[0108] Formula description: In this formula, |·| means taking the absolute value, reflecting the uniform treatment of positive and negative offsets. represents the equilibrium value of the product of course resource usage density, γ plays a compensatory role to avoid the denominator being too small due to too low density, δ·|T f -T k |Measures the temporal impact of midpoint differences in resource usage time on resource conflicts. The formula is beneficial in that it quantifies the conflict risk of course pairs by combining normalized harmonization of density differences with linear weighting of time intervals, forming a sortable and graded mutual exclusion tension index. The result shows that the larger the tension value between course pairs, the greater the degree of overlap in resource usage time and resource load, and the more concentrated the risk. Subsequent scheduling should prioritize the elimination or readjustment of their service binding relationships. The score value serves as the basis for the mutual exclusion level division, which directly corresponds to the generation of the mutual exclusion level sequence of course paths.

[0109] S313: Based on the mutually exclusive grade sequence of course paths, the mutually exclusive grade values ​​are mapped to the path order according to the marked course paths, a mutually exclusive grade correspondence table between course paths is constructed, resource sharing boundaries, temporal logic relationships, and mutually exclusive grade classification labels between path groups are sorted, and a mutually exclusive course path set is established;

[0110] According to the mapping relationship between the mutually exclusive scoring values ​​and path sequences of the course path pairs marked in the mutually exclusive grade sequence of the course paths, the course path pairs with scores higher than the limit value in the mutually exclusive grade are extracted one by one, and their path number fields are combined in pairs to construct a set of high mutually exclusive grade path pairs. The course service path index table is then called to obtain the resource usage density field and resource usage time field of each course unit in the path pair. The time segment and resource binding service node number are extracted to form the resource sharing boundary field, and the mutually exclusive grade label is additionally annotated. The path groups with the same resource binding nodes, overlapping time spans and mutually exclusive scores higher than the average value in the same course path group are classified, and the classification number and mutually exclusive grade label are output. A mutually exclusive relationship matrix is ​​established for each group of data. Each item in the matrix stores the resource overlapping boundary, time sequence dependency and mutually exclusive grade index value of the course path pair. The matrix is ​​recorded and a structural mapping is established to establish a mutually exclusive relationship course path set.

[0111] See also Figure 5 The specific steps for obtaining the sales path binding service list are as follows:

[0112] S411: Calling a mutually exclusive course path set, extracting the service function range identification field in the managed service item bound to the path node based on the course path node, combining the course path sequence record with the path node unique identification value, establishing a course path and service function correspondence structure, and obtaining a service function mapping table;

[0113] Call the course path nodes in the mutually exclusive course path set, extract the service function range identification field in the managed service item bound to each path node, combine the course path sequence record and the path node unique identification value, and build a service function mapping relationship structure. During the execution process, first call the node ID field and sorting field of each path node in the course path structure table, sort them in ascending order according to the path sequence field, extract the managed service ID field bound to each path node and further collect the function range identification item in the service item. The function range identification field is a four-bit code used to represent Indicates the teaching task category supported by the service. For example, "1001" represents the course resource access service, "2002" represents the assessment record synchronization service, etc. The unique identification value of the path node is bound and paired with the service function identifier to form a one-to-one mapping between the path node and the function identifier. In actual operation, for example, the path node IDs are C01, C02, and C03, and the service IDs S01, S02, and S03 are bound respectively. The function identifier of S01 is "1001", S02 is "2002", and S03 is "3003". The structure formed in the mapping table is as follows:

[0114] {C01:1001,C02:2002,C03:3003}, get the service function mapping table.

[0115] S412: Based on the service function mapping table and the service function path relationship, the path coherence score value of the course path node and the resource load stability coefficient field of the service item are extracted, and the course service binding pairs whose course path score value is greater than the path coherence reference value and whose resource mutual exclusion level is lower than the threshold value are screened using the formula:

[0116]

[0117] Obtain the bound service fitness scores of the course path pairs through calculation, sort and number them from high to low according to the score results, and generate service fitness ranking information;

[0118] Among them, B zp represents the binding service fitness score of course path z and service item p, Q z represents the normalized value of the path coherence score of course path z, U z represents the normalized value of the resource load stability coefficient on course path z, V z V represents the normalized value of resource exclusiveness level of course path z. p represents the normalized index of the mutual exclusion impact sensitivity of service item p, ∈ is the score base balance constant, which is used to suppress the abnormal interference of mutual exclusion fluctuations in the score;

[0119] According to the service function path relationship in the service function mapping table, the path coherence score value of the course path node and the resource load stability coefficient field of the service item are extracted. The course service binding pairs whose course path score value is greater than the path coherence reference value and the resource mutual exclusivity level is lower than the threshold value are screened. The path coherence reference value is set to 0.6, and the resource mutual exclusivity level threshold value is 0.75. The coherence score and mutual exclusivity level have been normalized. After the screening is completed, the service fitness of each course path and service binding pair is calculated using the formula:

[0120]

[0121] Here, ∈ is set to 0.05. In this example, the coherence score Q of path Z1 is z =0.8, resource load stability coefficient U z =0.64, the resource mutual exclusion level is V z =0.35, the mutual exclusion impact sensitivity of the corresponding service item is V p =0.42, substitute into the formula to calculate:

[0122]

[0123] After sorting, they are numbered in order according to the scores, and the top 10% are selected as priority recommendations to generate service fitness ranking information.

[0124] Formula description: In this formula, the multiplication part Used to comprehensively reflect the stability and continuity of the path, the denominator is 1+|V z -V p |+∈ suppresses abnormal scoring deviations caused by mutually exclusive interference. The benefit of the formula is that it suppresses and balances the scoring structure by introducing the mutually exclusive sensitivity difference between paths and services, strengthening the recommendation priority of high-coherence and high-load stable paths. The scoring value directly reflects the level of coordinated adaptability of the path and service combination; the result shows that the higher the scoring value, the more suitable its path combination structure is for recommending sales service combination configuration, and it will be directly introduced into the sales list structure as a recommended item in the future.

[0125] S413: Based on the service fitness ranking information, according to the course paths and service binding records in the priority screening section, the structural sequence number, functional scope label, and path matching relationship of the bound service items are extracted, and a sales recommendation item combination structure between the course paths and configurable services is constructed to obtain a sales path binding service list;

[0126] According to the course path and service binding records in the screening priority section of the service fitness ranking information, the structural serial number, functional scope label and path matching relationship of the bound service item are extracted. The first five groups of data in the ranking result are collected, and their service structure serial number, path node number and service function identifier are read. The same type of functional service items are aggregated uniformly through the structural serial number. For example, the serial number "S-FUNC-01" represents access services, and "S-FUNC-02" represents shared cache services. In the constructed structure, the course path node number is used as the first-level index, the structural serial number is used as the service dimension index, and the path matching item is a Boolean field indicating whether the course node has the corresponding service call permission. The mapping relationship table between the course path nodes and service items is summarized and entered into the recommended sales portfolio structure, as shown in Table 3:

[0127] Table 3. Recommended mapping table of course path nodes and service functions

[0128] Course path node number Service structure serial number Functional scope label Path matching value C01 S-FUNC-01 Course resource access True C02 S-FUNC-03 Teaching progress control True C03 S-FUNC-04 Service hours synchronization False C04 S-FUNC-02 Status cache update True

[0129] As shown in Table 3, based on the combination of course paths and service items extracted from the priority ranking segments, a three-dimensional mapping matrix of path structure-service label-adaptation status is formed, and a sales path binding service list is obtained.

[0130] See also Figure 6 ,The specific steps for obtaining the composite service synchronization schedule are:

[0131] S511: Based on the sales path binding service list, according to the filtered service items and course nodes, extract the resource opening start and end time fields and the service trigger offset duration fields recorded in each course unit, establish a time period correspondence table based on the course and service binding relationship, establish a time period set for each course service pair, and generate a course service time period comparison table;

[0132] Based on the filtered service items and course nodes in the sales path binding service list, the course unit data record table is read, and the resource opening start time field value and end time field value in each course unit are extracted to establish a start-end time mapping. The extraction method is to obtain a timestamp sequence by reading the fields "ResOpenStart" and "ResOpenEnd". At the same time, the service trigger offset field "TriggerOffset" is extracted from the bound service item record. The field value unit is minutes, and offset correction processing is required. That is, the offset is added to the course start time or service start time by setting an offset calculation benchmark to form a unified alignment structure. The time period correspondence table structure is established based on the one-to-one binding method between services and courses, and the course ID "CID", service ID "SID" and binding time period label are recorded. Multiple records are combined to form a course service time period set. For example, if the binding time period between course A and service S1 is 08:00-10:00, the service offset is corrected by 15 minutes to form a valid intersection range of 08:15-10:00. This data row is written to the structure table to form a course service time period comparison table, as shown in Table 4.

[0133] Table 4 Course service time period comparison table

[0134] CID SID ResOpenStart ResOpenEnd TriggerOffset(min) Corrected service time period C101 S001 08:00 10:00 15 08:15–10:00 C102 S002 09:00 11:00 10 09:10–11:00

[0135] As shown in Table 4, the course service time period comparison table clearly records the course resource opening interval and the service offset correction interval. A separate entry record is established for each pair of course service items to ensure that the time period data is independently identifiable and provide a clear data source for subsequent intersection interval judgment.

[0136] S512: Based on the course service time period comparison table, the intersection intervals between the course resource open time period and the service trigger offset correction time period are calculated, the start and end times of the intersection intervals are extracted, and the interval length is measured. The measured interval length value is compared with the configured service activation period lower limit to obtain the course service activation determination result;

[0137] According to each set of course resource opening time periods and service trigger offset correction time periods recorded in the course service time period comparison table, the minimum and maximum values ​​of the start and end time fields are calculated respectively to determine the interval intersection. If the course opening time is 08:00–10:00 and the service trigger interval is 08:15–10:00, the intersection start time is 08:15 and the end time is 10:00, and the intersection interval length is 105 minutes. The interval length is calculated using the min(End)-max(Start) operation format and the obtained intersection interval length is compared with the lower limit of the configured service activation period. The lower limit of the activation cycle is 60 minutes. This threshold is set based on the system's minimum valid service execution window, with a range of 30–90 minutes. This system uses the median value of 60 minutes for uniform adaptability. The judgment process is as follows: if the intersection interval length ≥ the lower limit, the activation condition is marked as "met," otherwise, it is marked as "not met." For example, if the intersection interval of course C101 is 105 minutes, the condition is met and is marked as "1." If the intersection interval of course C102 is 50 minutes, the condition is not met and is marked as "0." This determines the course service activation result. This result indicates whether the time period matching between the course and service is feasible for simultaneous activation, which is the prerequisite for establishing a subsequent synchronization schedule.

[0138] S513: Based on the course service activation determination result, for each course service pair whose intersection period length is greater than the lower limit of the service activation period, mark the synchronization activation status, write the corresponding course node number and service item structure number into the joint schedule record, and establish a combined service synchronization schedule;

[0139] The activation result of the course service is called, and for all course service pairs marked as "1", the course node number field "CID" and the service structure number field "SID" are extracted, and written into the unified joint scheduling structure table in record order, including the course node number, service number, resource binding tag, scheduling time range, and synchronization activation flag field. Before writing, the activation flag mark field value is set to "Y" according to the overlapping area of the course and the service on the time axis, forming a joint scheduling item with a binding structure and time consistency. For example, if course C101 and S001 are marked as an activated course service pair, the binding relationship is written into the scheduling table structure field. The structure field is set as follows: the CID field is "C101", the SID field is "S001", the synchronization flag field value is "Y", and the modified time section "08:15-10:00" is written. Each record establishes an independent scheduling structure row, and finally all course service pairs that meet the conditions are summarized to form a combined service synchronization scheduling table, which is used to drive resource scheduling logic and subsequent execution scheduling sequence output. The result represents the joint binding execution relationship of all courses and services under the condition of time synchronization activation, which is an important structural data basis for the system to complete resource coordination scheduling.

[0140] A system based on bundled sales of managed services and flexible configuration of courses, which is used to implement the above-mentioned method based on bundled sales of managed services and flexible configuration of courses. The system comprises:

[0141] The time linkage analysis module obtains a preset course bundle combination list, compares the time interval intersection between the planned teaching period and the service activation time window, establishes the effective cooperation time structure between the course and the supporting service, and obtains a supporting time linkage section set;

[0142] The conflict state detection module extracts the concurrent occupancy and time period overlap rate of course nodes calling the same service in the same section based on the supporting time linkage section set, judges whether the difference between the concurrent occupancy and the maximum carrying value of the resource is lower than the resource utilization warning threshold, and marks it as a conflict detection state, and establishes a service conflict prediction node list;

[0143] The mutual exclusion relationship identification module obtains the course level label and resource use density in the course content based on the service conflict prediction node list, divides the mutual exclusion priority level between the course paths, constructs the course path logic under the constraint of resource mutual exclusion, and obtains a mutual exclusion relationship course path set;

[0144] The sales service binding module calls the mutual exclusion relationship course path set, filters the course combination with a path coherence score higher than the path coherence reference value and a resource mutual exclusion level lower than the threshold, and lists the corresponding service items in the combination sales item bindable list, and generates a sales path binding service list.

[0145] The service synchronization combination module binds the service list based on the sales path, extracts the resource opening time period and the service trigger offset duration in each course unit, compares the intersection period length with the configured service activation cycle lower limit value, and if greater than the cycle lower limit value, synchronously writes the course node and the service item into the joint scheduling structure to obtain a combined service synchronization scheduling table.

[0146] The above is only a preferred embodiment of the present application, and does not limit the present application in other forms. Any person skilled in the art can use the disclosed technical content to make changes or modifications into equivalent embodiments applied to other fields, but any simple modification, equivalent change and modification made to the above embodiments according to the technical essence of the present application without departing from the technical solution content of the present application still belongs to the protection scope of the technical solution of the present application.

Claims

1. A method based on hosting service bundling and flexible course configuration, characterized in that: The following steps are involved: S1: Obtain a list of preset course bundles, compare the time interval intersection between the planned teaching cycle and the service activation time window, establish an effective collaborative time structure between the course and the supporting services, and obtain a set of supporting time linkage segments; S2: Based on the matching time linkage segment set, the concurrent occupancy of the course nodes that call the same service in the same segment is extracted and compared with the time period overlap rate. It is determined whether the difference between the concurrent occupancy and the maximum resource load value is lower than the resource utilization warning threshold. The nodes are marked as pending conflict detection status and a service conflict prediction node list is established. S3: Based on the service conflict prediction node list, obtain the course level label and resource usage density in the course content, divide the mutually exclusive priority levels between course paths, construct the course path logic under the resource mutual exclusion constraint, and obtain the mutually exclusive relationship course path set; S4: Call the mutually exclusive course path set, screen the course combinations whose path coherence score value is higher than the path coherence reference value and whose resource mutual exclusivity level is lower than the threshold, add the corresponding service items to the list of combinatorial sales items that can be bound, and generate a sales path binding service list.

2. The method based on hosting service bundling and flexible course configuration according to claim 1, characterized in that: The supporting time linkage segment set includes the course teaching cycle matching segment, the service activation period boundary value and the time overlap coefficient between the course and the service; the service conflict prediction node list includes the high concurrency service node identifier, the resource load difference calculation value and the conflict status flag; the mutually exclusive relationship course path set includes the course mutual exclusion priority label, the resource coverage intersection identifier between paths and the mutual exclusion rule matching record; the sales path binding service list includes the path scoring sorting result, the resource exclusivity filtering identifier and the service function range matching value.

3. The method based on hosting service bundling and flexible course configuration according to claim 2, characterized in that: The steps for obtaining the matching time linkage segment set are as follows: S111: Obtain a preset course bundle combination list, call the teaching stage number field and the planned teaching cycle field of the course unit in the combination list, extract the teaching sequence information corresponding to the teaching cycle start and end time and stage number of each course unit, establish a time mapping index of the course in the teaching structure, and obtain a teaching cycle structure table; S112: Based on the teaching cycle structure table, detect the service activation time window and course resource open time fields in the hosting service supporting items bound to the course unit, calculate the intersection of the teaching cycle interval and the service activation time window interval of each course unit, and select course service pairs with overlapping time intervals to obtain a set of overlapping time intervals; S113: Based on the time overlapping interval set, according to the time intersection range of the course service pair, combined with the course node number and time segment identification field in the teaching cycle structure table, a binding mapping between the course and the hosting service on the resource usage timeline is established to obtain a matching time linkage segment set.

4. The method based on hosting service bundling and flexible course configuration according to claim 3, characterized in that: The steps for obtaining the service conflict prediction node list are specifically as follows: S211: Based on the matching time linkage segment set, extract the course service time linkage interval field and the corresponding course unit identifier in each linkage record, collect service call records of the course unit-bound managed service item in each linkage segment, extract the call count field per unit time from the record, summarize and measure the service call frequency values ​​within the same linkage segment, and obtain the segment service call frequency value; S212: Based on the segment service call frequency value, the resource allocation identification field and the resource scheduling priority field in the course unit data structure are called to extract a list of course units bound to the same service node, locate the interval value between the service call time and the resource binding time, calculate and obtain the resource remaining risk, and determine whether the resource remaining risk is greater than the resource utilization warning threshold. If so, the service node is marked as a conflict pending node, and a resource conflict risk interval is generated; S213: Based on the resource conflict risk interval and according to the marked service node numbers, establish a course service pair relationship in which the nodes are judged to be in a high-risk conflict state in the time linkage section, organize the course coverage, time positioning information and resource risk values ​​of the conflicting nodes, summarize and organize the conflicting course service node groups, and establish a service conflict prediction node list.

5. The method based on hosting service bundling and flexible course configuration according to claim 4, characterized in that: The specific steps for obtaining the mutually exclusive course path set are: S311: Based on the service conflict prediction node list, according to the marked hosting service node number, extract the course unit path bound to the node in the corresponding time period, collect the path sequence number and bound service time period field of each course unit in the course path, classify the course path structure in chronological order, and obtain a course service path index table; S312: Call the course service path index table, collect the course grade label and resource usage density value in each course unit, screen the course pairs that exist under the conflicting service node and have adjacent path numbers, calculate and obtain the resource mutual exclusion degree value between the course pairs, use the degree value as the course path mutual exclusion grade scoring indicator, sort by degree value and set the grade boundary, and generate the course path mutual exclusion grade sequence; S313: Based on the mutually exclusive grade sequence of the course paths, according to the mapping relationship between the mutually exclusive scoring values ​​and the path sequence of the marked course paths, a mutually exclusive graded correspondence table between course paths is constructed, the resource sharing boundaries, temporal logic relationships and mutually exclusive grade classification labels between path groups are sorted out, and a mutually exclusive relationship course path set is established.

6. The method based on hosting service bundling and flexible course configuration according to claim 5, characterized in that: The steps for obtaining the sales path binding service list are as follows: S411: Calling the mutually exclusive course path set, extracting the service function range identification field in the managed service item bound to the path node based on the course path node, combining the course path sequence record and the path node unique identification value, establishing a course path and service function correspondence structure, and obtaining a service function mapping table; S412: Based on the service function mapping table and the service function path relationship, the path coherence score value of the course path node and the resource load stability coefficient field of the service item are extracted, and the course service binding pairs whose course path score value is greater than the path coherence reference value and whose resource mutual exclusivity level is lower than the threshold value are screened. The binding service fitness scores of the course path pairs are calculated and obtained. The scores are sorted from high to low and numbered to generate service fitness ranking information; S413: Based on the service fitness ranking information, according to the course path and service binding records located in the screening priority section, the structural serial number, functional scope label and path matching relationship of the bound service item are extracted, and a sales recommendation item combination structure between the course path and the configurable service is constructed to obtain a sales path binding service list.

7. The method based on hosting service bundling and flexible course configuration according to claim 6, characterized in that: The method further comprises the following steps: S5: Based on the sales path bound service list, extract the resource open time period and service trigger offset duration in each course unit, compare the intersection time period length with the configured service activation cycle lower limit, and if it is greater than the cycle lower limit, synchronously write the course node and service item into the joint scheduling structure to obtain the combined service synchronization schedule; The combined service synchronization schedule specifically includes a course and service joint activation signal, a synchronously activated time period, and a course service linkage scheduling index.

8. The method based on hosting service bundling and flexible course configuration according to claim 7, characterized in that: The steps for obtaining the composite service synchronization schedule are specifically as follows: S511: Based on the sales path binding service list, according to the filtered service items and course nodes, extract the resource opening start and end time fields and the service trigger offset duration fields recorded in each course unit, establish a time period correspondence table based on the course and service binding relationship, establish a time period set for each course service pair, and generate a course service time period comparison table; S512: Based on the course service time period comparison table, the intersection intervals between the course resource open time period and the service trigger offset correction time period are calculated, the start and end times of the intersection intervals are extracted, and the interval lengths are measured. The measured interval lengths are compared with the configured service activation period lower limit to obtain a course service activation determination result. S513: Based on the course service activation judgment result, according to the course service pairs whose intersection time period length is greater than the lower limit of the service activation cycle, mark the synchronization activation status, write the corresponding course node number and service item structure number into the joint scheduling table record, and establish a combined service synchronization scheduling table.

9. A system based on hosting service bundling and flexible course configuration, characterized by: The system is used to implement the method based on hosting service bundled sales and flexible course configuration according to any one of claims 1 to 8, and the system includes: The time linkage analysis module obtains a list of preset course bundles, compares the time interval intersection between the planned teaching cycle and the service activation time window, establishes an effective collaborative time structure between the course and the supporting services, and obtains a set of supporting time linkage segments; The conflict status detection module extracts the concurrent occupancy of the course nodes that call the same service in the same segment and compares it with the time period overlap rate based on the supporting time linkage segment set, determines whether the difference between the concurrent occupancy and the maximum resource load value is lower than the resource utilization warning threshold, marks it as a pending conflict detection state, and establishes a service conflict prediction node list; The mutually exclusive relationship identification module obtains the course level label and resource usage density in the course content based on the service conflict prediction node list, divides the mutually exclusive priority levels between course paths, constructs the course path logic under the resource mutual exclusion constraint, and obtains a mutually exclusive relationship course path set; The sales service binding module calls the mutually exclusive course path set, screens course combinations whose path coherence score is higher than the path coherence reference value and whose resource mutual exclusivity level is lower than the threshold, lists the corresponding service items in the combined sales item bindable list, and generates a sales path binding service list; The service synchronization combination module extracts the resource opening time period and service trigger offset duration in each course unit based on the sales path binding service list, compares the intersection time period length with the configured service activation cycle lower limit, and if it is greater than the cycle lower limit, the course node and service item are synchronously written into the joint scheduling structure to obtain a combined service synchronization schedule.

Images