Service function configuration method and device, equipment and storage medium

Abstract

The invention discloses a service function configuration method and device, equipment and a storage medium, and relates to the technical field of smart communities, and the method comprises the steps: determining matching demand points corresponding to service functions, and determining the function matching degree of the service functions according to a matching degree coefficient determination rule and the number of the matching demand points corresponding to the service functions; determining elastic demand information between a current demand point and each matched demand point, wherein the current demand point is any demand point except the matched demand point in the current region; determining a matching result of the current demand point and the service function according to the elastic demand information between the current demand point and each matched demand point and the function matching degree of the service function; and when the matching result is determined to be matched, configuring the service function to the current demand point. According to the technical scheme, the service function is configured to the demand point actually needing the service function, the service expenditure is reduced while the resident service experience is improved, and the service function configuration effect is improved.

Description

Technical Field

[0001] Embodiments of the present invention relate to the field of smart community technology, and in particular, to a method, device, equipment and storage medium for configuring a service function. Background Art

[0002] With the continuous growth of urban population and the increasingly developed urbanization, the problem of "urban diseases" in some areas is becoming increasingly serious. In order to solve the problems of urban development and achieve sustainable urban development, building smart cities has become an irreversible historical trend in urban development today. Smart communities are an important part of smart cities. Smart communities can use the Internet and even the Internet of Things technology to provide residents with convenient and timely services in medical care, property, business (for example, express delivery stations, online shopping stores, traditional stores, food wholesale and vegetable markets) and smart homes. The reasonable configuration of service functions plays an important role in improving the operating efficiency of smart communities. Therefore, how to configure service functions has become a technical problem that needs to be solved urgently.

[0003] In the prior art, a standardized configuration method is generally used to configure service functions for each demand point in a smart city. Service function configuration can also be performed based on the survey results of each demand point.

[0004] However, these methods are difficult to effectively adapt to the complex and diverse needs of smart communities, resulting in poor experience for residents in the community. Summary of the invention

[0005] The present invention provides a method, device, equipment and storage medium for configuring a service function, so as to realize reasonable configuration of the service function.

[0006] In the first aspect, an embodiment of the present invention provides a method for configuring a service function, including: determining a matching demand point corresponding to the service function, and determining the functional matching degree of the service function according to a matching coefficient determination rule and the number of matching demand points corresponding to the service function; determining elastic demand information between a current demand point and each of the matching demand points, wherein the current demand point is any demand point other than the matching demand point in the current area; determining a matching result between the current demand point and the service function according to the elastic demand information between the current demand point and each of the matching demand points and the functional matching degree of the service function; and configuring the service function to the current demand point when it is determined that the matching result is a match.

[0007] The technical solution of an embodiment of the present invention provides a method for configuring a service function, including: determining a matching demand point corresponding to the service function, and determining the functional matching degree of the service function according to a matching coefficient determination rule and the number of matching demand points corresponding to the service function; determining elastic demand information between a current demand point and each of the matching demand points, wherein the current demand point is any demand point other than the matching demand point in the current area; determining a matching result between the current demand point and the service function according to the elastic demand information between the current demand point and each of the matching demand points and the functional matching degree of the service function; and configuring the service function to the current demand point when it is determined that the matching result is a match. The above technical scheme can first determine the matching demand points corresponding to the service function, and secondly determine the matching coefficient corresponding to the service function according to the matching coefficient determination rule and the service scenario to which the service function belongs, and then determine the functional matching degree of the service function according to the number of matching demand points corresponding to the service function and the matching coefficient, so as to determine the matching demand points corresponding to the service function and the functional matching degree of the service function, and can also determine the elastic demand information between the current demand point and the current matching demand point in combination with the demand behavior characteristics and benchmark demand information of the current demand point and each matching demand point, so as to ensure the reliability of the elastic demand information while improving the accuracy, and then determine the matching result of the current demand point and the service function according to the elastic demand information between the current demand point and each matching demand point and the functional matching degree of the service function, and when it is determined that the matching result of the current demand point and the service function is a match, configure the service function to the current demand point, and in the process of configuring the service function, fully consider the differences between the community and the demand points within the community, configure the service function to the demand points that actually need the service function, and reduce the configuration of the service function to the demand points with low demand for the service function, so as to improve the service experience of residents while reducing service expenses, and improve the effect of service function configuration and improve the problem of poor service function adaptation effect.

[0008] Furthermore, the functional matching degree of the service function is determined according to a matching coefficient determination rule and the number of matching demand points corresponding to the service function, including: determining a service scenario of the service function, and determining the matching coefficient of the service function based on the matching coefficient determination rule and the service scenario; determining the functional matching degree of the service function according to the number of matching demand points corresponding to the service function and the matching coefficient.

[0009] Furthermore, the elastic demand information between the current demand point and each of the matching demand points is determined, including: for each of the matching demand points, the baseline demand information between the current demand point and the matching demand point is determined according to the static labels of the current demand point and the matching demand point; the baseline demand information between the current demand point and the matching demand point is updated according to the demand behavior characteristics of the current demand point and the matching demand point to obtain the elastic demand information between the current demand point and the matching demand point.

[0010] Furthermore, the benchmark demand information between the current demand point and the matching demand point is determined based on the static labels of the current demand point and the matching demand point, including: determining a static demand combination of the current demand point and the matching demand point in a demand database based on the static labels of the current demand point and the matching demand point; determining a static label similarity between the current demand point and the matching demand point in a correspondence table between static demand combinations and correlations based on the static demand combination, and determining the static label similarity as the benchmark demand information between the current demand point and the matching demand point.

[0011] Furthermore, the baseline demand information between the current demand point and the matching demand point is updated according to the demand behavior characteristics of the current demand point and the matching demand point to obtain the elastic demand information between the current demand point and the matching demand point, including: determining the similarity of the demand behavior characteristics of the current demand point and the matching demand point; determining a first comparison result by comparing the average similarity of the demand behavior characteristics between the demand points in the current area and the similarity of the demand behavior characteristics between the current demand point and the matching demand point; determining a second comparison result by comparing the average static label similarity between the demand points in the current area and the static label similarity between the current demand point and the matching demand point; determining the elastic demand information between the current demand point and the matching demand point according to the first comparison result and the second comparison result.

[0012] Further, the elastic demand information between the current demand point and the matching demand point is determined based on the first comparison result and the second comparison result, including: if the first comparison result and the second comparison result are both less than, then the larger value of the similarity of the demand behavior characteristics and the static label similarity between the current demand point and the matching demand point is determined as the elastic demand information between the current demand point and the matching demand point; if the first comparison result and / or the second comparison result is greater than or equal to, then the weighted sum of the similarity of the demand behavior characteristics and the static label similarity between the current demand point and the matching demand point is determined as the elastic demand information between the current demand point and the matching demand point.

[0013] Furthermore, based on the elastic demand information between the current demand point and each of the matching demand points and the functional matching degree of the service function, the matching result of the current demand point and the service function is determined, including: determining the demand critical value based on the functional matching degree and the pre-set matching degree standard value and initial critical value; if the elastic demand information between the current demand point and at least one of the matching demand points is not less than the demand critical value, the matching result is determined to be a match.

[0014] In a second aspect, an embodiment of the present invention further provides a device for configuring a service function, including:

[0015] A first determination module is used to determine the matching demand points corresponding to the service function, and determine the functional matching degree of the service function according to the matching degree coefficient determination rule and the number of matching demand points corresponding to the service function;

[0016] A second determination module is used to determine the elastic demand information between the current demand point and each of the matching demand points, wherein the current demand point is any demand point other than the matching demand point in the current area;

[0017] An execution module, configured to determine a matching result between the current demand point and the service function according to elastic demand information between the current demand point and each of the matching demand points and a functional matching degree of the service function;

[0018] A configuration module is used to configure the service function to the current demand point when it is determined that the matching result is a match.

[0019] In a third aspect, an embodiment of the present invention further provides an electronic device, comprising: at least one processor; and a memory communicatively connected to the at least one processor; wherein the memory stores a computer program executable by the at least one processor, and the computer program is executed by the at least one processor so that the at least one processor can execute a method for configuring a service function as described in any one of the first aspects.

[0020] In a fourth aspect, an embodiment of the present invention further provides a storage medium comprising computer executable instructions, wherein the computer executable instructions, when executed by a computer processor, are used to execute a method for configuring a service function as described in any one of the first aspects.

[0021] In a fifth aspect, the present application provides a computer program product, which includes computer instructions. When the computer instructions are executed on a computer, the computer executes the configuration method of the service function provided in the first aspect.

[0022] It should be noted that the above computer instructions may be stored in whole or in part on a computer-readable storage medium. The computer-readable storage medium may be packaged together with the processor of the service function configuration device, or may be packaged separately from the processor of the service function configuration device, and this application does not limit this.

[0023] The description of the second, third, fourth and fifth aspects in this application can refer to the detailed description of the first aspect; and the beneficial effects of the description of the second, third, fourth and fifth aspects can refer to the beneficial effect analysis of the first aspect, which will not be repeated here.

[0024] In this application, the name of the configuration device of the above service function does not limit the device or function module itself. In actual implementation, these devices or function modules may appear with other names. As long as the functions of each device or function module are similar to those of this application, they belong to the scope of the claims of this application and their equivalent technologies.

[0025] These and other aspects of the present application will become more apparent from the following description. BRIEF DESCRIPTION OF THE DRAWINGS

[0026] In order to more clearly illustrate the technical solutions in the embodiments of the present invention, the following briefly introduces the drawings required for use in the description of the embodiments. Obviously, the drawings described below are only some embodiments of the present invention. For ordinary technicians in this field, other drawings can be obtained based on these drawings without creative work.

[0027] Figure 1A flowchart of a method for configuring a service function provided by an embodiment of the present invention;

[0028] Figure 2 A flowchart of another method for configuring a service function provided by an embodiment of the present invention;

[0029] Figure 3 A schematic diagram of the structure of a device for configuring a service function provided by an embodiment of the present invention;

[0030] Figure 4 A schematic diagram of the structure of an electronic device provided by an embodiment of the present invention. DETAILED DESCRIPTION

[0031] The present invention will be further described in detail below in conjunction with the accompanying drawings and embodiments. It is to be understood that the specific embodiments described herein are only used to explain the present invention, rather than to limit the present invention. It should also be noted that, for ease of description, only parts related to the present invention, rather than all structures, are shown in the accompanying drawings.

[0032] The term "and / or" in this article is merely a description of the association relationship of associated objects, indicating that three relationships may exist. For example, A and / or B can mean: A exists alone, A and B exist at the same time, and B exists alone.

[0033] The terms "first" and "second" and the like in the specification and drawings of this application are used to distinguish different objects, or to distinguish different processing of the same object, rather than to describe a specific order of objects.

[0034] In addition, the terms "including" and "having" and any variations thereof mentioned in the description of the present application are intended to cover non-exclusive inclusions. For example, a process, method, system, product or device that includes a series of steps or units is not limited to the listed steps or units, but may optionally include other steps or units that are not listed, or may optionally include other steps or units that are inherent to these processes, methods, products or devices.

[0035] It should be mentioned before discussing exemplary embodiments in more detail that some exemplary embodiments are described as processes or methods depicted as flow charts. Although the flow charts describe various operations (or steps) as sequential processes, many operations therein can be implemented in parallel, concurrently or simultaneously. In addition, the order of various operations can be rearranged. The process can be terminated when its operation is completed, but can also have additional steps not included in the accompanying drawings. The process can correspond to methods, functions, procedures, subroutines, subprograms, etc. In addition, the embodiments in the present invention and the features in the embodiments can be combined with each other without conflict.

[0036] It should be noted that, in the embodiments of the present application, words such as "exemplary" or "for example" are used to indicate examples, illustrations or descriptions. Any embodiment or design described as "exemplary" or "for example" in the embodiments of the present application should not be interpreted as being more preferred or more advantageous than other embodiments or designs. Specifically, the use of words such as "exemplary" or "for example" is intended to present related concepts in a specific way.

[0037] In the description of the present application, unless otherwise specified, “plurality” means two or more.

[0038] Figure 1 This is a flow chart of a method for configuring a service function provided by an embodiment of the present invention. This embodiment is applicable to situations where service functions need to be configured for demand points in a region. The method can be executed by a service function configuration device, such as Figure 1 As shown, the specific steps include:

[0039] Step 110: determine the matching demand points corresponding to the service function, and determine the functional matching degree of the service function according to the matching degree coefficient determination rule and the number of matching demand points corresponding to the service function.

[0040] Among them, service functions can be understood as any service provided by the smart community to residents. Service functions are divided according to service categories and service levels. For example, service functions include medical services, elderly care services, catering services, security services, etc. Security services may include access control services, abnormal personnel detection services, and monitoring services for unauthorized personnel entering unauthorized areas. Monitoring services for unauthorized personnel entering unauthorized areas include foreign object monitoring services and person monitoring services.

[0041] Demand points can be understood as families, floors, buildings, communities, etc. with unified needs within the smart community. The matching demand points corresponding to service functions can be understood as demand points that determine the existence of demand for the service function, for example, families that have demand for door-to-door catering services in elderly care services.

[0042] Specifically, first, the demand points that determine the existence of demand for the service function can be determined as the matching demand points corresponding to the service function. The functional matching degree of the service function is determined based on the number of matching demand points corresponding to the service function and the matching coefficient. The matching coefficient determination rule is used to determine the matching coefficient corresponding to the service function according to the service scenario to which the service function belongs. Therefore, after determining the service scenario to which the service function belongs, the matching coefficient corresponding to the service function can be determined based on the matching coefficient determination rule and the service scenario to which the service function belongs. Furthermore, the functional matching degree of the service function can be determined based on the number of matching demand points corresponding to the service function and the matching coefficient.

[0043] In an embodiment of the present invention, after determining the matching demand points corresponding to the service function, the matching coefficient corresponding to the service function is determined according to the matching coefficient determination rule and the service scenario to which the service function belongs, and then the functional matching degree of the service function is determined according to the number of matching demand points corresponding to the service function and the matching coefficient, thereby determining the matching demand points corresponding to the service function and the functional matching degree of the service function.

[0044] Step 120: Determine the elastic demand information between the current demand point and each of the matching demand points.

[0045] The current demand point is any demand point other than the matching demand point in the current area, and the current area may be the current smart community.

[0046] For each matching demand point, the elastic demand information between the current demand point and the current matching demand point can be determined. The elastic demand information between two demand points is obtained by updating the baseline demand information between the two demand points based on the demand behavior characteristics corresponding to the two demand points. The demand behavior characteristics corresponding to the two demand points are collected by various community devices in the community. The baseline demand information between the two demand points is determined based on the static label approximation of the two demand points.

[0047] Therefore, first, the demand behavior characteristics corresponding to the current demand point and each matching demand point can be determined. Specifically, the log information of each community device in the community can be obtained, and the demand behavior characteristics corresponding to the current demand point and each matching demand point can be determined based on the identification information of the current demand point and each matching demand point in the log information of each community device. Secondly, the benchmark demand information between the current demand point and each matching demand point can be determined. Specifically, the static labels of the current demand point and each matching demand point can be obtained, and the approximation of the static labels of the current demand point and each matching demand point can be determined, and the approximation of the static labels of the current demand point and each matching demand point can be determined as the benchmark demand information between the current demand point and each matching demand point. For each matching demand point, the benchmark demand information between the current demand point and the current matching demand point can be updated according to the demand behavior characteristics of the current demand point and the current matching demand point, and the elastic demand information between the current demand point and the current matching demand point can be obtained.

[0048] In an embodiment of the present invention, the baseline demand information between the current demand point and the current matching demand point is updated according to the demand behavior characteristics of the current demand point and each matching demand point, and the elastic demand information between the current demand point and the current matching demand point is obtained. The elastic demand information between the current demand point and the current matching demand point is determined by combining the demand behavior characteristics of the current demand point and each matching demand point and the static label approximation, thereby ensuring the reliability of the elastic demand information while improving the accuracy.

[0049] Step 130: Determine a matching result between the current demand point and the service function according to the elastic demand information between the current demand point and each of the matching demand points and the functional matching degree of the service function.

[0050] Specifically, first, the demand critical value can be determined according to the functional matching degree of the service function, and secondly, the elastic demand information between the current demand point and each matching demand point can be compared with the demand critical value. If the elastic demand information between the current demand point and at least one matching demand point is not less than the demand critical value, then the matching result between the current demand point and the service function is determined to be a match; otherwise, the matching result between the current demand point and the service function is determined to be a mismatch.

[0051] In the embodiment of the present invention, the matching result between the current demand point and the service function is determined.

[0052] Step 140: When it is determined that the matching result is a match, the service function is configured to the current demand point.

[0053] Specifically, if it is determined that the matching result between the current demand point and the service function is a match, the service function is configured to the current demand point. If it is determined that the matching result between the current demand point and the service function is not a match, there is no need to configure the service function to the current demand point.

[0054] In the embodiment of the present invention, in the process of configuring service functions, the differences among communities and demand points within communities are fully considered, and the service functions are configured to the demand points that actually need the service functions, thereby improving residents' service experience while reducing service expenses.

[0055] The method for configuring a service function provided in an embodiment of the present invention includes: determining a matching demand point corresponding to the service function, and determining the functional matching degree of the service function according to a matching coefficient determination rule and the number of matching demand points corresponding to the service function; determining elastic demand information between a current demand point and each of the matching demand points, wherein the current demand point is any demand point other than the matching demand point in the current area; determining a matching result between the current demand point and the service function according to the elastic demand information between the current demand point and each of the matching demand points and the functional matching degree of the service function; and configuring the service function to the current demand point when it is determined that the matching result is a match. The above technical scheme can first determine the matching demand points corresponding to the service function, and secondly determine the matching coefficient corresponding to the service function according to the matching coefficient determination rule and the service scenario to which the service function belongs, and then determine the functional matching degree of the service function according to the number of matching demand points corresponding to the service function and the matching coefficient, so as to determine the matching demand points corresponding to the service function and the functional matching degree of the service function, and can also determine the elastic demand information between the current demand point and the current matching demand point in combination with the demand behavior characteristics and benchmark demand information of the current demand point and each matching demand point, so as to ensure the reliability of the elastic demand information while improving the accuracy, and then determine the matching result of the current demand point and the service function according to the elastic demand information between the current demand point and each matching demand point and the functional matching degree of the service function, and when it is determined that the matching result of the current demand point and the service function is a match, configure the service function to the current demand point, and in the process of configuring the service function, fully consider the differences between the community and the demand points within the community, configure the service function to the demand points that actually need the service function, and reduce the configuration of the service function to the demand points with low demand for the service function, so as to improve the service experience of residents while reducing service expenses, and improve the effect of service function configuration and improve the problem of poor service function adaptation effect.

[0056] Figure 2 This is a flow chart of another method for configuring a service function provided by an embodiment of the present invention. This embodiment is specific based on the above embodiment. Figure 2 As shown, in this embodiment, the method may further include:

[0057] Step 210: Determine the matching demand points corresponding to the service functions.

[0058] Step 220: Determine the functional matching degree of the service function according to the matching degree coefficient determination rule and the number of matching demand points corresponding to the service function.

[0059] In one implementation, step 220 may specifically include: determining a service scenario of the service function, determining the matching coefficient of the service function based on the matching coefficient determination rule and the service scenario; determining the functional matching degree of the service function according to the number of matching demand points corresponding to the service function and the matching coefficient.

[0060] The matching coefficient of the service scenario is related to the service scenario to which the service function belongs, and the value of the matching coefficient is determined according to a pre-configured matching coefficient determination rule and the service scenario to which the service function belongs.

[0061] Specifically, the service function can be firstly subdivided, and the service function can be subdivided based on the category and hierarchical relationship of the smart community service function to obtain multiple sub-functions corresponding to the service function. After determining the sub-function identifier of each sub-function, the target scene template library corresponding to each sub-function identifier is determined in the pre-built multiple scene template libraries, wherein each scene database includes multiple functions corresponding to scenes, and each function identifier corresponding to the same target scene template library is summarized into a set to obtain at least one sub-function identifier set, and the identification statistics corresponding to each sub-function identifier set are obtained by counting the number of sub-function identifiers included in each sub-function identifier set, and the scene corresponding to the sub-function identifier set with the largest identification statistics is determined as the service scene corresponding to the service function. For each scene in the service scene corresponding to the service function, the average matching number corresponding to the scene is determined according to the matching number of demand points in the historical service function usage information corresponding to the scene, and the matching number of demand points can be understood as the number of demand points that have matched the service function.

[0062] For each scenario, the ratio between the number of matching demand points corresponding to the service function and the number of matching demand points corresponding to the scenario is determined as the ratio of the number of customer demand points corresponding to the scenario. The weighted sum of the ratios of the number of customer demand points corresponding to each scenario is performed to obtain the target matching coefficient of the service function.

[0063] In an embodiment of the present invention, after determining the matching demand points corresponding to the service function, the matching coefficient corresponding to the service function is determined according to the matching coefficient determination rule and the service scenario to which the service function belongs, and then the functional matching degree of the service function is determined according to the number of matching demand points corresponding to the service function and the matching coefficient, thereby determining the matching demand points corresponding to the service function and the functional matching degree of the service function.

[0064] Step 230: For each of the matching demand points, determine the benchmark demand information between the current demand point and the matching demand point according to the static tags of the current demand point and the matching demand point.

[0065] In one implementation, step 230 may specifically include: determining a static demand combination of the current demand point and the matching demand point in a demand database based on the static labels of the current demand point and the matching demand point; determining a static label similarity between the current demand point and the matching demand point in a correspondence table between static demand combinations and correlations based on the static demand combination, and determining the static label similarity as the benchmark demand information between the current demand point and the matching demand point.

[0066] Among them, static tags can include political affiliation, age, gender, and common diseases.

[0067] Specifically, the demand library database stores static labels and static demands accordingly. After determining the static labels of the current demand point and the matching demand point, the static demand of the current demand point and the static demand of the matching demand point can be searched in the demand library database based on the static labels of the current demand point and the matching demand point, respectively, and the static demand of the current demand point and the static demand of the matching demand point can be determined as the static demand combination of the current demand point and the matching demand point.

[0068] The correspondence table between static demand combinations and correlations stores a one-to-one correspondence between static demand combinations and correlation characterization values. After determining the static demand combination of the current demand point and the matching demand point, the correlation characterization value can be determined in the correspondence table between the static demand combination and the correlation. The correlation characterization value is the static label similarity between the current demand point and the matching demand point. The static label similarity between the current demand point and the matching demand point is the benchmark demand information between the current demand point and the matching demand point.

[0069] In the embodiment of the present invention, the benchmark demand information between the current demand point and the matching demand point is determined.

[0070] Step 240: Update the baseline demand information between the current demand point and the matching demand point according to the demand behavior characteristics of the current demand point and the matching demand point to obtain the elastic demand information between the current demand point and the matching demand point.

[0071] In one implementation, step 240 may specifically include: determining the similarity between the demand behavior characteristics of the current demand point and the matching demand point; determining a first comparison result by comparing the average similarity between the demand behavior characteristics of the demand points in the current area and the similarity between the demand behavior characteristics of the current demand point and the matching demand point; determining a second comparison result by comparing the average static label similarity between the demand points in the current area and the static label similarity between the current demand point and the matching demand point; determining the elastic demand information between the current demand point and the matching demand point based on the first comparison result and the second comparison result.

[0072] Specifically, the demand behavior characteristics of the current demand point and the matching demand point can be obtained first. Specifically, the demand behavior characteristics corresponding to the current demand point and the matching demand point can be determined in the log information of each community device. In actual applications, the log information of each community device can be accessed based on the initial time period. If any community device feeds back information that cannot be accessed, the initial time period is updated until all community devices can access it. At this time, the time period is the corrected time period, that is, the demand behavior characteristics corresponding to the current demand point and the matching demand point can be determined based on the identification information of the current demand point and the matching demand point in the log information of each community device based on the corrected time period.

[0073] The demand behavior characteristics of the current demand point and the matching demand point obtained in the initial time period may be incomplete, while the demand behavior characteristics of the current demand point and the matching demand point obtained in the revised time period are relatively complete.

[0074] The demand behavior characteristics of the current demand points and matching demand points obtained in the initial time period and the corrected time period can form an ordered set of initial call spatiotemporal characteristics and an ordered set of corrected call spatiotemporal characteristics. The ordered set of initial call spatiotemporal characteristics includes the given spatial call duration of each behavior in the demand behavior characteristics corresponding to the initial time period and is arranged in a segmented order. The ordered set of corrected call spatiotemporal characteristics includes the given spatial call duration of each behavior in the demand behavior characteristics corresponding to the corrected time period and is arranged in a segmented order. The aforementioned behaviors can be understood as calls from demand points to community equipment.

[0075] Based on multiple segmentation methods, the initial call time-space feature ordered set and the revised call time-space feature ordered set are segmented and sampled to obtain multiple corresponding initial call time feature ordered subsets and multiple revised call time feature ordered subsets. The initial call time feature ordered subset and the corresponding revised call time feature ordered subset that include the most elements and are identical to each other are respectively determined as the target initial call time-space feature ordered subset and the target revised call time-space feature ordered subset.

[0076] For each given spatial call duration in the target initial call spatiotemporal feature ordered subset, calculate the difference between the given spatial call duration and the pre-configured given spatial call duration standard value (standard duration of the behavior), and obtain the initial call duration difference corresponding to the given spatial call duration, and calculate the sum of the initial call duration differences corresponding to each given spatial call duration in the target initial call spatiotemporal feature ordered subset, and obtain the spatiotemporal feature change correlation coefficient value of the target initial call spatiotemporal feature ordered subset. Based on the same method, the spatiotemporal feature change correlation coefficient value of the target revised call spatiotemporal feature ordered subset can be determined. Then, the spatiotemporal feature change correlation coefficient can be determined based on the ratio between the spatiotemporal feature change correlation coefficient value of the target initial call spatiotemporal feature ordered subset and the spatiotemporal feature change correlation coefficient value of the target revised call spatiotemporal feature ordered subset.

[0077] The demand behavior characteristics of the current demand point and the matching demand point obtained in the initial time period and the modified time period can form an initial call behavior characteristic ordered set and a modified call behavior characteristic ordered set. The initial call behavior characteristic ordered set includes each behavior in the demand behavior characteristic corresponding to the initial time period and is arranged in a segmented order. The modified call behavior characteristic ordered set includes each behavior in the demand behavior characteristic corresponding to the modified time period and is arranged in a segmented order. According to the ratio of the number of elements contained in the initial call behavior characteristic ordered set and the modified call behavior characteristic ordered set, the call behavior quantity correlation coefficient can be determined.

[0078] Based on multiple segmentation methods, the ordered set of initial call behavior characteristics and the ordered set of modified call behavior characteristics are segmented and sampled to obtain multiple corresponding ordered subsets of initial call behavior characteristics and multiple ordered subsets of modified call behavior characteristics. Each ordered subset of initial call time characteristics and each corresponding ordered subset of modified call time characteristics that include the same elements are determined as the target initial call behavior characteristic ordered subset and the target call demand behavior characteristic ordered subset, respectively.

[0079] Count the number of ordered subsets of target initial call behavior characteristics and the number of ordered subsets of target call demand behavior characteristics to obtain the number of initial combinations; count the number of ordered subsets of initial call behavior characteristics and the number of ordered subsets of revised call behavior characteristics to obtain the number of revised combinations; calculate the ratio between the initial number of combinations and the revised number of combinations; combine the ratio, the correlation coefficient of spatiotemporal characteristic changes, and the correlation coefficient of the call behavior quantity (for example, the three can be multiplied to obtain the similarity between the demand behavior characteristics of the current demand point and the matching demand point).

[0080] Based on the above steps, the similarity of demand behavior characteristics between each demand point in the community can be determined, and the average of the similarity of demand behavior characteristics between each demand point can be calculated to obtain the average of the similarity of demand behavior characteristics between each demand point in the community. By comparing the similarity of demand behavior characteristics between the current demand point and the matching demand point and the average of the demand behavior characteristic similarities, the first comparison result can be determined, that is, the first comparison result can be determined as the similarity of demand behavior characteristics between the current demand point and the matching demand point is less than, equal to or greater than the average of the demand behavior characteristic similarities.

[0081] It is also possible to search for corresponding static demands in the demand library database according to the static labels of each demand point in the community, and then determine the static demands of each demand point as a static demand combination of each demand point, and then determine the correlation characterization value corresponding to the static demand combination of each demand point in the correspondence table of static demand combination and correlation as the static label similarity of the static demand combination of each demand point. Then, the mean of the static label similarity between each demand point in the community can be calculated, and the mean of the static label similarity between each demand point in the community can be obtained. By comparing the static label similarity of the current demand point and the matching demand point with the mean of the static label similarity, the second comparison result can be determined, that is, the second comparison result can be determined as the static label similarity between the current demand point and the matching demand point is less than, equal to, or greater than the mean of the static label similarity.

[0082] Further, the elastic demand information between the current demand point and the matching demand point is determined based on the first comparison result and the second comparison result, including: if the first comparison result and the second comparison result are both less than, then the larger value of the similarity of the demand behavior characteristics and the static label similarity between the current demand point and the matching demand point is determined as the elastic demand information between the current demand point and the matching demand point; if the first comparison result and / or the second comparison result is greater than or equal to, then the weighted sum of the similarity of the demand behavior characteristics and the static label similarity between the current demand point and the matching demand point is determined as the elastic demand information between the current demand point and the matching demand point.

[0083] Specifically, if the first comparison result is that the similarity between the demand behavior characteristics of the current demand point and the matching demand point is less than the average of the demand behavior characteristic similarities, and the second comparison result is that the static label similarity between the current demand point and the matching demand point is less than the average of the static label similarities, then the larger value of the similarity between the demand behavior characteristics of the current demand point and the matching demand point and the static label similarity can be determined as the elastic demand information between the current demand point and the matching demand point (for example, if the static label similarity is greater than the demand behavior characteristic similarity, then the static label similarity can be determined as the elastic demand information; if the static label similarity is less than the demand behavior characteristic similarity, then the demand behavior characteristic similarity is determined as the elastic demand information). Of course, if the first comparison result is that the similarity between the demand behavior characteristics of the current demand point and the matching demand point is greater than or equal to the average of the demand behavior characteristic similarities, and / or the second comparison result is that the static label similarity between the current demand point and the matching demand point is greater than or equal to the average of the static label similarities, then the similarity between the demand behavior characteristics of the current demand point and the matching demand point and the static label similarity can be weighted and summed, and the weighted sum value can be determined as the elastic demand information between the current demand point and the matching demand point, and the weight coefficient corresponding to the static label similarity is greater than the weight coefficient corresponding to the similarity between the demand behavior characteristics.

[0084] In an embodiment of the present invention, the baseline demand information between the current demand point and the current matching demand point is updated according to the demand behavior characteristics of the current demand point and each matching demand point, and the elastic demand information between the current demand point and the current matching demand point is obtained. The elastic demand information between the current demand point and the current matching demand point is determined by combining the demand behavior characteristics of the current demand point and each matching demand point and the static label approximation, thereby ensuring the reliability of the elastic demand information while improving the accuracy.

[0085] Step 250: Determine a matching result between the current demand point and the service function according to the elastic demand information between the current demand point and each of the matching demand points and the functional matching degree of the service function.

[0086] The current demand point is any demand point other than the matching demand point in the current area.

[0087] In one implementation, step 250 may specifically include: determining a demand critical value based on the functional matching degree and a pre-set matching degree standard value and an initial critical value; if the elastic demand information between the current demand point and at least one of the matching demand points is not less than the demand critical value, determining that the matching result is a match.

[0088] Specifically, first, the matching ratio coefficient can be determined according to the functional matching degree of the service function and the pre-configured matching standard value, and the demand critical value can be determined according to the matching ratio coefficient and the pre-configured initial critical value. Secondly, the elastic demand information between the current demand point and each matching demand point can be compared with the demand critical value. If the elastic demand information between the current demand point and at least one matching demand point is not less than the demand critical value, then the matching result between the current demand point and the service function is determined to be a match. If the elastic demand information between the current demand point and each matching demand point is less than the demand critical value, then the matching result between the current demand point and the service function is determined to be a mismatch.

[0089] In the embodiment of the present invention, the matching result between the current demand point and the service function is determined.

[0090] Step 260: When it is determined that the matching result is a match, the service function is configured to the current demand point.

[0091] Specifically, if it is determined that the matching result between the current demand point and the service function is a match, the service function is configured to the current demand point. Of course, if it is determined that the matching result between the current demand point and the service function is not a match, there is no need to configure the service function to the current demand point.

[0092] In the embodiment of the present invention, in the process of configuring service functions, the differences among communities and demand points within communities are fully considered, and service functions are configured to demand points that actually need the service functions, rather than configuring service functions to demand points where the demand for the service functions is not high, thereby improving residents' service experience while reducing service expenses.

[0093] The method for configuring a service function provided in an embodiment of the present invention includes: determining a matching demand point corresponding to a service function; determining a functional matching degree of the service function according to a matching degree coefficient determination rule and the number of matching demand points corresponding to the service function; for each matching demand point, determining the baseline demand information between the current demand point and the matching demand point according to static tags of the current demand point and the matching demand point; updating the baseline demand information between the current demand point and the matching demand point according to demand behavior characteristics of the current demand point and the matching demand point to obtain the elastic demand information between the current demand point and the matching demand point; determining a matching result between the current demand point and the service function according to the elastic demand information between the current demand point and each matching demand point and the functional matching degree of the service function; and configuring the service function to the current demand point when it is determined that the matching result is a match. The above technical scheme can first determine the matching demand points corresponding to the service function, and secondly determine the matching coefficient corresponding to the service function according to the matching coefficient determination rule and the service scenario to which the service function belongs, and then determine the functional matching degree of the service function according to the number of matching demand points corresponding to the service function and the matching coefficient, so as to determine the matching demand points corresponding to the service function and the functional matching degree of the service function, and can also determine the elastic demand information between the current demand point and the current matching demand point in combination with the demand behavior characteristics and benchmark demand information of the current demand point and each matching demand point, so as to ensure the reliability of the elastic demand information while improving the accuracy, and then determine the matching result of the current demand point and the service function according to the elastic demand information between the current demand point and each matching demand point and the functional matching degree of the service function, and when it is determined that the matching result of the current demand point and the service function is a match, configure the service function to the current demand point, and in the process of configuring the service function, fully consider the differences between the community and the demand points within the community, configure the service function to the demand points that actually need the service function, and reduce the configuration of the service function to the demand points with low demand for the service function, so as to improve the service experience of residents while reducing service expenses, and improve the effect of service function configuration and improve the problem of poor service function adaptation effect.

[0094] Figure 3 This is a schematic diagram of the structure of a device for configuring a service function provided in an embodiment of the present invention, which can be applied to situations where service functions need to be configured for demand points in a region. The device can be implemented by software and / or hardware and is generally integrated in an electronic device, such as a computer device.

[0095] like Figure 3 As shown, the device comprises:

[0096] A first determination module 310 is used to determine the matching demand points corresponding to the service function, and determine the functional matching degree of the service function according to the matching degree coefficient determination rule and the number of matching demand points corresponding to the service function;

[0097] A second determination module 320 is used to determine elastic demand information between the current demand point and each of the matching demand points, wherein the current demand point is any demand point other than the matching demand point in the current area;

[0098] An execution module 330 is used to determine a matching result between the current demand point and the service function according to the elastic demand information between the current demand point and each of the matching demand points and the functional matching degree of the service function;

[0099] The configuration module 340 is used to configure the service function to the current demand point when it is determined that the matching result is a match.

[0100] The device for configuring the service function provided in the present embodiment determines the matching demand point corresponding to the service function, determines the functional matching degree of the service function according to the matching degree coefficient determination rule and the number of matching demand points corresponding to the service function; determines the elastic demand information between the current demand point and each of the matching demand points, wherein the current demand point is any demand point other than the matching demand point in the current area; determines the matching result between the current demand point and the service function according to the elastic demand information between the current demand point and each of the matching demand points and the functional matching degree of the service function; and when it is determined that the matching result is a match, configures the service function to the current demand point. The above technical scheme can first determine the matching demand points corresponding to the service function, and secondly determine the matching coefficient corresponding to the service function according to the matching coefficient determination rule and the service scenario to which the service function belongs, and then determine the functional matching degree of the service function according to the number of matching demand points corresponding to the service function and the matching coefficient, so as to determine the matching demand points corresponding to the service function and the functional matching degree of the service function, and can also determine the elastic demand information between the current demand point and the current matching demand point in combination with the demand behavior characteristics and benchmark demand information of the current demand point and each matching demand point, so as to ensure the reliability of the elastic demand information while improving the accuracy, and then determine the matching result of the current demand point and the service function according to the elastic demand information between the current demand point and each matching demand point and the functional matching degree of the service function, and when it is determined that the matching result of the current demand point and the service function is a match, configure the service function to the current demand point, and in the process of configuring the service function, fully consider the differences between the community and the demand points within the community, configure the service function to the demand points that actually need the service function, and reduce the configuration of the service function to the demand points with low demand for the service function, so as to improve the service experience of residents while reducing service expenses, and improve the effect of service function configuration and improve the problem of poor service function adaptation effect.

[0101] Based on the above embodiment, the first determination module 310 is specifically used to: determine the matching demand points corresponding to the service function; and determine the functional matching degree of the service function according to the matching coefficient determination rule and the number of matching demand points corresponding to the service function.

[0102] On the basis of the above embodiment, the second determination module 320 is specifically used to: for each of the matching demand points, determine the baseline demand information between the current demand point and the matching demand point according to the static labels of the current demand point and the matching demand point; update the baseline demand information between the current demand point and the matching demand point according to the demand behavior characteristics of the current demand point and the matching demand point, and obtain the elastic demand information between the current demand point and the matching demand point.

[0103] In one embodiment, the benchmark demand information between the current demand point and the matching demand point is determined based on the static labels of the current demand point and the matching demand point, including: determining a static demand combination of the current demand point and the matching demand point in a demand database based on the static labels of the current demand point and the matching demand point; determining the static label similarity between the current demand point and the matching demand point in a correspondence table between static demand combinations and correlations based on the static demand combination, and determining the static label similarity as the benchmark demand information between the current demand point and the matching demand point.

[0104] In one implementation, the baseline demand information between the current demand point and the matching demand point is updated according to the demand behavior characteristics of the current demand point and the matching demand point to obtain the elastic demand information between the current demand point and the matching demand point, including: determining the similarity of the demand behavior characteristics of the current demand point and the matching demand point; determining a first comparison result by comparing the average similarity of the demand behavior characteristics between the demand points in the current area and the similarity of the demand behavior characteristics between the current demand point and the matching demand point; determining a second comparison result by comparing the average static label similarity between the demand points in the current area and the static label similarity between the current demand point and the matching demand point; and determining the elastic demand information between the current demand point and the matching demand point according to the first comparison result and the second comparison result.

[0105] Further, the elastic demand information between the current demand point and the matching demand point is determined based on the first comparison result and the second comparison result, including: if the first comparison result and the second comparison result are both less than, then the larger value of the similarity of the demand behavior characteristics and the static label similarity between the current demand point and the matching demand point is determined as the elastic demand information between the current demand point and the matching demand point; if the first comparison result and / or the second comparison result is greater than or equal to, then the weighted sum of the similarity of the demand behavior characteristics and the static label similarity between the current demand point and the matching demand point is determined as the elastic demand information between the current demand point and the matching demand point.

[0106] Based on the above embodiment, the execution module 330 is specifically used to: determine the demand critical value based on the functional matching degree and the pre-set matching degree standard value and the initial critical value; if the elastic demand information between the current demand point and at least one of the matching demand points is not less than the demand critical value, then determine that the matching result is a match.

[0107] The device for configuring the service function provided in the embodiment of the present invention can execute the method for configuring the service function provided in any embodiment of the present invention, and has the corresponding functional modules and beneficial effects for executing the method for configuring the service function.

[0108] It is worth noting that in the embodiment of the configuration device of the above-mentioned service function, the various units and modules included are only divided according to functional logic, but are not limited to the above-mentioned division, as long as the corresponding functions can be achieved; in addition, the specific names of the various functional units are only for the convenience of distinguishing each other, and are not used to limit the scope of protection of the present invention.

[0109] Figure 4 A schematic diagram of the structure of an electronic device provided by an embodiment of the present invention. Figure 4 A block diagram of an exemplary electronic device 4 suitable for implementing embodiments of the present invention is shown. Figure 4 The electronic device 4 shown is only an example and should not bring any limitation to the functions and scope of use of the embodiments of the present invention.

[0110] like Figure 4 As shown, the electronic device 4 is in the form of a general purpose computing electronic device. The components of the electronic device 4 may include, but are not limited to: one or more processors or processing units 16, a system memory 28, and a bus 18 connecting different system components (including the system memory 28 and the processing unit 16).

[0111] Bus 18 represents one or more of several types of bus structures, including a memory bus or memory controller, a peripheral bus, an accelerated graphics port, a processor or a local bus using any of a variety of bus architectures. By way of example, these architectures include, but are not limited to, an Industry Standard Architecture (ISA) bus, a Micro Channel Architecture (MAC) bus, an Enhanced ISA bus, a Video Electronics Standards Association (VESA) local bus, and a Peripheral Component Interconnect (PCI) bus.

[0112] The electronic device 4 typically includes a variety of computer system readable media. These media can be any available media that can be accessed by the electronic device 4, including volatile and non-volatile media, removable and non-removable media.

[0113] The system memory 28 may include computer system readable media in the form of volatile memory, such as random access memory (RAM) 30 and / or cache memory 32. The electronic device 4 may further include other removable / non-removable, volatile / non-volatile computer system storage media. By way of example only, the storage system 34 may be used to read and write non-removable, non-volatile magnetic media ( Figure 4 not shown, usually called a "hard drive"). Although Figure 4Not shown in the figure, a disk drive for reading and writing to a removable non-volatile disk (e.g., a "floppy disk"), and an optical disk drive for reading and writing to a removable non-volatile optical disk (e.g., a CD-ROM, a DVD-ROM, or other optical media) may be provided. In these cases, each drive may be connected to the bus 18 via one or more data medium interfaces. The system memory 28 may include at least one program product having a set (e.g., at least one) of program modules that are configured to perform the functions of the various embodiments of the present invention.

[0114] A program / utility 40 having a set (at least one) of program modules 42 may be stored, for example, in system memory 28, such program modules 42 including, but not limited to, an operating system, one or more application programs, other program modules, and program data, each of which or some combination may include an implementation of a network environment. Program modules 42 generally perform the functions and / or methods of the embodiments described herein.

[0115] The electronic device 4 may also communicate with one or more external devices 14 (e.g., keyboards, pointing devices, displays 24, etc.), one or more devices that enable a user to interact with the electronic device 4, and / or any device that enables the electronic device 4 to communicate with one or more other computing devices (e.g., network cards, modems, etc.). Such communication may be performed via an input / output (I / O) interface 22. Furthermore, the electronic device 4 may also communicate with one or more networks (e.g., a local area network (LAN), a wide area network (WAN), and / or a public network, such as the Internet) via a network adapter 20. Figure 4 As shown, the network adapter 20 communicates with other modules of the electronic device 4 via the bus 18. It should be understood that although Figure 4 Not shown, other hardware and / or software modules may be used in conjunction with the electronic device 4, including but not limited to: microcode, device drivers, redundant processing units, external disk drive arrays, RAID systems, tape drives, and data backup storage systems.

[0116] The processing unit 16 executes various functional applications and page displays by running the program stored in the system memory 28, such as implementing the configuration method of the service function provided in an embodiment of the present invention, the method comprising: determining the matching demand point corresponding to the service function, and determining the functional matching degree of the service function according to the matching coefficient determination rule and the number of matching demand points corresponding to the service function; determining the elastic demand information between the current demand point and each of the matching demand points, wherein the current demand point is any demand point other than the matching demand point in the current area; determining the matching result between the current demand point and the service function according to the elastic demand information between the current demand point and each of the matching demand points and the functional matching degree of the service function; and configuring the service function to the current demand point when it is determined that the matching result is a match.

[0117] Of course, those skilled in the art can understand that the processor can also implement the technical solution of the method for configuring the service function provided by any embodiment of the present invention.

[0118] An embodiment of the present invention provides a computer-readable storage medium having a computer program stored thereon. When the program is executed by a processor, it implements, for example, a method for configuring a service function provided by an embodiment of the present invention, the method comprising: determining a matching demand point corresponding to the service function, and determining a functional matching degree of the service function according to a matching degree coefficient determination rule and the number of matching demand points corresponding to the service function; determining elastic demand information between a current demand point and each of the matching demand points, wherein the current demand point is any demand point other than the matching demand point in the current area; determining a matching result between the current demand point and the service function according to the elastic demand information between the current demand point and each of the matching demand points and the functional matching degree of the service function; and configuring the service function to the current demand point when it is determined that the matching result is a match.

[0119] The computer storage medium of the embodiment of the present invention can adopt any combination of one or more computer-readable media. The computer-readable medium can be a computer-readable signal medium or a computer-readable storage medium. The computer-readable storage medium can be, for example, but not limited to: an electrical, magnetic, optical, electromagnetic, infrared, or semiconductor system, device or device, or any combination of the above. More specific examples (non-exhaustive list) of computer-readable storage media include: an electrical connection with one or more wires, a portable computer disk, a hard disk, a random access memory (RAM), a read-only memory (ROM), an erasable programmable read-only memory (EPROM or flash memory), an optical fiber, a portable compact disk read-only memory (CD-ROM), an optical storage device, a magnetic storage device, or any suitable combination of the above. In this document, a computer-readable storage medium can be any tangible medium containing or storing a program, which can be used by an instruction execution system, device or device or used in combination with it.

[0120] Computer-readable signal media may include data signals propagated in baseband or as part of a carrier wave, which carry computer-readable program code. Such propagated data signals may take a variety of forms, including but not limited to electromagnetic signals, optical signals, or any suitable combination of the above. Computer-readable signal media may also be any computer-readable medium other than a computer-readable storage medium, which may send, propagate, or transmit a program for use by or in conjunction with an instruction execution system, apparatus, or device.

[0121] The program code embodied on the computer readable medium may be transmitted using any appropriate medium, including but not limited to wireless, wireline, optical fiber cable, RF, etc., or any suitable combination of the foregoing.

[0122] Computer program code for performing the operations of the present invention may be written in one or more programming languages ​​or a combination thereof, including object-oriented programming languages ​​such as Java, Smalltalk, C++, and conventional procedural programming languages ​​such as "C" or similar programming languages. The program code may be executed entirely on the user's computer, partially on the user's computer, as a separate software package, partially on the user's computer and partially on a remote computer, or entirely on a remote computer or server. In the case of a remote computer, the remote computer may be connected to the user's computer through any type of network, including a local area network (LAN) or a wide area network (WAN), or may be connected to an external computer (e.g., via the Internet using an Internet service provider).

[0123] It should be understood by those skilled in the art that the modules or steps of the present invention described above can be implemented by a general-purpose computing device, they can be concentrated on a single computing device, or distributed on a network composed of multiple computing devices, optionally, they can be implemented by a program code executable by a computer device, so that they can be stored in a storage device and executed by the computing device, or they can be made into individual integrated circuit modules, or multiple modules or steps therein can be made into a single integrated circuit module for implementation. Thus, the present invention is not limited to any specific combination of hardware and software.

[0124] In addition, the acquisition, storage, use, and processing of data in the technical solution of the present invention are in compliance with the relevant provisions of national laws and regulations.

[0125] Note that the above are only preferred embodiments of the present invention and the technical principles used. Those skilled in the art will understand that the present invention is not limited to the specific embodiments herein, and that various obvious changes, readjustments and substitutions can be made by those skilled in the art without departing from the scope of protection of the present invention. Therefore, although the present invention has been described in more detail through the above embodiments, the present invention is not limited to the above embodiments, and may include more other equivalent embodiments without departing from the concept of the present invention, and the scope of the present invention is determined by the scope of the appended claims.

Claims

1. A method for configuring a service function, characterized in that: include: Determine the matching demand points corresponding to the service function, and determine the functional matching degree of the service function according to the matching degree coefficient determination rule and the number of matching demand points corresponding to the service function; Determine elastic demand information between the current demand point and each of the matching demand points, wherein the current demand point is any demand point other than the matching demand point in the current area; Determining a matching result between the current demand point and the service function according to the elastic demand information between the current demand point and each of the matching demand points and the functional matching degree of the service function; When it is determined that the matching result is a match, the service function is configured to the current demand point.

2. The method for configuring service functions according to claim 1, characterized in that: Determining the functional matching degree of the service function according to the matching degree coefficient determination rule and the number of matching demand points corresponding to the service function includes: Determine a service scenario of the service function, and determine a matching coefficient of the service function based on the matching coefficient determination rule and the service scenario; The functional matching degree of the service function is determined according to the number of the matching demand points corresponding to the service function and the matching degree coefficient.

3. The method for configuring service functions according to claim 1, characterized in that: Determining elastic demand information between the current demand point and each of the matching demand points includes: For each of the matching demand points, determining the benchmark demand information between the current demand point and the matching demand point according to the static tags of the current demand point and the matching demand point; The benchmark demand information between the current demand point and the matching demand point is updated according to the demand behavior characteristics of the current demand point and the matching demand point to obtain the elastic demand information between the current demand point and the matching demand point.

4. The method for configuring service functions according to claim 3, characterized in that: Determining the benchmark demand information between the current demand point and the matching demand point according to the static tags of the current demand point and the matching demand point includes: Determine a static demand combination of the current demand point and the matching demand point in a demand database according to the static tags of the current demand point and the matching demand point; The static label similarity between the current demand point and the matching demand point is determined in a correspondence table between the static demand combination and the correlation according to the static demand combination, and the static label similarity is determined as the benchmark demand information between the current demand point and the matching demand point.

5. The method for configuring service functions according to claim 3, characterized in that: Updating the reference demand information between the current demand point and the matching demand point according to the demand behavior characteristics of the current demand point and the matching demand point to obtain the elastic demand information between the current demand point and the matching demand point includes: Determine the similarity between the demand behavior characteristics of the current demand point and the matching demand point; Determine a first comparison result by comparing the average similarity values ​​of the demand behavior characteristics between the demand points in the current area and the similarity between the demand behavior characteristics of the current demand point and the matching demand point; Determine a second comparison result by comparing the average values ​​of the static label approximations between the demand points in the current area and the static label approximations between the current demand point and the matching demand point; The elastic demand information between the current demand point and the matching demand point is determined according to the first comparison result and the second comparison result.

6. The method for configuring service functions according to claim 5, characterized in that: Determining the elastic demand information between the current demand point and the matching demand point according to the first comparison result and the second comparison result includes: If both the first comparison result and the second comparison result are less than, the larger value of the similarity of the demand behavior characteristics between the current demand point and the matching demand point and the static label similarity is determined as the elastic demand information between the current demand point and the matching demand point; If the first comparison result and / or the second comparison result is greater than or equal to, the elastic demand information between the current demand point and the matching demand point is determined according to the weighted sum of the similarity of the demand behavior characteristics and the static label approximation between the current demand point and the matching demand point.

7. The method for configuring service functions according to claim 1, characterized in that: Determining a matching result between the current demand point and the service function according to the elastic demand information between the current demand point and each of the matching demand points and the functional matching degree of the service function includes: Determining a demand critical value according to the functional matching degree and a preset matching degree standard value and an initial critical value; If the elastic demand information between the current demand point and at least one of the matching demand points is not less than the demand critical value, the matching result is determined to be a match.

8. A device for configuring a service function, characterized in that: include: A first determination module is used to determine the matching demand points corresponding to the service function, and determine the functional matching degree of the service function according to the matching degree coefficient determination rule and the number of matching demand points corresponding to the service function; A second determination module is used to determine the elastic demand information between the current demand point and each of the matching demand points, wherein the current demand point is any demand point other than the matching demand point in the current area; An execution module, configured to determine a matching result between the current demand point and the service function according to elastic demand information between the current demand point and each of the matching demand points and a functional matching degree of the service function; A configuration module is used to configure the service function to the current demand point when it is determined that the matching result is a match.

9. An electronic device, characterized in that: The electronic device comprises: at least one processor; and a memory communicatively coupled to the at least one processor; The memory stores a computer program executable by the at least one processor, and the computer program is executed by the at least one processor so that the at least one processor can execute the method for configuring the service function as described in any one of claims 1-7.

10. A storage medium containing computer executable instructions, characterized in that: The computer executable instructions are used to execute the method for configuring the service function as claimed in any one of claims 1 to 7 when executed by a computer processor.

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