Grid drawing method and device

Abstract

The invention discloses a grid drawing method and device, and relates to the technical field of computers. A specific embodiment of the method comprises the following steps: receiving a grid drawing request for a target area, wherein the grid drawing request comprises a plurality of business indexes of each grid in the target area and a parameter range corresponding to each business index; determining each sub-region in the target region and a parameter value, corresponding to each business index, of each sub-region; and according to the parameter value, corresponding to each business index, of each sub-region and the parameter range, corresponding to each business index, of each grid, aggregating each sub-region in the target region so as to determine each grid in the target region. According to the embodiment, automatic drawing of each grid in the target area can be realized, the grid drawing efficiency and effect are improved, the operation cost is reduced, and the user experience is improved.

Description

Technical Field

[0001] The present invention relates to the field of computer technology, and in particular to a method and device for grid drawing. Background Art

[0002] In the field of e-commerce, the refined operation of instant retail business scenarios depends on the determination of the spatial grid range, that is, different operators correspond to different grid ranges. Therefore, by drawing grids in designated areas, the executable range of different operators can be determined.

[0003] In the related technology, the existing grid drawing platform is mainly drawn in the following two ways: one is to draw a custom grid range by manually marking points on the map one by one; the other is to cut or combine existing data such as streets, business districts, etc. and then drag and adjust the points. However, when facing the grid drawing scenes of multiple cities, the above two methods have a large workload and low efficiency, and rely on manual experience and high operating costs. Summary of the invention

[0004] In view of this, an embodiment of the present invention provides a method and device for grid drawing, which can realize automatic drawing of each grid in a target area, improve the efficiency and effect of grid drawing, reduce operating costs, and enhance user experience.

[0005] To achieve the above object, according to one aspect of an embodiment of the present invention, a method for drawing a grid is provided, comprising:

[0006] receiving a grid drawing request for a target area, the grid drawing request including a plurality of business indicators of each grid in the target area and a parameter range corresponding to each of the business indicators;

[0007] Determine each sub-area in the target area and a parameter value corresponding to each of the business indicators in each of the sub-areas;

[0008] The sub-regions in the target region are aggregated according to the parameter value corresponding to each of the business indicators in each of the sub-regions and the parameter range corresponding to each of the business indicators in each of the grids to determine the grids in the target region.

[0009] Optionally, the sub-regions have corresponding region types, and aggregating the sub-regions in the target region includes:

[0010] Determine each first sub-region corresponding to and adjacent to the sub-region;

[0011] Acquire, from each of the first sub-regions, a second sub-region having the same region type as the sub-region;

[0012] The sub-region and the second sub-region are aggregated to obtain a grid corresponding to the sub-region.

[0013] Optionally, determining each first sub-region corresponding to and adjacent to the sub-region includes:

[0014] Determine a geocoding set of the sub-region; the geocoding set includes multiple geocodings;

[0015] Determining each candidate sub-region corresponding to each set of geocodes including at least one of the geocodes;

[0016] Determine an adjacent judgment result between the sub-region and each of the candidate sub-regions;

[0017] Determine each first sub-region from each candidate sub-region according to the adjacent judgment result.

[0018] Optionally, aggregating the sub-region and the second sub-region to determine each grid in the target region includes:

[0019] For any of the sub-regions, taking the sub-region as a current cluster;

[0020] Pre-aggregating the sub-region with each of the second sub-regions, and determining a pre-aggregation cluster corresponding to each of the second sub-regions, wherein the pre-aggregation cluster includes an aggregation parameter value corresponding to each of the service indicators;

[0021] Determining whether each of the aggregation parameter values ​​in the pre-aggregation cluster is less than or equal to an upper limit of a parameter range of a corresponding service indicator;

[0022] If so, determining that the pre-aggregation cluster is a candidate pre-aggregation cluster, and updating the current cluster according to the candidate pre-aggregation cluster;

[0023] If not, when each of the aggregation parameter values ​​in the pre-aggregation cluster is greater than or equal to the lower limit of the parameter range of the corresponding service indicator, the current cluster is used as the grid corresponding to the sub-area in the target area.

[0024] Optionally, there are multiple candidate pre-aggregation clusters, and updating the current cluster according to the candidate pre-aggregation clusters includes:

[0025] Determining the number of business indicators whose aggregation parameter values ​​in the candidate pre-aggregation cluster are within a parameter range of a corresponding business indicator;

[0026] Determine a target pre-aggregation cluster from each candidate pre-aggregation cluster according to the number of business indicators;

[0027] The current cluster is updated according to the target pre-aggregation cluster.

[0028] Optionally, determining a target pre-aggregation cluster from each candidate pre-aggregation cluster according to the number of service indicators includes:

[0029] Determine whether the number of candidate pre-aggregation clusters with the largest number of business indicators is greater than 1;

[0030] If not, taking the candidate pre-aggregation cluster with the largest number of business indicators as the target pre-aggregation cluster;

[0031] If so, determine the sum of achievement rates of each indicator corresponding to each candidate pre-aggregation cluster with the largest number of business indicators; and determine the target pre-aggregation cluster according to the sum of achievement rates of each indicator.

[0032] Optionally, after taking the current cluster as the grid corresponding to the sub-region in the target region, the method further includes:

[0033] Acquire each remaining sub-area in the target area that does not belong to any grid;

[0034] For each of the remaining sub-regions, obtaining each candidate grid adjacent to each of the remaining sub-regions and the region type of each of the candidate grids;

[0035] Determining a target grid from the candidate grids according to a preset area type priority;

[0036] The target grid is one, and the remaining sub-areas are assigned to the target grid; or

[0037] There are multiple target grids, and the sum of the achievement rates of the indicators of the remaining sub-regions and each target grid is determined, and the remaining sub-regions are assigned to the target grid with the lowest sum of the achievement rates of the indicators.

[0038] According to another aspect of an embodiment of the present invention, there is provided a device for drawing a grid, comprising:

[0039] A receiving module receives a grid drawing request for a target area, wherein the grid drawing request includes a plurality of business indicators of each grid in the target area and a parameter range corresponding to each of the business indicators;

[0040] A first determination module is used to determine each sub-area in the target area and a parameter value corresponding to each business indicator of each sub-area;

[0041] The second determination module aggregates the sub-areas in the target area according to the parameter value corresponding to each of the business indicators in each of the sub-areas and the parameter range corresponding to each of the business indicators in each of the grids to determine the grids in the target area.

[0042] According to another aspect of an embodiment of the present invention, there is provided an electronic device, including:

[0043] one or more processors;

[0044] a storage device for storing one or more programs,

[0045] When the one or more programs are executed by the one or more processors, the one or more processors implement the grid drawing method provided by the present invention.

[0046] According to another aspect of an embodiment of the present invention, a computer-readable medium is provided, on which a computer program is stored. When the program is executed by a processor, the method for grid drawing provided by the present invention is implemented.

[0047] An embodiment of the above invention has the following advantages or beneficial effects: the grid drawing method of the embodiment of the present invention receives a grid drawing request for a target area, the grid drawing request includes the parameter range of each business indicator of each grid; determines each sub-area in the target area and the parameter value of each business indicator of each sub-area; according to the parameter value of each business indicator of each sub-area and the parameter range of each business indicator of each grid, aggregates each sub-area to obtain each grid in the target area. The method realizes intelligent grid drawing according to the parameter value of the business indicator of the sub-area and the parameter range of the business indicator of the grid, improves the efficiency and effect of grid drawing, reduces the operation cost, and the drawn grid can meet the business needs to a high degree; the method supports users to make customized adjustments and real-time calculations during the grid drawing process, which improves the user experience.

[0048] The further effects of the above-mentioned non-conventional optional manner will be described below in conjunction with the specific implementation manner. BRIEF DESCRIPTION OF THE DRAWINGS

[0049] The accompanying drawings are used to better understand the present invention and do not constitute an improper limitation of the present invention.

[0050] Figure 1 is a schematic diagram of the main process of a method for drawing a grid according to an embodiment of the present invention;

[0051] Figure 2 is a schematic diagram of the main process of another method for drawing a grid according to an embodiment of the present invention;

[0052] Figure 3 is a schematic diagram of the main process of another method for drawing a grid according to an embodiment of the present invention;

[0053] Figure 4 is a flow chart of a method for drawing a grid according to an embodiment of the present invention;

[0054] Figure 5 is a flow chart of another method for drawing a grid according to an embodiment of the present invention;

[0055] Figure 6 is a schematic diagram of main modules of a grid drawing apparatus according to an embodiment of the present invention;

[0056] Figure 7 is an exemplary system architecture diagram to which embodiments of the present invention may be applied;

[0057] Figure 8 It is a schematic diagram of the structure of a computer system of a terminal device or a server suitable for implementing an embodiment of the present invention. DETAILED DESCRIPTION

[0058] The following is a description of exemplary embodiments of the present invention in conjunction with the accompanying drawings, including various details of the embodiments of the present invention to facilitate understanding, which should be considered as merely exemplary. Therefore, it should be recognized by those of ordinary skill in the art that various changes and modifications may be made to the embodiments described herein without departing from the scope and spirit of the present invention. Similarly, for clarity and conciseness, the description of well-known functions and structures is omitted in the following description.

[0059] Figure 1 FIG. 1 is a schematic diagram of the main process of a method for drawing a grid according to an embodiment of the present invention. Figure 1 As shown, the grid drawing method includes the following steps:

[0060] Step S101: receiving a grid drawing request for a target area, where the grid drawing request includes a plurality of business indicators of each grid in the target area and a parameter range corresponding to each business indicator;

[0061] Step S102: determining each sub-area in the target area and a parameter value corresponding to each business indicator of each sub-area;

[0062] Step S103: Aggregate the sub-regions in the target region according to the parameter value corresponding to each business indicator of each sub-region and the parameter range corresponding to each business indicator of each grid to determine each grid in the target region.

[0063] In an embodiment of the present invention, the grid drawing method can be applied to grid drawing in the city dimension in an instant retail business scenario to determine the executable scope of different operators, so that different operators can perform work within the corresponding grid scope, such as store expansion within the grid scope.

[0064] In an embodiment of the present invention, the grid drawing method can be implemented by a grid drawing platform. A grid drawing request for a target area is received, and the target area is the dimension of the grid drawing. The dimension can be customized according to business needs. For example, if the dimension can be a city dimension, the target area is the city to be grid drawn. The grid drawing request includes multiple business indicators for each grid and a parameter range corresponding to each business indicator. Business indicators can be customized according to business needs. For example, business indicators can include city targets, such as the estimated gross merchandise volume (GMV) of the city dimension in the preset data, such as the annual GMV, that is, the sum of the GMVs of each grid. Business indicators can also include the estimated gross merchandise volume, that is, the annual GMV; business indicators can also include the number of covered stores and the coverage area. That is, the multiple business indicators of each grid can include the annual GMV, the number of covered stores, and the coverage area of ​​each grid, and each grid has a corresponding type, and the number of covered stores and the coverage area of ​​different types of grids can be different. The types of grids can include campus types, commercial office types, community residential types, scenic leisure, hospital, travel types, etc.

[0065] Among them, each business indicator has a corresponding parameter range, and the parameter range can be a set value or value range. For example, the parameter range of the estimated total commodity transaction amount in the city dimension and the estimated total commodity transaction amount of each grid can be set to a value or a value range, and the number of covered stores and the coverage area of ​​each grid can be set to a value range. For example, the annual GMV of the city can be set to a value or a value range greater than or equal to 0, such as 20 million; the number of covered stores of each grid can be set to different store number ranges according to the type of grid, such as the community residential type grid can be set to cover 300-600 stores; the coverage area of ​​each grid can be set to different area number ranges according to the type of grid, such as the community residential type grid can be set to cover 5-8 square kilometers; the annual GMV of each grid can be set to different GMV ranges according to the type of grid, such as the community residential type grid sets the annual GMV to 500,000-1 million. Of course, users can also adjust the parameter range corresponding to each business indicator according to business needs.

[0066] In an embodiment of the present invention, after receiving a grid drawing request for a target area, the parameter values ​​of each business indicator of each sub-area and each sub-area in the target area are determined. The sub-areas in the target area can be set according to business needs, such as a sub-area can be an interest surface (such as an Area of ​​Interest, AOI), and an AOI represents a social entity, such as a campus, a hospital, etc. AOI is surface data, which is composed of a polygonal fence boundary and the coordinates of the longitude and latitude points therein. AOI has a corresponding area type, such as a community, and the corresponding area type is commercial residential. AOIs of the same area type constitute a grid of this type.

[0067] In an embodiment of the present invention, a parameter value corresponding to each business indicator of each sub-region is determined. For example, the parameter value corresponding to the business indicator of each sub-region may be the annual GMV, number of covered stores and coverage area of ​​each sub-region, wherein the number of covered stores of each sub-region may be obtained by obtaining the latitude and longitude coordinates of each store, and taking the stores whose latitude and longitude coordinates fall within the sub-region as the covered stores of the sub-region, thereby obtaining the number of covered stores of the sub-region. The coverage area of ​​each sub-region may be determined based on the boundary of the sub-region and the latitude and longitude coordinates therein, and the annual GMV of each sub-region may be obtained based on the city target GMV, the historical annual GMV of the AOI and the historical annual GMV of the city.

[0068] In an embodiment of the present invention, before receiving a grid drawing request for a target area, a grid drawing rule is configured. The grid drawing rule may include an aggregation priority of a sub-area. The aggregation priority may be an aggregation priority of an area type, such as a priority order from high to low of campus type> commercial office type> community residential type> scenic leisure, hospital, travel type> other types; the grid drawing rule also includes aggregating AOIs of the same or similar types within a certain range with a certain type of AOI as the center. The grid drawing rule may also include basic drawing rules, such as along physical boundaries such as roads, rivers, and buildings, and not allowing cross-social entities; the boundaries of adjacent grids are fitted without gaps.

[0069] In the embodiment of the present invention, after determining the parameter value corresponding to each business indicator of each sub-region, the sub-regions in the target region are aggregated in combination with the parameter range corresponding to each business indicator of each grid to obtain each grid. For example, the sum of the parameter values ​​of any two sub-regions can be compared with the parameter range, and whether to aggregate can be determined according to the comparison result. If the sum of the parameter values ​​is within the parameter range, the two sub-regions can be aggregated, and the above process can be continued with any remaining sub-region until it is not within the parameter range, then the aggregation is stopped to obtain the corresponding grid; each grid in the target region can be obtained according to the above method.

[0070] In the embodiment of the present invention, the sub-area has a corresponding area type, such as Figure 2 As shown, each sub-area in the target area is aggregated to determine each grid in the target area, including:

[0071] Step S201: determining each first sub-region corresponding to and adjacent to the sub-region;

[0072] Step S202: acquiring a second sub-region having the same region type as the sub-region from each first sub-region;

[0073] Step S203: Aggregate the sub-region and the second sub-region to obtain a grid corresponding to the sub-region.

[0074] In an embodiment of the present invention, each sub-region has a corresponding region type, and sub-regions of the same region type can form a grid of a corresponding type, that is, each sub-region can be aggregated according to the region type. First, each sub-region corresponding to each adjacent first sub-region is determined, such as by determining the adjacent sub-region set of each sub-region, the adjacent sub-region set of each sub-region indicates each first sub-region adjacent to the sub-region, and then the second sub-region of the same region type is obtained from each first sub-region, each sub-region and the second sub-region of the same region type are aggregated, and a grid containing the sub-region and the second sub-region is determined, that is, the second sub-region of the same region type adjacent to each sub-region is aggregated to obtain the corresponding grid.

[0075] In an embodiment of the present invention, when determining the adjacent first sub-region or adjacent sub-region set of each sub-region, a set of all longitude and latitude point coordinates of each sub-region can be obtained. For any two sub-regions, based on the set of all longitude and latitude coordinates of each sub-region of the two sub-regions, it is determined whether the two sub-regions have at least two identical longitude and latitude point coordinates. If so, it means that the two sub-regions have a common edge, that is, the two sub-regions are adjacent.

[0076] In an embodiment of the present invention, determining each first sub-region adjacent to a sub-region includes: determining a geocoding set of the sub-region; the geocoding set includes multiple geocodings; determining each candidate sub-region corresponding to each geocoding set including at least one geocoding; determining an adjacency judgment result between the sub-region and each candidate sub-region; determining each first sub-region from each candidate sub-region according to the adjacency judgment result, so as to determine an adjacent sub-region set according to the first sub-region.

[0077] In an embodiment of the present invention, each first sub-region adjacent to a sub-region such as an AOI is determined, and the geocoding set of each sub-region is first calculated. Specifically, for each sub-region, N longitude and latitude point coordinates can be uniformly sampled from all longitude and latitude point coordinate sets constituting the sub-region, where N is a natural number greater than or equal to 1, such as sampling every 10 point coordinates; then, each sampled longitude and latitude point coordinate is encoded by a geocoding method, and the geocoding set of the sub-region is obtained after deduplication, and the geocoding set contains multiple geocodings. Among them, the geocoding method is an algorithm that can convert two-dimensional longitude and latitude point coordinates into a string, such as GeoHash (a geocoding method that encodes two-dimensional longitude and latitude into a string), H3 (a spatial index algorithm based on a hexagonal grid), and other algorithms.

[0078] For example, an AOI consists of 100 longitude and latitude point coordinates, including (x1=[116.45090,37.34523], x2=[116.45091,37.34525], x3=[116.461,37.3665],…, x100=[116.45090,37.34523]). A point set (x1,x11,x21,x31,…) is generated every 10 samples. Each point coordinate is GeoHash-encoded to obtain (wwdu3,wwdu3, wwdu3, wwdu4,…). After deduplication, the geocoding set of the AOI (wwdu3,wwdu4,…) is obtained.

[0079] After determining the set of geocodes for each sub-region, respective first sub-regions for each sub-region are calculated. Specifically, according to each geocode in the geocode set of the current subregion, each geocode set including at least one geocode in the geocode set of the current subregion and each candidate subregion corresponding to each geocode set are determined from the geocode sets of other subregions, that is, if for any other subregion, the other subregion is a subregion other than the current subregion, if the geocode set of the other subregion includes at least one geocode in the geocode set of the current subregion, then the other subregion is used as a candidate subregion; then, whether the current subregion is adjacent to each candidate subregion is judged to determine an adjacent judgment result, and a first subregion is determined according to the adjacent judgment result, and the first subregion is added to the adjacent subregion set of the current subregion, wherein it is judged whether the current subregion is adjacent to the candidate subregion, that is, whether the subregion and the candidate subregion have a common edge, that is, whether the subregion and the candidate subregion have at least two common point coordinates, if so, it means that the candidate subregion is the first subregion, and the adjacent subregion set of the subregion is obtained according to each first subregion, if not, the candidate subregion is not the first subregion.

[0080] For example, if the current AOI1 is encoded as (wwdu3, wwdu4), first find other AOIs whose geographic codes contain wwdu3 or wwdu4 as the AOI set to be compared (AOI2, AOI3, AOI4, AOI5, AOI18, AOI19, AOI20), then compare AOI1 with each AOI in the AOI set to be compared in turn to determine whether the two AOIs have common edges (that is, there are at least two identical point coordinates). If so, the two AOIs are considered adjacent, and this AOI is added to the adjacent AOI matrix of the current AOI1 to obtain the adjacent sub-area set (AOI2, AOI3, AOI4, AOI5). Generate the adjacent AOIs of other AOIs according to this method.

[0081] In the embodiment of the present invention, Figure 3 As shown, the sub-region and the second sub-region are aggregated to determine each grid in the target region, including:

[0082] Step S301: for any sub-region, take the sub-region as the current cluster; pre-aggregate the sub-region with each second sub-region, determine a pre-aggregated cluster corresponding to each second sub-region, and the pre-aggregated cluster includes an aggregation parameter value corresponding to each business indicator;

[0083] Step S302: determine whether each aggregation parameter value in the pre-aggregation cluster is less than or equal to the upper limit of the parameter range of the corresponding business indicator; if so, execute step S303; if not, execute step S304;

[0084] Step S303: determining the pre-aggregation cluster as a candidate pre-aggregation cluster, and updating the current cluster according to the candidate pre-aggregation cluster;

[0085] Step S304: when each aggregation parameter value in the pre-aggregation cluster is greater than or equal to the lower limit of the parameter range of the corresponding business indicator, the current cluster is used as the grid corresponding to the sub-area in the target area.

[0086] In an embodiment of the present invention, when a sub-region is aggregated with a second sub-region, a breadth-first traversal algorithm (i.e., Breadth-Fist Search, BFS) can be used. Each sub-region is used as the current cluster, and then each second sub-region corresponding to the sub-region is aggregated. Before aggregating the current cluster with each second sub-region, pre-aggregation is performed to obtain a pre-aggregated cluster corresponding to each second sub-region, and then a target pre-aggregated cluster can be determined from each pre-aggregated cluster as the updated current cluster, and the next round of traversal is performed until the aggregation stops. Then, any remaining sub-region is selected, and the above process is repeated until all sub-regions are visited, thereby obtaining the remaining sub-regions that cannot be aggregated with any sub-region and do not meet the conditions of being a grid individually.

[0087] Specifically, any sub-region is taken as the current cluster, and the current cluster is pre-aggregated with each second sub-region to obtain a corresponding pre-aggregated cluster, wherein the pre-aggregated cluster includes an aggregated parameter value of each business indicator, and the aggregated parameter value of each business indicator in the pre-aggregated cluster may be the sum of the parameter value of the business indicator of the current cluster and the parameter value of the business indicator of the second sub-region; then, for any pre-aggregated cluster, it is determined whether the aggregated parameter value of each business indicator in the pre-aggregated cluster is less than or equal to the upper limit of the parameter range of the corresponding business indicator of the grid, that is, whether the pre-aggregated cluster meets the grid generation condition, wherein the grid may be a grid of the same area type as the current cluster;

[0088] If so, the pre-aggregation cluster meets the grid generation condition, and the pre-aggregation cluster is determined as a candidate aggregation cluster. The current cluster is updated according to the candidate aggregation cluster. That is, if the aggregation parameter value of the number of covered stores, the aggregation parameter value of the covered area, and the aggregation parameter value of the annual GMV in the pre-aggregation cluster are respectively less than the upper limit of the parameter range of the number of covered stores, the upper limit of the parameter range of the covered area, and the upper limit of the parameter range of the annual GMV of the grid, then the pre-aggregation cluster meets the grid generation condition and can be used as a candidate pre-aggregation cluster; according to the updated current cluster, continue the next round of traversal, aggregate the updated current cluster with the remaining second sub-region of the sub-region until the aggregation stops;

[0089] If not, the aggregation stops, and then it is determined whether the current cluster meets the grid generation conditions, that is, whether the aggregation parameter value of each business indicator of the current cluster (if the current cluster is a sub-region, the parameter value of each business indicator) is greater than or equal to the lower limit of the parameter range of the business indicator corresponding to the grid, that is, whether the aggregation parameter value of each business indicator of the current cluster is within the parameter range of the business indicator corresponding to the grid. If so, the current cluster can be used as a grid, otherwise, the current cluster cannot be used as a grid. The sub-regions that cannot be aggregated with other sub-regions and cannot be used as a grid are the remaining sub-regions.

[0090] In the embodiment of the present invention, if the number of candidate pre-aggregation clusters is one, the candidate pre-aggregation cluster is used as the updated current cluster.

[0091] In an embodiment of the present invention, there are multiple candidate pre-aggregation clusters, and updating the current cluster according to the candidate pre-aggregation clusters includes: determining the number of business indicators whose aggregation parameter values ​​in the candidate pre-aggregation clusters are within the parameter range of the corresponding business indicators; determining a target pre-aggregation cluster from each candidate pre-aggregation cluster according to the number of business indicators; and updating the current cluster according to the target pre-aggregation cluster.

[0092] In an embodiment of the present invention, if there are multiple candidate pre-aggregation clusters, one can be randomly selected from each candidate pre-aggregation cluster as a candidate pre-aggregation cluster. In order to improve the aggregation efficiency and aggregation effect, a greedy clustering algorithm is used to determine the optimal pre-aggregation cluster, that is, the target pre-aggregation cluster, from each candidate pre-aggregation cluster. Specifically, the number of business indicators whose aggregation parameter values ​​of each candidate pre-aggregation cluster are within the parameter range of the corresponding business indicator can be determined, that is, it can be determined that there are several business indicators in the candidate pre-aggregation cluster whose aggregation parameter values ​​are within the parameter range. According to the number of business indicators, the target pre-aggregation cluster can be determined, and the target pre-aggregation cluster can be used as the updated current cluster, that is, the second sub-area corresponding to the target pre-aggregation cluster is aggregated with the current cluster to update the current cluster.

[0093] In an embodiment of the present invention, a target pre-aggregation cluster is determined from each candidate pre-aggregation cluster according to the number of business indicators, including: judging whether the number of candidate pre-aggregation clusters with the largest number of business indicators is greater than 1; if not, taking the candidate pre-aggregation cluster with the largest number of business indicators as the target pre-aggregation cluster; if so, determining the sum of the achievement rates of each indicator corresponding to each candidate pre-aggregation cluster with the largest number of business indicators; and determining the target pre-aggregation cluster according to the sum of the achievement rates of each indicator.

[0094] In an embodiment of the present invention, if the number of candidate pre-aggregation clusters with the largest number of business indicators is one, the candidate pre-aggregation cluster with the largest number of business indicators is used as the target pre-aggregation cluster; if there are multiple candidate pre-aggregation clusters with the largest number of business indicators, the sum of the achievement rates of each indicator of each candidate pre-aggregation cluster in the multiple candidate pre-aggregation clusters is calculated, and the candidate pre-aggregation cluster with the largest sum of the achievement rates of each indicator is used as the target pre-aggregation cluster. The sum of the achievement rates of each indicator is the sum of the scores of each indicator, and the score of each indicator = (aggregation parameter value - lower limit of parameter range) / (upper limit of parameter range - lower limit of parameter range). For example, if the parameter range of the number of covered stores of the grid is 20-60, and the aggregation parameter value of the number of covered stores is 10, then the indicator score of the number of covered stores is (10-20) / (60-20) = -0.25; if the aggregation parameter value of the number of covered stores is 30, then the indicator score of the number of covered stores is (30-20) / (60-20) = 0.25. An indicator score less than 0 indicates that the lower limit of the parameter range has not been reached, a score in [0,1] indicates that it is within the parameter range, and the closer the score is to 1, the closer it is to the upper limit of the parameter range.

[0095] In the embodiment of the present invention, after the current cluster is used as the grid corresponding to the sub-region in the target region, the method further includes:

[0096] Obtain each remaining sub-area in the target area that does not belong to any grid;

[0097] For each remaining sub-region, obtaining each candidate grid adjacent to each remaining sub-region and the region type of each candidate grid;

[0098] Determining a target grid from the candidate grids according to a preset area type priority;

[0099] The target grid is one, and the remaining sub-areas are assigned to the target grid; or

[0100] There are multiple target grids, and the sum of the achievement rates of the indicators of the remaining sub-regions and each target grid is determined, and the remaining sub-regions are assigned to the target grid with the lowest sum of the achievement rates of the indicators.

[0101] In the embodiment of the present invention, after the current cluster is used as the grid corresponding to the sub-region in the target region, the remaining sub-regions that do not belong to any grid and cannot form a grid are obtained. For each remaining sub-region, each candidate grid adjacent to the remaining sub-region is obtained, that is, the candidate grid is the grid where the sub-region adjacent to the remaining sub-region is located, and each candidate grid has a corresponding region type.

[0102] In one implementation of the embodiments of the present invention, a candidate grid with the same area type as the remaining sub-area can be selected as the target grid according to the area type of the remaining sub-area. If there is no candidate grid with the same area type as the remaining sub-area, the target grid is determined from each candidate grid according to a preset area type priority.

[0103] In another implementation of the present invention, the target grid can be determined according to the priority of each candidate grid according to the preset area type priority, and the remaining sub-areas can be assigned to the target grid. The preset area type priority can be customized, such as the order of priority from high to low can be: campus type> commercial office type> community residential type> scenic leisure, hospital, travel type> other types.

[0104] If there is one target grid, the remaining sub-areas are directly assigned to the target grid; if there are multiple target grids, the sum of the achievement rates of each indicator of the remaining sub-areas and each target grid is calculated, that is, the remaining sub-areas are pre-aggregated with each target grid to obtain a pre-aggregated grid, and the aggregation parameter values ​​of each business indicator of each pre-aggregated grid are calculated. The score of each indicator is calculated based on the aggregation parameter value of each business indicator. The sum of the achievement rates of each indicator is the sum of the scores of each indicator. The score of each indicator = (aggregation parameter value-lower limit of parameter range) / (upper limit of parameter range-lower limit of parameter range). For example, if the parameter range of the number of covered stores of the grid is 20-60, and the number of covered stores of the pre-aggregated grid is 70, then the score of the number of covered stores indicator is (70-20) / (60-20)=1.25. A score greater than 1 indicates that the aggregation parameter value exceeds the upper limit of the parameter range. The more it exceeds, the higher the score. The score of the indicator that does not exceed the upper limit of the parameter range is less than 1. After determining the sum of the achievement rates of each indicator of each pre-aggregated grid, the remaining sub-areas are assigned to the target grid with the lowest sum of the achievement rates of each indicator.

[0105] Figure 4The figure is a flowchart of a method for grid drawing according to an embodiment of the present invention. (a) shows the original AOI distribution, i.e., each AOI in the target area, the type of each AOI, and the AOI adjacent to each AOI. It should be noted that the AOI shape shown in the figure has nothing to do with the actual AOI area, and is only a schematic diagram for illustrating the aggregation process of each AOI; then the campus 1 AOI is selected as the current cluster, and pre-aggregated with the adjacent campus 2 AOI and campus 3 AOI of the same type, respectively, to obtain the pre-aggregated cluster 1 corresponding to the campus 2 AOI and the pre-aggregated cluster 2 corresponding to the campus 3 AOI. After the pre-aggregated cluster 1 and the pre-aggregated cluster 2 are compared, they are first aggregated with the campus 2 AOI, and then aggregated with the campus 3 AOI to obtain the updated current cluster; then, the pre-aggregated clusters are further aggregated with the campus 4 AOI and the campus 5 AOI, respectively. Pre-aggregation is performed to obtain pre-aggregation cluster 3 and pre-aggregation cluster 4 of campus 4 and campus 5 AOI respectively. The aggregation parameter value of at least one business indicator in pre-aggregation cluster 3 and pre-aggregation cluster 4 exceeds the upper limit of the parameter range of the corresponding business indicator, and the aggregation stops. Campus 1 AOI, campus 2 AOI and campus 3 AOI are output as a grid. According to the above method, other AOIs are selected to repeat the aggregation process to obtain the result shown in (b), wherein campus 1 AOI, campus 2 AOI and campus 3 AOI generate a campus-type grid 1, campus 5 AOI and campus 6 AOI generate a campus-type grid 4, residential 1 AOI and residential 2 AOI generate a residential-type grid 2, and hospital 1 AOI generates a hospital-type grid 3. The remaining campus 4 AOI and hospital 2 AOI cannot be aggregated with any AOI and do not meet the conditions of being a grid individually; then the hospital 2 AOI can be assigned to the same type of grid 3; the campus 4 AOI is pre-aggregated with the adjacent grids 1 and 4, and the sum of the total indicator success rate is calculated respectively. It is found that the total indicator success rate is the lowest when it is assigned to grid 4, so it is selected to be assigned to grid 4; the grids of the target area are output, as shown in (c): grid 1: campus 1 AOI, campus 2 AOI, campus 3 AOI, grid 2: residential 1 AOI, residential 2 AOI, grid 3: hospital 1 AOI, hospital 2 AOI, grid 4: campus 5 AOI, campus 6 AOI and campus 4 AOI.

[0106] Figure 5The present invention is a flowchart of a method for drawing a grid according to an embodiment of the present invention. The method for drawing a grid can be implemented by a grid drawing platform. First, the user logs in to the grid drawing platform and clicks the smart drawing button. In the pop-up window, the user can set each business indicator in the target area and the parameter range of each business indicator. The grid drawing platform is connected to the algorithm model, and the algorithm model is processed by the algorithm model. The algorithm model is an algorithm model based on a greedy clustering strategy. Specifically, the parameter values ​​of each sub-area in the target area and each business indicator of each sub-area are obtained. According to the parameter value of each business indicator of each sub-area and the parameter range of the corresponding business indicator of each grid, each grid in the target area is obtained, and then the algorithm result, i.e., each grid, is output. The algorithm result layer is rendered on the page. It is determined whether the algorithm result meets expectations. If it does not meet expectations, the business indicator is reset and the above process is repeated. If it meets expectations, the grid can be edited and adjusted. Then the grid is saved and the process ends.

[0107] In an embodiment of the present invention, after determining each grid in the target area, a grid identifier corresponding to each grid is generated, and then each grid layer is rendered to the page to visually display the drawn grids to the user. The user can determine whether to re-execute the grid drawing process according to needs. The user can also select a single grid in the page to customize the grid, such as dragging and moving the vertices of the grid for editing.

[0108] The grid drawing method of the embodiment of the present invention receives a grid drawing request for a target area, wherein the grid drawing request includes a parameter range of each business indicator of each grid; determines each sub-area in the target area and the parameter value of each business indicator of each sub-area; and aggregates each sub-area according to the parameter value of each business indicator of each sub-area and the parameter range of each business indicator of each grid to obtain each grid in the target area. The method realizes intelligent grid drawing according to the parameter value of the business indicator of the sub-area and the parameter range of the business indicator of the grid, improves the efficiency and effect of grid drawing, reduces the operation cost, and overcomes the problem of low efficiency and high operation cost caused by manual grid drawing; the method aggregates adjacent sub-areas into grids and adopts an algorithm model of a greedy clustering strategy so that the business indicators of each grid meet the business needs as much as possible, and can be applied to the grid drawing of the city dimension in the instant retail business scenario; the method supports users to make custom adjustments and real-time calculations during the grid drawing process; the algorithm model is connected with the automated grid drawing platform to realize the real-time visualization of the results of the algorithm model, thereby improving the user experience.

[0109] According to another aspect of the embodiment of the present invention, Figure 6 As shown, a grid drawing device 600 is provided, comprising:

[0110] A receiving module 601 receives a grid drawing request for a target area, where the grid drawing request includes a plurality of business indicators of each grid in the target area and a parameter range corresponding to each business indicator;

[0111] A first determination module 602 determines each sub-area in the target area and a parameter value corresponding to each business indicator of each sub-area;

[0112] The second determination module 603 aggregates the sub-regions in the target region according to the parameter value corresponding to each business indicator of each sub-region and the parameter range corresponding to each business indicator of each grid, so as to determine each grid in the target region.

[0113] In an embodiment of the present invention, the sub-region has a corresponding region type, and the second determination module 603 is further used to: determine each first sub-region corresponding to the sub-region; obtain a second sub-region having the same region type as the sub-region from each first sub-region; aggregate the sub-region and the second sub-region to obtain a grid corresponding to the sub-region.

[0114] In this embodiment of the present invention, the second determining module 603 is further configured to:

[0115] Determine a geocode set of sub-regions; the geocode set contains multiple geocodes;

[0116] Determine each candidate sub-region corresponding to each geocoding set including at least one geocoding;

[0117] Determine the adjacent judgment result of the sub-region and each candidate sub-region;

[0118] Each first sub-region is determined from each candidate sub-region according to the adjacent judgment result.

[0119] In this embodiment of the present invention, the second determining module 603 is further configured to:

[0120] For any of the sub-regions, taking the sub-region as a current cluster;

[0121] Pre-aggregating the sub-region with each of the second sub-regions, and determining a pre-aggregation cluster corresponding to each of the second sub-regions, wherein the pre-aggregation cluster includes an aggregation parameter value corresponding to each of the service indicators;

[0122] Determining whether each of the aggregation parameter values ​​in the pre-aggregation cluster is less than or equal to an upper limit of a parameter range of a corresponding service indicator;

[0123] If so, determining that the pre-aggregation cluster is a candidate pre-aggregation cluster, and updating the current cluster according to the candidate pre-aggregation cluster;

[0124] If not, when each of the aggregation parameter values ​​in the pre-aggregation cluster is greater than or equal to the lower limit of the parameter range of the corresponding service indicator, the current cluster is used as a grid in the target area.

[0125] In an embodiment of the present invention, there are multiple candidate pre-aggregation clusters, and the second determination module 603 is further used to: determine the number of business indicators whose aggregation parameter values ​​in the candidate pre-aggregation clusters are within the parameter range of the corresponding business indicators; determine a target pre-aggregation cluster from each candidate pre-aggregation cluster according to the number of business indicators; and update the current cluster according to the target pre-aggregation cluster.

[0126] In an embodiment of the present invention, the second determination module 603 is further used to: determine whether the number of the candidate pre-aggregation clusters with the largest number of business indicators is greater than 1; if not, use the candidate pre-aggregation cluster with the largest number of business indicators as the target pre-aggregation cluster; if so, determine the sum of the achievement rates of each indicator corresponding to each candidate pre-aggregation cluster with the largest number of business indicators; and determine the target pre-aggregation cluster based on the sum of the achievement rates of each indicator.

[0127] In the embodiment of the present invention, after taking the current cluster as the grid corresponding to the sub-region in the target region, the second determining module 603 is further configured to:

[0128] Acquire each remaining sub-area in the target area that does not belong to any grid;

[0129] For each of the remaining sub-regions, obtaining each candidate grid adjacent to each of the remaining sub-regions and the region type of each of the candidate grids;

[0130] Determining a target grid from the candidate grids according to a preset area type priority;

[0131] The target grid is one, and the remaining sub-areas are assigned to the target grid; or

[0132] There are multiple target grids, and the sum of the achievement rates of the indicators of the remaining sub-regions and each target grid is determined, and the remaining sub-regions are assigned to the target grid with the lowest sum of the achievement rates of the indicators.

[0133] According to another aspect of an embodiment of the present invention, an electronic device is provided, comprising: one or more processors; a storage device for storing one or more programs, wherein when the one or more programs are executed by the one or more processors, the one or more processors implement the grid drawing method provided by the present invention.

[0134] According to another aspect of an embodiment of the present invention, a computer readable medium is provided, on which a computer program is stored. When the program is executed by a processor, the method for grid drawing provided by the present invention is implemented.

[0135] Figure 7 An exemplary system architecture 700 is shown to which the method or apparatus for grid drawing according to an embodiment of the present invention may be applied.

[0136] like Figure 7 As shown, system architecture 700 may include terminal devices 701, 702, 703, network 704 and server 705. Network 704 is used to provide a medium for communication links between terminal devices 701, 702, 703 and server 705. Network 704 may include various connection types, such as wired, wireless communication links or optical fiber cables, etc.

[0137] The user can use the terminal devices 701, 702, 703 to interact with the server 705 through the network 704 to receive or send messages, etc. Various communication client applications can be installed on the terminal devices 701, 702, 703, such as shopping applications, web browser applications, search applications, instant messaging tools, email clients, social platform software, etc. (only for example).

[0138] The terminal devices 701 , 702 , and 703 may be various electronic devices having a display screen and supporting web browsing, including but not limited to smart phones, tablet computers, laptop computers, and desktop computers.

[0139] The server 705 may be a server that provides various services, such as a backend management server (only an example) that provides support for shopping websites browsed by users using the terminal devices 701, 702, and 703. The backend management server may analyze and process the received data such as product information query requests, and feed back the processing results (such as target push information, product information - only an example) to the terminal device.

[0140] It should be noted that the grid drawing method provided in the embodiment of the present invention is generally executed by the server 705 , and accordingly, the grid drawing device is generally disposed in the server 705 .

[0141] It should be understood that Figure 7 The number of terminal devices, networks and servers in the embodiment is only for illustration. Any number of terminal devices, networks and servers may be provided according to implementation requirements.

[0142] Reference below Figure 8 , which shows a schematic diagram of the structure of a computer system 800 of a terminal device suitable for implementing an embodiment of the present invention. Figure 8The terminal device 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.

[0143] like Figure 8 As shown, the computer system 800 includes a central processing unit (CPU) 801, which can perform various appropriate actions and processes according to a program stored in a read-only memory (ROM) 802 or a program loaded from a storage part 808 to a random access memory (RAM) 803. In the RAM 803, various programs and data required for the operation of the system 800 are also stored. The CPU 801, the ROM 802, and the RAM 803 are connected to each other through a bus 804. An input / output (I / O) interface 805 is also connected to the bus 804.

[0144] The following components are connected to the I / O interface 805: an input section 806 including a keyboard, a mouse, etc.; an output section 807 including a cathode ray tube (CRT), a liquid crystal display (LCD), etc., and a speaker, etc.; a storage section 808 including a hard disk, etc.; and a communication section 809 including a network interface card such as a LAN card, a modem, etc. The communication section 809 performs communication processing via a network such as the Internet. A drive 810 is also connected to the I / O interface 805 as needed. A removable medium 811, such as a magnetic disk, an optical disk, a magneto-optical disk, a semiconductor memory, etc., is installed on the drive 810 as needed, so that a computer program read therefrom is installed into the storage section 808 as needed.

[0145] In particular, according to the embodiments disclosed in the present invention, the process described above with reference to the flowchart can be implemented as a computer software program. For example, the embodiments disclosed in the present invention include a computer program product, which includes a computer program carried on a computer-readable medium, and the computer program contains program code for executing the method shown in the flowchart. In such an embodiment, the computer program can be downloaded and installed from the network through the communication part 809, and / or installed from the removable medium 811. When the computer program is executed by the central processing unit (CPU) 801, the above-mentioned functions defined in the system of the present invention are executed.

[0146] It should be noted that the computer-readable medium shown in the present invention may be a computer-readable signal medium or a computer-readable storage medium or any combination of the above two. The computer-readable storage medium may 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 of computer-readable storage media may include, but are not limited to: 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 the present invention, a computer-readable storage medium may be any tangible medium containing or storing a program that can be used by or in combination with an instruction execution system, device or device. In the present invention, a computer-readable signal medium may include a data signal propagated in a baseband or as part of a carrier wave, which carries a computer-readable program code. This propagated data signal 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 computer-readable storage media, which may send, propagate or transmit a program for use by or in conjunction with an instruction execution system, apparatus or device. The program code contained on the computer-readable medium may be transmitted using any appropriate medium, including but not limited to: wireless, wire, optical cable, RF, etc., or any suitable combination of the above.

[0147] The flow chart and block diagram in the accompanying drawings illustrate the possible architecture, function and operation of the system, method and computer program product according to various embodiments of the present invention. In this regard, each box in the flow chart or block diagram can represent a module, a program segment, or a part of a code, and the above-mentioned module, program segment, or a part of a code contains one or more executable instructions for realizing the specified logical function. It should also be noted that in some alternative implementations, the functions marked in the box can also occur in a different order from the order marked in the accompanying drawings. For example, two boxes represented in succession can actually be executed substantially in parallel, and they can sometimes be executed in the opposite order, depending on the functions involved. It should also be noted that each box in the block diagram or flow chart, and the combination of the boxes in the block diagram or flow chart can be implemented with a dedicated hardware-based system that performs a specified function or operation, or can be implemented with a combination of dedicated hardware and computer instructions.

[0148] The modules involved in the embodiments of the present invention may be implemented by software or hardware. The modules described may also be set in a processor, for example, it may be described as: a processor includes a receiving module, a first determining module, and a second determining module. The names of these modules do not constitute a limitation on the modules themselves in some cases, for example, the receiving module may also be described as a "module for receiving a mesh drawing request for a target area".

[0149] As another aspect, the present invention also provides a computer-readable medium, which may be included in the device described in the above embodiment; or may exist independently without being assembled into the device. The above computer-readable medium carries one or more programs, and when the above one or more programs are executed by a device, the device includes: receiving a grid drawing request for a target area, the grid drawing request including multiple business indicators of each grid in the target area and a parameter range corresponding to each business indicator; determining each sub-area in the target area and a parameter value corresponding to each business indicator of each sub-area; according to the parameter value corresponding to each business indicator of each sub-area and the parameter range corresponding to each business indicator of each grid, the sub-areas in the target area are aggregated to determine each grid in the target area.

[0150] According to the technical solution of the embodiment of the present invention, the method for grid drawing of the embodiment of the present invention receives a grid drawing request for a target area, wherein the grid drawing request includes the parameter range of each business indicator of each grid; determines the parameter values ​​of each sub-area and each business indicator of each sub-area in the target area; aggregates each sub-area according to the parameter value of each business indicator of each sub-area and the parameter range of each business indicator of each grid, and obtains each grid in the target area. The method realizes intelligent grid drawing according to the parameter value of the business indicator of the sub-area and the parameter range of the business indicator of the grid, improves the efficiency and effect of grid drawing, reduces the operation cost, and overcomes the problem of low efficiency and high operation cost caused by manual grid drawing; the method aggregates adjacent sub-areas into grids and adopts an algorithm model of a greedy clustering strategy, so that the business indicators of each grid meet the business needs as much as possible; the method supports users to make custom adjustments and real-time calculations during the grid drawing process; the algorithm model is connected with the automated grid drawing platform, and the results of the algorithm model are visualized in real time, which improves the user experience.

[0151] The above specific implementations do not constitute a limitation on the protection scope of the present invention. It should be understood by those skilled in the art that various modifications, combinations, sub-combinations and substitutions may occur depending on design requirements and other factors. Any modification, equivalent substitution and improvement made within the spirit and principle of the present invention shall be included in the protection scope of the present invention.

Claims

1. A method for drawing a grid, characterized in that: include: receiving a grid drawing request for a target area, the grid drawing request including a plurality of business indicators of each grid in the target area and a parameter range corresponding to each of the business indicators; Determine each sub-area in the target area and a parameter value corresponding to each of the business indicators in each of the sub-areas; The sub-regions in the target region are aggregated according to the parameter value corresponding to each of the business indicators in each of the sub-regions and the parameter range corresponding to each of the business indicators in each of the grids to determine the grids in the target region.

2. The method according to claim 1, characterized in that The sub-regions have corresponding region types, and the sub-regions in the target region are aggregated, including: Determine each first sub-region corresponding to and adjacent to the sub-region; Acquire, from each of the first sub-regions, a second sub-region having the same region type as the sub-region; The sub-region and the second sub-region are aggregated to obtain a grid corresponding to the sub-region.

3. The method according to claim 2, characterized in that Determining each first sub-region corresponding to and adjacent to the sub-region includes: Determine a geocoding set of the sub-region; the geocoding set includes multiple geocodings; Determining each candidate sub-region corresponding to each set of geocodes including at least one of the geocodes; Determine an adjacent judgment result between the sub-region and each of the candidate sub-regions; Determine each first sub-region from each candidate sub-region according to the adjacent judgment result.

4. The method according to claim 2, characterized in that: Aggregating the sub-region and the second sub-region includes: For any of the sub-regions, taking the sub-region as a current cluster; Pre-aggregating the sub-region with each of the second sub-regions, and determining a pre-aggregation cluster corresponding to each of the second sub-regions, wherein the pre-aggregation cluster includes an aggregation parameter value corresponding to each of the service indicators; Determining whether each of the aggregation parameter values ​​in the pre-aggregation cluster is less than or equal to an upper limit of a parameter range of a corresponding service indicator; If so, determining that the pre-aggregation cluster is a candidate pre-aggregation cluster, and updating the current cluster according to the candidate pre-aggregation cluster; If not, when each of the aggregation parameter values ​​in the pre-aggregation cluster is greater than or equal to the lower limit of the parameter range of the corresponding service indicator, the current cluster is used as the grid corresponding to the sub-area in the target area.

5. The method according to claim 4, characterized in that There are multiple candidate pre-aggregation clusters, and updating the current cluster according to the candidate pre-aggregation clusters includes: Determining the number of business indicators whose aggregation parameter values ​​in the candidate pre-aggregation cluster are within a parameter range of a corresponding business indicator; Determine a target pre-aggregation cluster from each candidate pre-aggregation cluster according to the number of business indicators; The current cluster is updated according to the target pre-aggregation cluster.

6. The method according to claim 5, characterized in that Determining a target pre-aggregation cluster from each candidate pre-aggregation cluster according to the number of business indicators includes: Determine whether the number of candidate pre-aggregation clusters with the largest number of business indicators is greater than 1; If not, taking the candidate pre-aggregation cluster with the largest number of business indicators as the target pre-aggregation cluster; If so, determine the sum of achievement rates of each indicator corresponding to each candidate pre-aggregation cluster with the largest number of business indicators; and determine the target pre-aggregation cluster according to the sum of achievement rates of each indicator.

7. The method according to claim 4, characterized in that After the current cluster is used as the grid corresponding to the sub-region in the target region, the method further includes: Acquire each remaining sub-area in the target area that does not belong to any grid; For each of the remaining sub-regions, obtaining each candidate grid adjacent to each of the remaining sub-regions and the region type of each of the candidate grids; Determining a target grid from the candidate grids according to a preset area type priority; The target grid is one, and the remaining sub-areas are assigned to the target grid; or There are multiple target grids, and the sum of the achievement rates of the indicators of the remaining sub-regions and each target grid is determined, and the remaining sub-regions are assigned to the target grid with the lowest sum of the achievement rates of the indicators.

8. A device for drawing a grid, characterized in that: include: A receiving module receives a grid drawing request for a target area, wherein the grid drawing request includes a plurality of business indicators of each grid in the target area and a parameter range corresponding to each of the business indicators; A first determination module determines each sub-area in the target area and a parameter value corresponding to each business indicator of each sub-area; The second determination module aggregates the sub-areas in the target area according to the parameter value corresponding to each of the business indicators in each of the sub-areas and the parameter range corresponding to each of the business indicators in each of the grids to determine the grids in the target area.

9. An electronic device, characterized in that: include: one or more processors; a storage device for storing one or more programs, When the one or more programs are executed by the one or more processors, the one or more processors implement the method according to any one of claims 1 to 7.

10. A computer readable medium having a computer program stored thereon, characterized in that: When the program is executed by a processor, the method according to any one of claims 1 to 7 is implemented.

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