TW202219851A - Resource allocation method and system based on binary space partition capable of allocating marketing resources for potential enterprise customers - Google Patents

Abstract

In a resource allocation method and system, an allocation server: divides the predetermined geographic area into a plurality of geographic areas by using a binary space partition method so that each geographic area has only one marketing resource and obtains geographic area data of each geographic area, according to multiple pieces of resource location data and multiple pieces of object location data and geographic range data with respect to multiple marketing resources and multiple reference partition objects within a predetermined geographic range; according to the object location data and all geographic area data, uses the binary space partition relationship to build a binary tree; and according to the collected multiple customer data of multiple potential enterprise customers and the binary tree, allocates each potential enterprise customer to the corresponding marketing resource, so that the number of all potential customers allocated to each marketing resource does not exceed its allocated capacity.

Description

Resource allocation method and system based on binary space segmentation

The present invention relates to resource allocation of enterprise marketing, in particular to a resource allocation method and system based on binary space division.

Before marketing related financial products to potential corporate customers, financial enterprises usually use geographic administrative regions or geographic distances as the basis for how to allocate marketing resources (such as all branches to which financial enterprises belong). However, in fact, there may be multiple marketing resources (such as branches of multiple bank branches) in the same geographical administrative area, or there may be no marketing resources. In the aforementioned situation, it will be difficult to make effective decisions for all potential corporate customers Marketing resource allocation. Also, if the allocated marketing resources (ie, a branch of a bank branch) are determined according to the geographic location of each potential corporate customer (such as the registered address of the corporate customer), for each potential corporate customer, the Allocate to the marketing resources that are geographically closest to it. Such an allocation method will no longer consider other objective factors other than geographical distance, such as traffic, terrain, field responsibility areas and other factors.

Therefore, under the fierce market competition, for a large number of potential corporate customers, how to come up with a resource allocation method that can be highly efficient and conducive to the promotion of marketing business has become one of the urgent issues that financial enterprises need to solve.

Therefore, the purpose of the present invention is to provide a resource allocation method and system based on binary space division, which can overcome at least one disadvantage of the prior art.

Therefore, a resource allocation method based on binary space segmentation provided by the present invention is suitable for P (P≥2) marketing resources provided by a financial institution with the same allocation capacity N and located in a predetermined geographical range and utilizing A computer system is implemented, and includes the following steps: (A) Obtaining resource location data indicating the geographical locations of the P marketing resources, geographical range data of the predetermined geographical range, and Q (P>Q≥1) ) pen respectively indicates the object location data of the geographic locations of Q different reference division objects located within the predetermined geographical range; (B) according to the P pieces of resource location data, the Q pieces of object location data and the geographical range data, and Using the binary space division method, divide the predetermined geographic area into P geographic areas, so that each geographic area has only one of the P marketing resources corresponding to one of the marketing resources, and obtain P pens to indicate the P Geographical area data of geographical areas, wherein the P geographical areas are divided by the Q reference division objects; (C) according to the Q pieces of object location data and the P pieces of geographical area data, using a binary space division relationship, Build a binary tree with Q non-terminal nodes corresponding to the Q reference division objects and P leaf nodes respectively corresponding to the P geographic regions, wherein each non-terminal node stores a data indicating the corresponding reference division object. Object location data of geographic locations, and each leaf node stores geographic area data indicating the corresponding geographic area; (D) collect M (M≤N×P) pieces of information about M potential locations located within the predetermined geographic range. Customer data of corporate customers, each customer data at least indicates the geographic location of the corresponding potential corporate customer; and (E) according to the M customer data and the binary tree, assign each potential corporate customer to the P marketing One of the resources corresponds to the marketing resources, so that the number of all potential customers allocated to each marketing resource does not exceed the allocated capacity N, wherein for each potential enterprise customer, the marketing resources in the geographic area where the potential enterprise customer is located As the corresponding marketing resource, or the marketing resource in the geographic area corresponding to another leaf node having an adjacent relationship with a leaf node corresponding to the geographic area where the potential enterprise customer is located, as the corresponding marketing resource.

In the resource allocation method based on binary space division of the present invention, each customer data also indicates the capital amount of the corresponding potential enterprise customer, and the computer system also utilizes the sorting method related to the capital amount to assign the M potential enterprises Customers are sorted to get a sorted result. The computer system executes an allocation process for each potential enterprise customer according to the sorting result.

In the resource allocation method based on binary space segmentation of the present invention, for each potential customer, when the computer system confirms that the marketing resources in the geographic area where the potential corporate customer is located have been allocated to the cumulative number of potential corporate customers is less than When the allocated capacity is N, the computer system uses the marketing resources in the geographic area where the potential enterprise customer is located as the corresponding marketing resources, and updates the accumulated quantity corresponding to the corresponding marketing resources; and when the computer system confirms the potential When the cumulative number of potential enterprise customers allocated to the marketing resources in the geographical area where the enterprise customer is located has reached the allocated capacity N, the computer system sequentially confirms and corresponds to a leaf node corresponding to the geographical area where the potential enterprise customer is located. Whether the cumulative number of potential enterprise customers in the geographic area corresponding to one or more candidate leaf nodes starting from the nearest neighbor is less than the allocated capacity N until a candidate leaf node is identified for the first time. When the cumulative number of marketing resources in the corresponding geographic region is less than the allocation capacity N, the marketing resources in the geographic region corresponding to the candidate leaf node are used as the corresponding marketing resources, and the corresponding marketing resources are updated. Cumulative quantity.

The resource allocation method based on binary space partitioning of the present invention further comprises the step of: (F) sending a user terminal provided by each marketing resource to a distribution result containing the customer data of all potential customers allocated by the marketing resource , .

Therefore, a resource allocation system based on binary space segmentation provided by the present invention is suitable for P (P≥2) marketing resources provided by a financial institution with the same allocation capacity N and located in a predetermined geographical range, and includes , and includes a data server and a distribution server.

The data server is configured to collect M (M≤N×P) pieces of customer data about M potential enterprise customers located in the predetermined geographic range, and each customer data at least indicates the geographic location of the corresponding potential enterprise customer Location.

The distribution server is connected to the data server to receive the M pieces of customer data, and includes a storage module and a processing module electrically connected to the storage module. The allocation server obtains resource location data of P pens indicating the geographic locations of the P marketing resources, geographic range data of the predetermined geographic range, and Q (P>Q≥1) pens respectively indicating that the P marketing resources are located within the predetermined geographic range The object location data of the Q different reference divisions of the object's geographic location.

The processing module of the distribution server divides the predetermined geographic area into P geographic areas according to the obtained P pieces of resource location data, the Q pieces of object location data, and the geographic area data, and using a binary space division method , so that each geographic region has only one of the P marketing resources corresponding to one of the marketing resources, and obtains P pieces of geographic region data indicating the P geographic regions, wherein the P geographic regions are composed of the Q Divided by reference to dividing objects.

The processing module of the distribution server establishes a non-terminal node with Q pieces corresponding to the Q reference division objects respectively by using the binary space division relationship according to the obtained position data of the Q objects and the P pieces of geographical area data. and P binary trees respectively corresponding to the leaf nodes of the P geographic regions, and storing the binary trees in the storage module. Each non-terminal node of the binary tree stores object location data indicating the geographic location of the corresponding reference divided object, and each leaf node in the binary tree stores geographic area data indicating the corresponding geographic region.

The processing module of the allocation server allocates each potential enterprise customer to one of the P marketing resources corresponding to the M pieces of customer data received from the data server and the binary tree stored by the storage module marketing resources, so that the number of all potential customers allocated to each marketing resource does not exceed the allocation capacity N, wherein for each potential enterprise customer, the marketing resources in the geographic area where the potential enterprise customer is located are used as the corresponding marketing A resource, or a marketing resource in a geographic area corresponding to another leaf node that has an adjacent relationship with a leaf node corresponding to the geographic area where the potential enterprise customer is located, is used as the corresponding marketing resource.

In the resource allocation system based on binary space division of the present invention, each customer data also indicates the capital amount of the corresponding potential enterprise customer. According to the M pieces of customer data, the data server sorts the M potential corporate customers in a capital-related sorting manner to obtain a sorting result, and transmits the M pieces of customer data together with the sorting result to the Allocate servers. The processing module of the distribution server executes the distribution process of each potential enterprise customer according to the sorting result from the data server.

In the resource allocation system based on binary space division of the present invention, in the allocation server, the storage module further stores an allocation record table, and the allocation record table records the potential enterprise customers to which each marketing resource has been allocated. For each potential corporate customer, when the processing module confirms that the cumulative number of potential corporate customers recorded by the marketing resources in the geographic area where the potential corporate customer is located in the allocation record table stored by the storage module is less than the allocation When the capacity is N, the processing module takes the marketing resources in the geographic area where the potential enterprise customer is located as the corresponding marketing resource, and records the new location of the potential enterprise customer in the allocation record table stored in the storage module, and when the processing module confirms that in the allocation record table stored by the storage module, the cumulative number of potential corporate customers to which the marketing resources in the geographic region where the potential corporate customer is located has been allocated has reached the allocation capacity N, The processing module sequentially confirms, in the allocation record table stored by the storage module, one or more candidate leaf nodes from the nearest neighbor in the degree of proximity to a leaf node corresponding to the geographic area where the potential enterprise customer is located. Whether the cumulative number of potential enterprise customers recorded by the marketing resources in the corresponding geographical area is less than the allocation capacity N, until it is confirmed for the first time that the cumulative number of marketing resources in the geographical area corresponding to a candidate leaf node is less than the allocation capacity N At the time, the marketing resource in the geographic area corresponding to the candidate leaf node is used as the corresponding marketing resource, and the new location of the potential enterprise customer is recorded in the allocation record table stored in the storage module.

In the resource allocation system based on binary space division of the present invention, the processing module of the allocation server generates P pieces corresponding to the P pieces according to the M pieces of customer data and the allocation record table stored in the storage module. Assignment results of marketing resources, each assignment result indicates a corresponding marketing resource among the P marketing resources and includes customer data of all potential customers to which the corresponding marketing resource is assigned. The allocation server sends a corresponding allocation result among the P allocation results to a user terminal provided by each marketing resource.

The effect of the present invention is: since the predetermined geographic area is based on reference segmentation objects taking into account traffic facilities, natural geographic environment, geographic locations of the marketing resources, etc. and uses binary space segmentation to divide these geographic areas, Therefore, according to the established binary tree, all potential enterprise customers can be appropriately allocated in a relatively fast manner, so that the potential enterprise customers allocated to each marketing resource are geographically different from the location of the marketing resource. There is a considerable degree of proximity relationship, so as to achieve the optimal configuration, which can be beneficial to the execution of the follow-up marketing business, in order to effectively improve the achievement rate of the marketing business.

Before the present invention is described in detail, it should be noted that in the following description, similar elements are designated by the same reference numerals.

Referring to FIG. 1 , a resource allocation system 100 based on binary space partitioning according to an embodiment of the present invention is suitable for being provided by a marketing institution (for example, a banking institution, but not limited thereto) with the same allocation capacity N and located in a predetermined P (P ≥ 2) marketing resources (eg, but not limited to a branch of a banking institution) of geographic scope (eg, but not limited to a city area). The resource allocation system 100 can be implemented as a computer system, and includes, for example, a data server 1 for customer data collection, and a distribution server 2 in communication with the data server 1 . The distribution server 2 includes, for example, a storage module 21 and a processing module 22 electrically connected to the storage module 21 .

Hereinafter, referring to FIG. 1 and FIG. 2 , how the resource allocation system 100 executes a resource allocation procedure for the marketing resources within the predetermined geographic range will be exemplarily explained. The resource configuration program includes the following steps S21 to S27.

In step S21, the data server 1 is configured to collect, for example, from the official database of the Ministry of Economic Affairs, all information about an industry (eg, green energy industry, but not limited to) located within the predetermined geographic area related to a specific marketing project. Customer profiles of potential business customers. In this embodiment, each piece of customer data, for example, indicates the geographic location, capital amount and other relevant information of the corresponding potential enterprise customer. These potential corporate clients are industries related to a specific marketing project (eg, the green energy industry, but not limited thereto).

Afterwards, in step S22, the data server 1 sorts all potential corporate customers according to the capital amount in descending order according to all the collected customer data, and sorts the top M (M≤N×P) top ones in the sorting order. The sorting results of the enterprise customers and the corresponding M pieces of customer data are sent to the distribution server 2 together. More specifically, under the condition that the number of all potential enterprise customers is not greater than N×P, the data server 1 takes the collected customer data of all potential enterprise customers as the M pieces of customer data, and in the data of all potential enterprise customers. In the case where the number is greater than N×P, in order to take into account the allocated capacity N that each marketing resource can support for marketing, the data server 1 will only correspond to the first N×P potential corporate customers (that is, with a relatively large capital amount). The customer information of the potential enterprise customer) is used as the M customer information.

Therefore, when the distribution server 2 receives the arrangement result and the M pieces of customer data from the data server 1, the processing module 22 stores the M pieces of customer data in the storage module 22, and establishes a related The allocation record table 212 of the M potential enterprise customers and the P marketing resources (which is used to record the allocation of all marketing resources), and the allocation record table 212 is stored in the storage module 22 (see FIG. 1 ).

On the other hand, in step S23, the allocation server 2 may obtain resource location data indicating the geographical locations of the P marketing resources and the geographical range of the pre-determined range by means of manual input or external reception by means of P pens. The data and Q (P>Q≥1) pen respectively indicate the object position data of the geographic locations of Q different reference division objects located within a predetermined geographic range. In this embodiment, each reference dividing object may be a railway, a river or a desired geographic dividing line.

Next, in step S24, the processing module 22 of the allocation server 2, according to the obtained P resource location data, the Q object location data and the geographic range data, uses a binary space division method to divide the The predetermined geographic area is divided into P geographic regions, so that each geographic region has only one of the P marketing resources corresponding to one of the marketing resources, and the P pens respectively indicate the geographic region data of the P geographic regions, wherein the The P geographic areas are divided by the Q reference dividing objects.

For example, in the example shown in FIG. 3 , the predetermined geographic range includes, for example, 10 (=P) marketing resources and 9 (=Q) reference division objects (hereinafter, represented by L1 to L9 respectively). In this example, the geographic locations of the marketing resources are represented by A1~A10, and the reference division object L1 is, for example, a railway, the reference division objects L2 and L3 are, for example, a river, and the other reference division objects L4~ L9 is, for example, a desired geographic dividing line. It is worth noting that these geographical dividing lines are not limited to straight lines or horizontal lines, and may also be oblique lines in other aspects. In more detail, the processing module 22 first divides the predetermined geographic area 3 into the left-hand side according to the object position data (hereinafter, denoted by D1 ) corresponding to the reference divided object L1 (railway) and the geographic area data. A sub-range and a second sub-range on the right side. Then, the processing module 22 divides the first sub-range into the lower left part according to the object position data (hereinafter, represented by D2) corresponding to the reference divided object L2 (river), the geographic range data and the object position data D1 The third sub-range and the fourth sub-range on the upper left; and according to the geographic location data (hereinafter, represented by D3), the geographic range data and the object location data D1 corresponding to the reference division object L3 (river), the The second sub-range is divided into a fifth sub-range in the lower right and a sixth sub-range in the upper right. Next, the processing module 22, according to the object position data (hereinafter, denoted by D4) corresponding to the reference division object L4 (for example, a vertical geographical division line equidistant from the geographic positions A2 and A3 in the horizontal direction), the The geographic area data, and the object position data D1, D2 divide the third sub-area into a seventh sub-area on the left and a geographic area 33 on the right, and obtain geographic area data indicating the geographic area 33 (hereinafter, with E3); according to the object position data (hereinafter, denoted by D5) corresponding to the reference division object L5 (for example, a vertical geographical division line equidistant from the geographical location A4, A5 in the horizontal direction), the geographical range data, and the object position data D1, D2, divide the fourth sub-range into a geographic area 34 on the left and a geographic area 35 on the right, and obtain two pieces of geographic area data indicating these geographic areas 34, 35 respectively ( Hereinafter, represented by E4 and E5 respectively); according to the object location data (hereinafter, represented by D6) corresponding to the reference partition object L6 (for example, a vertical geographic partition line equidistant from the geographic locations A6 and A8 in the horizontal direction) ), the geographic area data, and the object position data D1, D3 divide the fifth sub-area into an eighth sub-area on the left and a geographic area 38 on the right, and obtain geographic area data indicating the geographic area 38 (hereinafter, denoted by E8); and according to the object position data (hereinafter, denoted by D7) corresponding to the reference dividing object L7 (for example, a vertical geographic dividing line equidistant from the geographic location A9, A10 in the horizontal direction) ), the geographic area data, and the object position data D1, D3, divide the sixth sub-area into a geographic area 39 on the left and a geographic area 40 on the right, and obtain two geographic areas 39, 40 respectively indicating Geographic area data (hereinafter, represented by E9 and E10 respectively). Finally, the processing module 22, according to the object position data (hereinafter, denoted by D8) corresponding to the reference division object L8 (for example, a horizontal geographical division line equidistant from the geographical position A1, A2 in the longitudinal direction), the The geographic range data, and the geographic location data D2, D4 divide the seventh sub-range into a lower geographic area 31 and an upper geographic area 32, and obtain two geographic records indicating these geographic areas 31, 32 respectively Area data (hereinafter, represented by E1, E2, respectively); and object location data (hereinafter, according to the object location data corresponding to the reference division object L9 (for example, a horizontal geographic division line equidistant from the geographic locations A6, A7 in the longitudinal direction) , represented by D9 ), the geographic range data, and the object position data D1 , D3 , D6 divide the eighth sub-range into a lower geographic area 36 and an upper geographic area 37 , and obtain respectively indicating the Two pieces of geographic area data of equal geographic areas 36 and 37 (hereinafter, represented by E6 and E7 respectively). Therefore, the processing module 22 divides the predetermined geographic area 3 into the geographic areas 31-40 (ie, P=10), and each geographic area 31/.../40 has only one marketing resource.

In the step S25 following the step S24, the processing module 22 of the distribution server 2 uses the binary space division relationship to establish a space with Q items according to the obtained position data of the Q objects and the P geographical area data. The binary trees 211 corresponding to the non-terminal nodes of the Q reference division objects and the P leaf nodes respectively corresponding to the P geographic regions are stored in the storage module 21 . Please note that in this embodiment, each non-terminal node of the binary tree 211 stores object location data indicating the geographic location of the corresponding reference partitioned object, and each leaf node in the binary tree 211 stores an indication The geographic area information of the corresponding geographic area is displayed.

For example, in the case shown in FIG. 3, please refer to FIG. 4, the binary tree 211 established by the processing module 22 has 9 (=Q) non-terminal nodes 411-419 and 10 (=Q) Leaf nodes 421~430. The non-terminal nodes 411-419 store the object location data D1-D9, respectively, and the leaf nodes 421-430 store the geographic area data E1-E10, respectively.

In step S26 following step S22 and step S25 , the allocation record table 212 and the binary tree 211, sequentially allocate each potential enterprise customer to one of the P marketing resources corresponding to one of the marketing resources, so that the number of all potential customers allocated to each marketing resource is different. exceeds the allocated capacity N.

More specifically, in step S26, for each potential enterprise customer, the processing module 22 may first identify the potential enterprise according to the customer data of the potential enterprise customer and the geographic area data stored in the leaf nodes of the binary tree 211. The geographic area where the geographic location of the customer is located, and then, according to the allocation record table 212 , it is confirmed whether the cumulative number of potential enterprise customers to which the marketing resources located in the geographic area have been allocated is less than the allocated capacity N. If the confirmation result is positive, the processing module 22 then takes the marketing resources in the geographic area where the potential enterprise customer is located as the corresponding marketing resource (ie, assigns the potential enterprise customer to the marketing resources in the geographic area where the potential enterprise customer is located). marketing resources), and record the potential enterprise customer newly in the allocation record table 212 stored in the storage module 22 . On the contrary, if the confirmation result is negative (that is, the cumulative number of potential customers to which the marketing resources in the geographic area where the potential enterprise customer is located has already reached the allocated capacity N), in this case, the processing mode will Group 22 will further identify one or more other leaf nodes in the binary tree 211 that have a contiguous relationship (particularly starting from closest in proximity) to a leaf node corresponding to the geographic area in which the potential business customer is located Whether the cumulative number of potential enterprise customers to which the marketing resources in the geographical area corresponding to the candidate leaf node (hereinafter, also referred to as the candidate leaf node) have been allocated is less than the allocation capacity N, until the geographical area corresponding to a candidate leaf node is confirmed for the first time When the cumulative number of marketing resources is less than the allocated capacity N, the marketing resources in the geographic area corresponding to the candidate leaf node are used as the corresponding marketing resources, and the potential enterprise customer is newly added to the storage module 22. The allocation record table 212 is stored.

Taking the geographical areas 31 to 40 divided in FIG. 3 and the binary tree 211 in FIG. 4 as examples (ie, P=9 and Q=10), it is further illustrated that in the case of N=5 and M=50, for a (to be allocated) potential enterprise customer, if the processing module 22 confirms that the geographic location of the potential enterprise customer is located in the geographic area 36, and at the same time confirms that the marketing resources within the geographic area 36 (whose geographic location is A6) have When the cumulative number of allocated potential business customers is, for example, 4 (which is less than 5), in this case, the processing module 22 allocates the potential business customer to the marketing resource in the geographic area 34, and assigns the A potential customer is newly added to the field in the allocation record table 212 corresponding to the marketing resource in the geographic area 34. In other words, the cumulative number of potential enterprise customers to which the marketing resource in the geographic area 36 has been allocated is from 4 is updated to 5 (that is, the allocated capacity has been reached), after which the processing module 22 will not allocate any potential enterprise customers to this marketing resource. Afterwards, for another (to be allocated) potential enterprise customer, if the processing module 2 confirms that the geographic location of the potential enterprise customer is still in the geographic area 36 (its corresponding leaf node 426 in FIG. 4 ), and confirms at the same time When it is found that the cumulative number of potential enterprise customers to which the marketing resources have been allocated in the geographical area 36 has reached 5, in this case, the processing module 22 will first confirm the relationship between the leaf node in the binary tree 211 of FIG. 4 and the 426 Whether the accumulated number of potential enterprise customers in the geographical area 37 corresponding to the nearest candidate leaf node, ie, the leaf node 427 , to which the marketing resources have been allocated is less than five. If unfortunately, the cumulative number of potential enterprise customers to which the marketing resources in the geographic area 37 have been allocated reaches 5, the processing module 22 will further confirm that the binary tree 211 in FIG. 4 is adjacent to the leaf node 426 times The candidate leaf node of , that is, the leaf node 428 in the upper level, whether the cumulative number of potential enterprise customers to which the marketing resources in the corresponding geographic area 38 have been allocated is less than 5. If the cumulative number of potential business customers to which the marketing resource within the geographic area 38 has been allocated is less than 5, the processing module 22 will assign the other potential business customer to the marketing resource within the geographic area 38, and The other potential customer is newly added to a field in the allocation record table 212 corresponding to the marketing resource within the geographic area 38 . Otherwise, the processing module 22 will further confirm the candidate leaf node relatively adjacent to the leaf node 426 in the binary tree 211 of FIG. When the cumulative number of potential enterprise customers to which the marketing resources in the corresponding geographic area 40 have been allocated is less than 5, the processing module 22 allocates the other potential enterprise customer to the marketing resources in the geographic area 40, and assigns the The other potential customer is newly added to a field in the allocation record table 212 corresponding to the marketing resource within the geographic area 40 .

When the allocation of all potential enterprise customers is completed, finally, in step S27, the processing module 22 of the allocation server 2 generates P according to the M pieces of customer data stored in the storage module 21 and the allocation record table 212 are respectively corresponding to the allocation results of the P marketing resources. In this embodiment, each allocation result indicates, for example, a corresponding marketing resource and includes customer data of all potential enterprise customers to which the corresponding marketing resource is allocated. Then, the allocation server 2 sends a corresponding allocation result to a user terminal 200 (see FIG. 1 ) provided by each marketing resource. In this way, each marketing resource can arrange subsequent marketing operations according to the received allocation results.

To sum up, in the resource allocation system 100 of the present invention, since the predetermined geographical range is based on the reference of the traffic facilities, the natural geographical environment, the geographical location of the marketing resources, etc. Therefore, the binary tree 211 established according to the method can perform appropriate allocation processing for all potential enterprise customers in a relatively fast manner, so that for each potential enterprise customer allocated to each marketing resource, Geographically, it has a considerable degree of proximity to the location where the marketing resources are located, so as to achieve the optimal configuration, which is conducive to the execution of the subsequent marketing business, in order to effectively improve the achievement rate of the marketing business. Therefore, the resource allocation system 100 of the present invention can indeed achieve the purpose of the present invention.

However, the above are only examples of the present invention, and should not limit the scope of implementation of the present invention. Any simple equivalent changes and modifications made according to the scope of the patent application of the present invention and the contents of the patent specification are still included in the scope of the present invention. within the scope of the invention patent.

100: Resource allocation system 1: Data server 2: Assign the server 21: Storage Module 211: Binary tree 212: Allocation record sheet 22: Processing modules S21-S27: Steps 3: Predetermined geographic range 31~40: Geographical area L1~L9: Reference to divide objects A1~A10: Geographical location of marketing resources 411~419: non-terminal node 421~430: Leaf node D1~D9: Object location data E1~E10: Geographical area data

Other features and effects of the present invention will be clearly presented in the embodiments with reference to the drawings, wherein: 1 is a block diagram illustrating the architecture of a resource allocation system according to an embodiment of the present invention; FIG. 2 is a flow chart illustrating how the embodiment executes a resource allocation procedure for marketing resources within a predetermined geographic range; 3 is a schematic diagram illustrating how a distribution server of this embodiment divides the predetermined geographic area into ten geographic areas based on binary space partitioning; and FIG. 4 is a schematic diagram illustrating, by way of example, the structure of the binary tree created by the distribution server and corresponding to the ten geographic regions as shown in FIG. 3 .

100: Resource allocation system

1: Data server

2: Assign the server

21: Storage Module

22: Processing modules

Claims (8)

A resource allocation method based on binary space division, suitable for P (P ≥ 2) marketing resources provided by a marketing agency with the same allocation capacity N and located in a predetermined geographic range and executed by a computer system, and Contains the following steps: (A) Obtaining resource location data indicating the geographic locations of the P marketing resources, geographic range data of the predetermined geographic range, and Q pens respectively indicating Q located within the predetermined geographic range (P>Q≥ 1) Object location data with reference to the geographic location of the divided objects; (B) According to the P pieces of resource location data, the Q pieces of object location data and the geographical range data, and using a binary space division method, divide the predetermined geographical range into P geographical areas, so that each geographical area is only Having one of the P marketing resources corresponding to one of the marketing resources, and obtaining P pens respectively indicating the geographic region data of the P geographic regions, wherein the P geographic regions are divided by the Q reference division objects; (C) According to the location data of the Q objects and the data of the P geographic areas, using the binary space division relationship, establish a non-terminal node with Q corresponding to the Q reference divided objects and P corresponding to the P respectively A binary tree of leaf nodes of geographic regions, wherein each non-terminal node stores object location data indicating the geographic location of the corresponding reference divided object, and each leaf node stores geographic region data indicating the corresponding geographic region; (D) collecting M (M≤N×P) pieces of customer information about M potential corporate customers located within the predetermined geographic range, each piece of customer data at least indicating the geographic location of the corresponding potential corporate customer; and (E) According to the M pieces of customer data and the binary tree, assign each potential enterprise customer to one of the P marketing resources, so that the number of all potential customers allocated to each marketing resource is not equal Exceeds the allocation capacity N, wherein for each potential enterprise customer, the marketing resources in the geographic region where the potential enterprise customer is located are used as the corresponding marketing resources, or have a leaf node corresponding to the geographic region where the potential enterprise customer is located. The marketing resource in the geographic area corresponding to another leaf node of the adjacent relationship is used as the corresponding marketing resource. The resource allocation method based on binary space partitioning as described in claim 1, wherein: In step (D), each piece of customer information also indicates the capital amount of the corresponding potential enterprise customer, and the computer system further uses a sorting method related to the capital amount to sort the M potential business customers to obtain a ranking result; and In step (E), the computer system executes an allocation process for each potential enterprise customer according to the sorting result. The resource allocation method based on binary space partitioning according to claim 1 or 2, wherein, in step (E), for each potential enterprise customer: When the computer system confirms that the cumulative number of potential enterprise customers to which the marketing resources in the geographic area where the potential enterprise customer is located is allocated is less than the allocated capacity N, the computer system determines that the potential enterprise customer is located in the geographic area where the potential enterprise customer is located. as the corresponding marketing resource, and update the cumulative quantity corresponding to the corresponding marketing resource; and When the computer system confirms that the cumulative number of potential enterprise customers to which the marketing resources in the geographic area where the potential enterprise customer is located has been allocated has reached the allocated capacity N, the computer system sequentially confirms and corresponds to the potential enterprise customer Whether the cumulative number of potential enterprise customers in the geographic region corresponding to one or more candidate leaf nodes corresponding to the one or more candidate leaf nodes in the geographic region of the geographic region is less than the allocated capacity N, Until it is confirmed for the first time that the cumulative number of marketing resources in the geographic region corresponding to a candidate leaf node is less than the allocated capacity N, the marketing resources in the geographic region corresponding to the candidate leaf node are regarded as the corresponding marketing resources, and The cumulative quantity corresponding to the corresponding marketing resource is updated. The resource allocation method based on binary space segmentation as described in claim 1, further comprising the following steps: (F) To a user terminal provided by each marketing resource, send an assignment result containing customer data of all potential enterprise clients to which the marketing resource is assigned. A resource allocation system based on binary space division, suitable for P (P≥2) marketing resources provided by a marketing agency with the same allocation capacity N and located in a predetermined geographic range, and comprising: A data server, configured to collect M (M≤N×P) pieces of customer data about M potential enterprise customers located in the predetermined geographical area, each customer data at least indicates the corresponding potential business customer geographic location; and a distribution server, connected to the data server to receive the M pieces of customer data, and comprising a storage module and a processing module electrically connected to the storage module, and obtained P pens respectively indicate the P marketing resources The resource location data of the geographical location, the geographical range data of the predetermined geographical range, and the object location data of the Q (P>Q≥1) pen respectively indicating the geographical locations of Q different reference division objects located within the predetermined geographical range ; Wherein, the processing module of the distribution server divides the predetermined geographical range into P pieces according to the obtained P resource location data, the Q object location data and the geographical range data, and uses a binary space division method geographic area, so that each geographic area has only one of the P marketing resources corresponding to one of the marketing resources, and obtains P pens respectively indicating the geographic area data of the P geographic areas, wherein the P geographic areas are determined by the divided by Q reference division objects; Wherein, the processing module of the distribution server uses the binary space division relationship according to the obtained position data of the Q objects and the P geographical area data to create a set of Q objects corresponding to the Q reference division objects respectively. Non-terminal nodes and P binary trees corresponding to the leaf nodes of the P geographic regions respectively, and storing the binary tree in the storage module, each non-terminal node of the binary tree stores a reference division indicating the corresponding Object location data for the geographic location of the object, and each leaf node in the binary tree stores geographic area data indicating the corresponding geographic area; and Wherein, the processing module of the allocation server allocates each potential enterprise customer to the P marketing resources according to the M pieces of customer data received from the data server and the binary tree stored by the storage module. A corresponding marketing resource, so that the number of all potential customers allocated to each marketing resource does not exceed the allocation capacity N, wherein for each potential enterprise customer, the marketing resource in the geographic area where the potential enterprise customer is located is used as the Corresponding marketing resources, or marketing resources in a geographic region corresponding to another leaf node having an adjacent relationship with a leaf node corresponding to the geographic region where the potential enterprise customer is located, are used as the corresponding marketing resources. The resource allocation system based on binary space partitioning according to claim 5, wherein: Each client profile also indicates the capital amount of the corresponding potential corporate client; According to the M pieces of customer data, the data server sorts the M potential corporate customers in a capital-related sorting manner to obtain a sorting result, and transmits the M pieces of customer data together with the sorting result to the allocating servers; and The processing module of the distribution server executes the distribution process of each potential enterprise customer according to the sorting result from the data server. The resource allocation system based on binary space partitioning according to claim 5 or 6, wherein, in the allocation server: The storage module also stores an allocation record table, and the allocation record table records the potential enterprise customers to which each marketing resource has been allocated; For each potential corporate customer, when the processing module confirms that the cumulative number of potential corporate customers recorded by the marketing resources in the geographic area where the potential corporate customer is located in the allocation record table stored by the storage module is less than the allocation When the capacity is N, the processing module takes the marketing resources in the geographic area where the potential enterprise customer is located as the corresponding marketing resource, and records the new location of the potential enterprise customer in the allocation record table stored in the storage module, and When the processing module confirms that in the allocation record table stored by the storage module, the cumulative number of potential corporate customers to whom the marketing resources in the geographic area where the potential corporate customer is located has been allocated has reached the allocation capacity N, the The processing module sequentially confirms that in the allocation record table stored by the storage module, one or more candidate leaf nodes corresponding to a leaf node corresponding to the geographic area where the potential enterprise customer is located are corresponding to one or more candidate leaf nodes starting from the nearest neighbor in degree of proximity Whether the cumulative number of potential enterprise customers recorded by the marketing resources in the geographical area is less than the allocation capacity N, until it is confirmed for the first time that the cumulative number of marketing resources in the geographical area corresponding to a candidate leaf node is less than the allocation capacity N , the marketing resource in the geographic area corresponding to the candidate leaf node is used as the corresponding marketing resource, and the new location of the potential enterprise customer is recorded in the allocation record table stored in the storage module. The resource allocation system based on binary space partitioning according to claim 5, wherein: The processing module of the allocation server generates P allocation results respectively corresponding to the P marketing resources according to the M pieces of customer data and the allocation record table stored in the storage module, and each allocation result indicates the A corresponding marketing resource among the P marketing resources and including customer information of all potential enterprise customers to which the corresponding marketing resource is allocated; and The allocation server sends a corresponding allocation result among the P allocation results to a user terminal provided by each marketing resource.

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