Geographic location information processing method, device, equipment and storage medium

Abstract

The present application provides a method, device, equipment and storage medium for processing geographic location information, which obtains the pre-selected geographic location of the target store and the object information within a preset distance range centered on the pre-selected geographic location, and then processes the object information within the preset distance range to obtain the location influence factor and store efficiency factor when opening the target store at the pre-selected geographic location, and finally determines whether the pre-selected geographic location meets the target store opening requirements based on the attribute information of the target store, the location influence factor and store efficiency factor when opening the target store at the pre-selected geographic location. In this technical solution, it is possible to accurately determine whether the pre-selected geographic location meets the target store opening requirements without the need for specialized personnel to analyze the collected information, which saves labor costs and improves site selection efficiency.

Description

Technical Field

[0001] The present application relates to the field of big data technology, and in particular to a method, device, equipment and storage medium for processing geographic location information. Background Art

[0002] People's daily lives are inseparable from the transaction of goods. Compared with online shopping, customers can get the items they need in the first time through offline shopping, can conveniently check the actual goods on site, and can also ensure the safety of funds to the greatest extent. Therefore, offline shopping is the most indispensable part of people's daily lives.

[0003] At present, in order to ensure that the stores where users shop can operate normally and provide convenient services to the society, it is generally necessary to collect a large amount of information related to the pre-selected address when selecting a site, and manually evaluate the expected benefits of the store, so as to determine whether the pre-selected address meets the needs of the store.

[0004] In the process of realizing the present invention, the inventors found that there are at least the following problems in the prior art: the above method requires specialized personnel to conduct a large amount of investigation on various information near the address, which is time-consuming and labor-intensive, with high labor costs, and there is no scientific basis for comprehensive and detailed analysis from all aspects, and it is impossible to efficiently and quickly judge whether the store location is reasonable, resulting in low store location efficiency. Summary of the invention

[0005] The present application provides a method, device, equipment and storage medium for processing geographic location information, which are used to solve the problems of high labor cost and low efficiency in the existing store site selection process.

[0006] In a first aspect, an embodiment of the present application provides a method for processing geographic location information, including:

[0007] Obtaining a pre-selected geographic location of a target store and information about objects within a preset distance range centered on the pre-selected geographic location;

[0008] Processing the object information within the preset distance range to obtain a location influence factor and a store efficiency factor when opening the target store at the preselected geographical location;

[0009] It is determined whether the preselected geographical location meets the target store opening requirements based on the attribute information of the target store, the location influence factor when opening the target store in the preselected geographical location, and the store efficiency factor.

[0010] In a possible design of the first aspect, determining whether the preselected geographical location meets the target store opening requirements according to the attribute information of the target store, the location influence factor when opening the target store in the preselected geographical location, and the store efficiency factor includes:

[0011] According to the attribute information of the target store, obtaining the flow of people, the area and the cost of the target store in a preset time period;

[0012] Determine the transaction information of the target store in the preset time period according to the location influence factor, the store efficiency factor, the preset per capita consumption information and the traffic information volume;

[0013] Determine location benefit information of the target store in the preset time period according to the transaction information and the target store area;

[0014] Determining the revenue information of the target store in the preset period according to the transaction information and the cost of the target store;

[0015] According to the location benefit information and the revenue information of the target store in the preset time period, it is determined whether the pre-selected geographical location meets the requirements for opening a target store.

[0016] In the above possible design of the first aspect, the transaction information of the target store in the preset time period is obtained by the following formula:

[0017] S=a1*a2*b*c

[0018] Among them, S is the transaction information of the target store in the preset time period and the transaction value of the preset time period, a1 represents the location influence factor, a2 represents the store efficiency factor, b represents the preset per capita consumption information, and c represents the target user flow information.

[0019] In another possible design of the first aspect, the object information includes: population information and community information;

[0020] Determining the location influence factor of the target store according to the object information within a preset distance range centered on the preselected geographical location includes:

[0021] Processing the object information within the preset distance range to obtain a location influence factor when opening the target store at the preselected geographical location includes:

[0022] Determine the average location cost of the cell within the preset distance range and the population information and cell information of the target area within the preset distance range according to the population information and cell information within the preset distance range;

[0023] Determine the average cell location cost of the target area according to the population information and cell information of the target area;

[0024] The location impact factor of the target store is determined according to the average location cost of the cell within the preset distance range and the average location cost of the cell in the target area.

[0025] Optionally, the average cell location cost of the target area is obtained by the following formula:

[0026]

[0027] Wherein, k1 is the mean value of the cell locations in the target area, A i is the location cost of the ith cell in the target area, B i The number of households in the i-th cell in the target area, n is the number of cells in the target area, and n is an integer greater than or equal to 1;

[0028] The average cell location cost k2 within the preset distance range is obtained by the following formula:

[0029]

[0030] Wherein, k2 is the average value of the cell locations within the preset distance range, A i is the location cost of the ith cell within the preset distance range, B i The number of households in the ith cell within the preset distance range, where m is the number of cells within the preset distance range;

[0031] Both m and n are integers greater than or equal to 1, and m is greater than or equal to n;

[0032] The location influence factor of the target store is obtained by the following formula:

[0033] a1=k2 / k1

[0034] Wherein, a1 is the location impact factor, k1 is the average location cost of the cells in the target area, and k2 is the average location cost of the cells within the preset distance range.

[0035] In another possible design of the first aspect, the object information includes: information about competitors of the target store;

[0036] Processing the object information within the preset distance range to obtain a store efficiency factor when opening the target store at the preselected geographical location includes:

[0037] Determine at least one competitor type of the target store and the quantity of each competitor type according to competitor information of the target store within the preset distance range;

[0038] The store performance factor of the target store is determined according to at least one competitor type of the target store, the quantity of each competitor type, and a preset competition coefficient of each competitor type.

[0039] Optionally, the store efficiency factor is obtained by the following formula:

[0040]

[0041] Wherein, a2 is the store efficiency factor, and x l is the number of the lth competitor type, the y l is the competition coefficient of the l-th competitor type, h is the number of types of the l-th competitor, and h is an integer greater than or equal to 1.

[0042] In a second aspect, the present application provides a device for processing geographic location information, including: an acquisition module and a processing module;

[0043] The acquisition module is used to acquire a pre-selected geographical location of a target store and information about objects within a preset distance range centered on the pre-selected geographical location;

[0044] The processing module is used to process the object information within the preset distance range to obtain the location influence factor and the store efficiency factor when opening the target store in the preselected geographical location, and determine whether the preselected geographical location meets the target store opening requirements based on the attribute information of the target store, the location influence factor and the store efficiency factor when opening the target store in the preselected geographical location.

[0045] In a possible design of the second aspect, the processing module is used to determine whether the preselected geographical location meets the target store opening requirements based on the attribute information of the target store, the location influence factor when opening the target store in the preselected geographical location, and the store efficiency factor, specifically:

[0046] The processing module is specifically used for:

[0047] According to the attribute information of the target store, obtaining the flow of people, the area and the cost of the target store in a preset time period;

[0048] Determine the transaction information of the target store in the preset time period according to the location influence factor, the store efficiency factor, the preset per capita consumption information and the traffic information;

[0049] Determine location benefit information of the target store in the preset time period according to the transaction information and the target store area;

[0050] Determining the revenue information of the target store in the preset period according to the transaction information and the cost of the target store;

[0051] According to the location benefit information and the revenue information of the target store in the preset time period, it is determined whether the pre-selected geographical location meets the requirements for opening a target store.

[0052] Optionally, the transaction information of the target store in the preset time period is obtained by the following formula:

[0053] S=a1*a2*b*c

[0054] Among them, S is the transaction information of the target store in the preset time period, a1 represents the location influence factor, a2 represents the store efficiency factor, b represents the preset per capita consumption information, and c represents the flow of people information.

[0055] In another possible design of the second aspect, the object information includes: population information and cell information;

[0056] The processing module is used to process the object information within the preset distance range to obtain the location influence factor when opening the target store at the preselected geographical location, specifically:

[0057] The processing module is specifically used for:

[0058] Determine the average location cost of the cell within the preset distance range and the population information and cell information of the target area within the preset distance range according to the population information and cell information within the preset distance range;

[0059] Determine the average cell location cost of the target area according to the population information and cell information of the target area;

[0060] The location impact factor of the target store is determined according to the average location cost of the cell within the preset distance range and the average location cost of the cell in the target area.

[0061] Optionally, the average cell location cost of the target area is obtained by the following formula:

[0062]

[0063] Wherein, k1 is the mean value of the cell locations in the target area, A iis the location cost of the ith cell in the target area, B i The number of households in the i-th cell in the target area, n is the number of cells in the target area, and n is an integer greater than or equal to 1;

[0064] The average cell location cost k2 within the preset distance range is obtained by the following formula:

[0065]

[0066] Wherein, k2 is the average value of the cell locations within the preset distance range, A i is the location cost of the ith cell within the preset distance range, B i The number of households in the ith cell within the preset distance range, where m is the number of cells within the preset distance range;

[0067] Both m and n are integers greater than or equal to 1, and m is greater than or equal to n;

[0068] The location influence factor of the target store is obtained by the following formula:

[0069] a1=k2 / k1

[0070] Wherein, a1 is the location impact factor, k1 is the average location cost of the cells in the target area, and k2 is the average location cost of the cells within the preset distance range.

[0071] In another possible design of the second aspect, the object information includes: information about competitors of the target store;

[0072] The processing module is used to process the object information within the preset distance range to obtain the store efficiency factor when opening the target store at the preselected geographical location, specifically:

[0073] The processing module is specifically used for:

[0074] Determine at least one competitor type of the target store and the quantity of each competitor type according to competitor information of the target store within the preset distance range;

[0075] The store performance factor of the target store is determined according to at least one competitor type of the target store, the quantity of each competitor type, and a preset competition coefficient of each competitor type.

[0076] Optionally, the store efficiency factor is obtained by the following formula:

[0077]

[0078] Wherein, a2 is the store efficiency factor, and x l is the number of the lth competitor type, the y l is the competition coefficient of the lth competitor type, h is the number of the lth competitor type, and h is an integer greater than or equal to 1.

[0079] In a third aspect, the present application provides an electronic device, including: a processor, a memory, a display, and a system bus;

[0080] The memory stores computer-executable instructions;

[0081] When the processor executes the computer program instructions, the method provided in the first aspect and various possible designs is implemented.

[0082] In a fourth aspect, the present application provides a computer-readable storage medium, in which computer program instructions are stored. When the computer program instructions are executed by a processor, they are used to implement the methods provided in the first aspect and various possible designs.

[0083] The method, device, equipment and storage medium for processing geographic location information provided in the embodiments of the present application obtain the pre-selected geographic location of the target store and the object information within a preset distance range centered on the pre-selected geographic location, process the object information within the preset distance range, obtain the location influence factor and store efficiency factor when opening the target store at the pre-selected geographic location, and finally determine whether the pre-selected geographic location meets the target store opening requirements based on the attribute information of the target store, the location influence factor and store efficiency factor when opening the target store at the pre-selected geographic location. In this technical solution, it is possible to accurately determine whether the target store opening requirements are met when the pre-selected geographic location is opened without the need for specialized personnel to analyze the collected information, which saves labor costs and improves site selection efficiency. BRIEF DESCRIPTION OF THE DRAWINGS

[0084] Figure 1 A schematic diagram of an application scenario of the method for processing geographic location information provided in an embodiment of the present application;

[0085] Figure 2 A flowchart of a first embodiment of a method for processing geographic location information provided in an embodiment of the present application;

[0086] Figure 3 A schematic diagram of monitoring data provided in an embodiment of the present application;

[0087] Figure 4A A flowchart of a second embodiment of a method for processing geographic location information provided in an embodiment of the present application;

[0088] Figure 4BA schematic diagram of the evaluation of a pre-selected geographical location provided in an embodiment of the present application;

[0089] Figure 5 A schematic diagram of interpreting the terminology of the evaluation and judgment rules for preselected geographic locations provided in an embodiment of the present application;

[0090] Figure 6 A flowchart of a third embodiment of a method for processing geographic location information provided in an embodiment of the present application;

[0091] Figure 7 A flowchart of a fourth embodiment of a method for processing geographic location information provided in an embodiment of the present application;

[0092] Figure 8 A schematic diagram of the structure of a device for processing geographic location information provided in an embodiment of the present application;

[0093] Fig. 9 A schematic diagram of the structure of an electronic device provided in an embodiment of the present application. DETAILED DESCRIPTION

[0094] In order to make the purpose, technical solution and advantages of the embodiments of the present application clearer, the technical solution in the embodiments of the present application will be clearly and completely described below in conjunction with the drawings in the embodiments of the present application. Obviously, the described embodiments are part of the embodiments of the present application, not all of the embodiments. Based on the embodiments in the present application, all other embodiments obtained by ordinary technicians in this field without creative work are within the scope of protection of this application.

[0095] Figure 1 Schematic diagram of an application scenario of the method for processing geographic location information provided in an embodiment of the present application. Figure 1 As shown, the application scenario is explained by the geographic location information of the target store displayed on the interactive interface of the terminal device 11.

[0096] For the processing scenario of the geographic location information of the target store in the actual application, the target store type, pre-selected geographic location, and preset distance range are set on the initial interface of the terminal device 11. For example, "target store type": indicates the type of the pre-selected target store, such as a fresh food store, a supermarket, a clothing store, etc.; "pre-selected geographic location": select from the map of the terminal device 11, and automatically generate detailed information of the target address; "pre-set distance range": preset reference range around the target store, within which stores that have been opened and are in competition with the preset target store are displayed in real time.

[0097] For example, this application explains the site selection of a fresh food store, and the preset distance range is within a radius of 0.5 km as a reference. The terminal device 11 displays: within the preset distance range of 0.5 km radius, there are 1 fruit and vegetable good, 1 Xinfadi and 1 fresh food store. After the user confirms the preset site selection for the above fresh food store, he can select "Next" to perform specific configuration, which is described in detail in the following embodiments.

[0098] Understandably, Figure 1 The "target store type", "pre-selected geographic location", "pre-set distance range", "next step", etc. presented in the window can be set according to actual conditions. They are only used as examples here and do not limit the displayed content.

[0099] In this embodiment, the user selects a location for a pre-opened target store through a terminal device, and generates detailed information on whether the pre-selected geographical location meets the needs of the target store, thereby providing support for determining whether the target store in the pre-selected geographical location meets the needs of the target store, allowing the user to save time and energy spent on analyzing relevant information about the target store in the pre-selected geographical location.

[0100] The embodiments of the present application are aimed at the problem that site selection in the prior art is time-consuming, labor-intensive and inefficient. The technical conception process of the inventor is as follows: the inventor finds that by presetting information related to the target store, selecting the preset target store type and address on the terminal device, and configuring relevant parameters, it is possible to determine whether the pre-selected geographical location meets the requirements for opening the target store based on the relevant parameters.

[0101] Based on the above technical concept, the present application provides a method for processing geographic location information, by obtaining the pre-selected geographic location of the target store, the object information within a preset distance range centered on the pre-selected geographic location, and then processing the object information within the preset distance range, to obtain the location influence factor and store efficiency factor when opening the target store at the pre-selected geographic location, and finally determine whether the pre-selected geographic location meets the target store opening requirements based on the attribute information of the target store, the location influence factor and store efficiency factor when opening the target store at the pre-selected geographic location. This technical solution does not require specialized personnel to analyze the collected information, and can accurately determine whether the pre-selected geographic location meets the requirements for opening the target store, which saves labor costs and improves site selection efficiency.

[0102] Below Figure 1 The application scenarios shown in the figure describe the technical solutions of the present application in detail through specific embodiments. It should be noted that the following specific embodiments can be combined with each other, and the same or similar concepts or processes may not be repeated in some embodiments. The embodiments of the present application will be described below in conjunction with the accompanying drawings.

[0103] Figure 2This is a flow chart of Embodiment 1 of the method for processing geographic location information provided in the present application. Figure 2 As shown, the method for processing geographic location information provided in the embodiment of the present application may include the following steps:

[0104] Step 21: Obtain a pre-selected geographic location of the target store and information about objects within a preset distance range centered on the pre-selected geographic location.

[0105] In this embodiment, the description is made after the type of the target store to be opened is selected as a fresh food store, and the pre-selected geographical location of the target store is selected. At this time, the information around the pre-selected geographical location needs to be configured.

[0106] Optionally, the object information within a preset distance range centered on a preselected geographic location includes the number of target users in a preset time period, and the number of target users is determined by the flow of people information centered on the preselected geographic location. The flow of people information here can be obtained through manual monitoring and input into the terminal device; it can also be measured by a detection device and obtained by the terminal device from the detection device. There is no limitation here.

[0107] Specifically, the traffic information is as follows: Figure 3 As shown, Figure 3 The monitoring data schematic diagram provided for the embodiment of the present application includes the detection date "XXXX-XX month", the detection flow rate (peak), the detection duration (peak) and the detection duration (flat peak), and the detection flow rate (flat peak). Correspondingly, according to the flow rate information, the target number of users in the preset time period can be determined. The embodiment of the present application takes a preset time period of one month as an example, and determines that the target number of users is 200,000 people.

[0108] Step 22: Process the object information within the preset distance range to obtain the location influence factor and store efficiency factor when opening a target store in the pre-selected geographical location.

[0109] In this embodiment, the opening of a fresh food store needs to consider the information of the communities, residents and related target stores within a certain range centered on the preselected geographical location. That is, since the scope of influence of a fresh food store has certain geographical restrictions, the 0.5km radius range centered on the preselected geographical location is taken as an example for explanation here. By determining the information of the communities, residents and related target stores within the preset distance range, and then processing the information of the communities, residents and related stores within the preset distance range, the location influence factor and store efficiency factor when opening the target store in the preselected geographical location are determined.

[0110] Step 23: Determine whether the pre-selected geographical location meets the target store opening requirements based on the target store's attribute information, the location influence factor when opening the target store in the pre-selected geographical location, and the store efficiency factor.

[0111] For example, the attribute information of the target store includes the target store rent and the target store area. The attribute information can be determined by calling relevant data recorded in a network database or obtained through field investigation, which is not limited here.

[0112] Optionally, the attribute information of the fresh food store is that the rent of the target store is 200,000 yuan / month, the area of ​​the target store is 200 square meters, the location influence factor is the influence of the residents and community prices within a radius of 0.5 km on the target store, and the store efficiency factor is the influence of other competing stores within a radius of 0.5 km on the target store. Further, based on the attribute information of the target store, the location influence factor, and the store efficiency factor, a comprehensive evaluation is performed to determine whether the pre-selected geographical location meets the requirements for opening the target store. The specific evaluation process is given in the following embodiment and will not be repeated here.

[0113] The method for processing geographic location information provided in the embodiment of the present application obtains the pre-selected geographic location of the target store and the object information within a preset distance range centered on the pre-selected geographic location, and then processes the object information within the preset distance range to obtain the location influence factor and store efficiency factor when opening the target store at the pre-selected geographic location. Finally, according to the attribute information of the target store, the location influence factor and store efficiency factor when opening the target store at the pre-selected geographic location, it is determined whether the pre-selected geographic location meets the target store opening requirements. In this technical solution, it is possible to accurately determine whether the pre-selected geographic location meets the target store opening requirements without the need for specialized personnel to analyze the collected information, which saves labor costs and improves site selection efficiency.

[0114] Based on the above embodiments, Figure 4A This is a flowchart of Embodiment 2 of the method for processing geographic location information provided in the embodiment of the present application. Figure 4B This is a schematic diagram of the evaluation of the pre-selected geographical location provided in the embodiment of the present application. Figure 4B The evaluation diagram shown in FIG. 1 illustrates the above step 23. Optionally, refer to Figure 4B As shown, the evaluation diagram includes XX Street, XX District, XX City, evaluation results, the number of target users within 0.5km, the number of target users within 1km, location benefit information of target stores, revenue information of target stores, 0.5km community population information, information of competitors, transaction value of preset time period and evaluation results.

[0115] In this embodiment, if Figure 4AAs shown, the above step 23 may include the following steps:

[0116] Step 41: According to the attribute information of the target store, obtain the traffic information volume, target store area and target store cost of the target store in a preset time period.

[0117] Optionally, the preset period can be determined according to actual conditions. For example, the preset period is one month.

[0118] Optionally, the attribute information of the target store includes the number of target users of the target store, the area of ​​the target store and the cost of the target store, etc. Therefore, when the attribute information of the target store is obtained, the number of target users of the target store, the area of ​​the target store and the cost of the target store in a preset time period can be determined.

[0119] For example, refer to Figure 2 From the introduction of the target store attribute information in the illustrated embodiment, it can be seen that the target number of users is 200,000, the target store rent is 200,000 / month, and the target store area is 200 square meters. The specific determination method will not be repeated here.

[0120] Step 42: Determine the transaction information of the target store in a preset time period based on the location influence factor, the store efficiency factor, the preset per capita consumption information and the amount of traffic information.

[0121] Optionally, the location influence factor is the influence of community residents and community housing prices within a 0.5km radius of the target store, that is, the community factor value of the store within a 0.5km radius; the effectiveness factor is the influence of other stores that may be in competition with the target store within a 0.5km radius, that is, the market share of the store within a 0.5km radius; the preset per capita consumption information is determined according to the market fresh food consumption level, and the per capita consumption amount ranges from 40 to 60 yuan. The calculation methods of the above location influence factors and store effectiveness factors are given in the following embodiments and will not be repeated here.

[0122] Specifically, the transaction information of the fresh food store within a month, that is, the transaction value, is obtained by the following formula:

[0123] S=a1*a2*b*c

[0124] Among them, a1 is the location influence factor, a2 is the store efficiency factor, b is the average consumption amount per person, and c is the number of target users.

[0125] For example, when a1=1.33, a2=60%, b=50 yuan, and c=200,000 people / month, the transaction value of the fresh food store in one month is S=a1*a2*b*c=1.33*60%*50*200,000=8,000,000 yuan.

[0126] Step 43: Determine the location benefit information of the target store in a preset time period based on the transaction information and the target store area.

[0127] Optionally, the transaction value of the target store within one month is determined above, and the benefit generated per square meter of the target store is determined according to the ratio of the transaction value to the area of ​​the target store, that is, the location benefit information of the target store.

[0128] Specifically, the location benefit information of the target store within one month is obtained by the following formula:

[0129]

[0130] Among them, i is the location benefit information, S is the transaction value of the target store, and v is the area of ​​the target store.

[0131] For example, when i=40000, S=8000000, and v=200 square meters,

[0132] Step 44: Determine the revenue information of the target store in a preset period based on the transaction information and the target store cost.

[0133] Optionally, based on the ratio of the transaction value to the cost of the fresh food store, the ratio of the rent of the target store in one month to the transaction value, that is, the revenue information of the target store, is determined.

[0134] Specifically, the target store's revenue information within a month is obtained through the following formula:

[0135]

[0136] Among them, j is the revenue information, S is the transaction value of the target store, and w is the rent of the target store.

[0137] For example, when j = 4%, S = 8,000,000 yuan, and w = 200,000 yuan, the income information

[0138] Step 45: Determine whether the pre-selected geographical location meets the requirements for opening a target store based on the location benefit information and revenue information of the target store in a preset time period.

[0139] Optionally, after determining the location benefit information and the target store's revenue information, it is possible to comprehensively evaluate whether the pre-selected geographical location meets the target store opening requirements. Exemplarily, whether the pre-selected geographical location meets the target store opening requirements can be given by the evaluation result, which is displayed in the form of lights, with three lights indicating that it is recommended to open a store, one light indicating that it is not recommended to open a store, and two lights indicating that it is possible to consider opening a store.

[0140] Optional, Figure 4B It also includes: city analysis, surrounding analysis, crowd analysis and other information. Figure 4B An information summary of the city profile is given as an example, for example, the city where the pre-selected geographical location is located is XX city, which is a second-tier city.

[0141] Exemplarily, for user reference and to facilitate the user to view the assessment report at any time, the user can export the assessment report information by selecting the option of "exporting pre-selected geographic location information assessment information".

[0142] Specifically, Figure 5 Diagram showing the interpretation of decision rule terms for pre-selected geographic locations. Figure 5 As shown, the term interpretation diagram includes: judgment rules, lighting rules, total population, number of target users, location benefits of target stores and revenue information of target stores, etc.

[0143] Optionally, factors that affect the "judgment rule" include "total population, number of target users, location benefits of the store, and revenue information of the store". The specific rule may be a "lighting rule", which is "if there is one or more red lights, one light will be on the geographic location information evaluation diagram; if there is no red light and one or more yellow lights, two lights will be on the geographic location information evaluation diagram; if all lights are green, three lights will be on the geographic location information evaluation diagram". This is just an example and does not limit the judgment rules in actual application.

[0144] Optional, in Figure 5 Among them, the lighting rules for "location benefit information of target store" (feasibility of opening a store) are "red light: location benefit information is below 45,000, yellow light: location benefit information is between 45,000 and 50,000, green light: location benefit information is above 50,000", and the lighting rules for "profit information of target store" (feasibility of opening a store) are "red light: profit information is above 8%, yellow light: profit information is between 6% and 8%, green light: profit information is below 6%".

[0145] Optional, such as Figure 4B As shown, the "Evaluation Result" is displayed as a light, which means that it is not recommended to open a store. Specifically, although the revenue information of the target store is green, the location benefit is red. The reason for not recommending opening a store may be that, compared with the location benefit of 40,000 yuan / square meter per month, excluding labor costs, commodity costs, property costs, decoration costs, etc., the actual benefits obtained by the target store are not very large. Therefore, this location is not recommended as the best location for a fresh food store.

[0146] Through the above Figure 4B and Figure 5 The schematic diagram shown allows the user to intuitively understand the information related to the pre-selected geographical location and suggestions on whether it meets the needs of opening a store.

[0147] The method for processing geographic location information provided in this embodiment obtains the target store's traffic information, target store area, and target store cost in a preset time period based on the target store's attribute information, and then determines the target store's transaction information in the preset time period based on the location influencing factor, store efficiency factor, preset per capita consumption information, and traffic information. Then, based on the transaction information and the target store area, the target store's location benefit information in the preset time period is determined. Based on the transaction information and the target store's cost, the target store's revenue information in the preset time period is determined. Finally, based on the target store's location benefit information and revenue information in the preset time period, it is determined whether the pre-selected geographic location meets the target store opening requirements. In this technical solution, an accurate assessment is made of whether the pre-selected geographic location meets the target store opening requirements based on the target store's transaction value, location benefit information, and revenue information.

[0148] Figure 6 Flow chart of the third embodiment of the method for processing geographic location information provided in the embodiment of the present application. When the object information includes: population information, community information, refer to Figure 6 As shown, the above step 22 of processing the object information within the preset distance range to obtain the location influence factor when opening a target store at the preselected geographical location may include the following steps:

[0149] Step 61: Determine the average location cost of the cells within the preset distance range and the population information and cell information of the target area within the preset distance range according to the population information and cell information within the preset distance range.

[0150] Exemplarily, the population information and community information within the preset distance range are the population information and community information within a 0.5km radius of the target store. Based on the population information and community information within a 0.5km radius, the location cost and the number of households in all communities within the 0.5km radius can be obtained.

[0151] The target area within the preset distance range refers to a community with the most commercial districts within the preset distance range.

[0152] Optionally, the average location cost of all cells within the preset distance range may be determined according to the following formula and the location costs of all cells within the preset distance range and the number of households in the cells.

[0153] That is, the average location cost of all cells within the preset distance range is obtained by the following formula:

[0154]

[0155] Among them, k2 is the average value of the cell location within the preset distance range, A iis the location cost of the ith cell within the preset distance range, B i is the number of households in the ith cell within the preset distance range, and m is the number of cells within the preset distance range.

[0156] For example, assume that there are 4 cells within a radius of 0.5 km, and the location costs of the 4 cells are: A1 is 20,000, A2 is 15,000, A3 is 10,000, and A4 is 35,000. The number of households in the 4 cells is: B1 is 1,000 households, B2 is 1,000 households, B3 is 1,000 households, and B4 is 1,000 households.

[0157] Specifically, based on the location cost and number of households in the four communities within a radius of 0.5 km, we can calculate the average location cost k2 of the four communities to be (10,000):

[0158]

[0159] Step 62: Determine the average cell location cost of the target area based on the population information and cell information of the target area.

[0160] Exemplarily, the population information and community information of the target area refer to the location cost and the number of households in the community with the most communities within a preset distance range, for example, the location cost and the number of households in the community with the most communities within a radius of 0.5 km, that is, the average price and the number of households in the community of the target area.

[0161] Optionally, according to the following formula and the location cost of the target area and the number of households in the community, the average location cost of the community of the target area within the preset distance range can be calculated.

[0162] That is, the mean cell location cost of the target area is obtained by the following formula:

[0163]

[0164] Among them, k1 is the average location cost of the cell in the target area, A i is the location cost of the i-th cell in the target area, B i is the number of households in the ith cell of the target area, and n is the number of cells in the target area.

[0165] Optionally, A1, A2, and A3 are location costs of three communities within the target area, and B1, B2, and B3 are the numbers of households in the three communities within the target area.

[0166] Specifically, the average location cost of three cells within a 0.5km radius is (ten thousand):

[0167]

[0168] Exemplarily, the number of cells within the preset distance range may be m, and the number of cells in the target area may be n, where m is an integer greater than or equal to n, and the minimum value of n is 1.

[0169] Step 63: Determine the location impact factor of the target store according to the average location cost of the cell within the preset distance range and the average location cost of the cell in the target area.

[0170] Exemplarily, according to the above steps, the average cell location cost within the preset distance range and the average cell location cost of the target area have been determined. Further, the location influence factor of the target store is determined based on the ratio of the average cell location cost within the preset distance range to the average cell location cost of the target area.

[0171] Optionally, the location influence factor of the target store is obtained by the following formula:

[0172]

[0173] Among them, a1 is the location impact factor, k1 is the average cell location cost of the target area, and k2 is the average cell location cost within the preset distance range.

[0174] It is worth noting that the calculation result of the location influence factor of the target store is a maximum of 1.5, and if it exceeds 1.5, it is calculated as 1.5, and the minimum is 0.5, and if it is lower than 0.5, it is calculated as 0.5. Therefore, the location influence factor of the target store takes a value between 0.5 and 1.5 according to the calculation result.

[0175] The method for processing geographic location information provided in the embodiment of the present application is based on the object information within a preset distance range centered on the pre-selected geographic location, and determines the average cell location cost within the preset distance range and the population information and cell information of the target area within the preset distance range according to the population information and cell information of the target area within the preset distance range, and then determines the average cell location cost of the target area according to the population information and cell information of the target area within the preset distance range, and finally determines the location impact factor of the target store according to the average cell location cost within the preset distance range and the average cell location cost of the target area. In this technical solution, the location impact factor provides a basis for determining the transaction value of the preset target store.

[0176] Figure 7 Flow chart of the fourth embodiment of the method for processing geographic location information provided in the embodiment of the present application. Optionally, the object information includes: information about the target store's competitors, see Figure 7 As shown, processing the object information within a preset distance range to obtain the store efficiency factor when opening a target store at a preselected geographical location may include the following steps:

[0177] Step 71: Determine at least one competitor type of the target store and the quantity of each competitor type based on competitor information of the target store within a preset distance range.

[0178] Exemplarily, based on population information, community information and competitor information within a 0.5km radius of the target address, it is determined that competitors in the area include 1 Fruit and Vegetable Good, 1 Xinfadi and 1 fresh food store.

[0179] Step 72: Determine the store performance factor of the target store based on at least one competitor type of the target store, the number of each competitor type, and a preset competition coefficient of each competitor type.

[0180] Exemplarily, the competition coefficient is related to the type of the competition object and is a value preset according to a survey.

[0181] Optionally, the store effectiveness factor is obtained by the following formula:

[0182]

[0183] Among them, a2 is the store efficiency factor, x l is the number of the lth competitor type, y l is the competition coefficient of the lth competitor type, h is the number of the lth competitor type, and h is an integer greater than or equal to 1.

[0184] For example, when the store efficiency factor is 60%, the competition coefficient of a fresh food store that has been opened is 100%, the competition coefficient of a fruit and vegetable store is 50%, and the competition coefficient of a Xinfadi store is 16.67%, the store efficiency factor within a radius of 0.5 km is obtained by the following formula:

[0185]

[0186] It is worth noting that the value of the store efficiency factor is between 0% and 100%.

[0187] The method for processing geographic location information provided in the embodiment of the present application determines at least one competitor type and the number of each competitor type of the target store based on the competitor information of the target store within a preset distance range; determines the store efficiency factor of the target store based on at least one competitor type and the number of each competitor type of the target store and the preset competition coefficient of each competitor type. In this technical solution, the store efficiency factor provides a basis for determining the transaction value of the preset target store.

[0188] Figure 8 This is a schematic diagram of the structure of a device for processing geographic location information provided in an embodiment of the present application. Figure 8As shown, the device includes an acquisition module 81 and a processing module 82.

[0189] The acquisition module 81 is used to acquire the pre-selected geographical location of the target store and the object information within a preset distance range centered on the pre-selected geographical location.

[0190] The processing module 82 is used to process the object information within a preset distance range to obtain the location influence factor and the store efficiency factor when opening a target store in the preselected geographical location, and determine whether the preselected geographical location meets the target store opening requirements based on the attribute information of the target store, the location influence factor and the store efficiency factor when opening the target store in the preselected geographical location.

[0191] In a possible design of the embodiment of the present application, the processing module 82 is used to determine whether the pre-selected geographical location meets the target store opening requirements according to the attribute information of the target store, the location influence factor and the store efficiency factor when opening the target store in the pre-selected geographical location, specifically:

[0192] The processing module 82 is specifically used for:

[0193] According to the attribute information of the target store, obtain the traffic information volume, target store area and target store cost of the target store in the preset time period;

[0194] Determine the transaction information of the target store in the preset time period based on the location influence factor, store efficiency factor, preset per capita consumption information and traffic information;

[0195] Determine the location benefit information of the target store during the preset time period based on the transaction information and the target store area;

[0196] Determine the target store's revenue information in a preset period based on transaction information and target store costs;

[0197] Based on the location benefit information and revenue information of the target store in the preset time period, determine whether the pre-selected geographical location meets the requirements for opening the target store.

[0198] Optionally, the transaction information of the target store in the preset period is obtained by the following formula:

[0199] S=a1*a2*b*c

[0200] Among them, S is the transaction information of the target store in the preset time period, a1 represents the location influence factor, a2 represents the store efficiency factor, b represents the preset per capita consumption information, and c represents the flow of people information.

[0201] In another possible design of the embodiment of the present application, the object information includes: population information, cell information;

[0202] The processing module 82 is used to process the object information within the preset distance range to obtain the location influence factor when opening a target store in the pre-selected geographical location, specifically:

[0203] The processing module 82 is specifically used for:

[0204] Determine the average location cost of the cell within the preset distance range and the population information and cell information of the target area within the preset distance range according to the population information and cell information within the preset distance range;

[0205] Determine the average location cost of the cells in the target area based on the population information and cell information of the target area;

[0206] The location impact factor of the target store is determined based on the average location cost of the cell within the preset distance range and the average location cost of the cell in the target area.

[0207] Optionally, the mean cell location cost of the target area is obtained by the following formula:

[0208]

[0209] Among them, k1 is the mean cell location of the target area, A i is the location cost of the ith cell in the target area, B i The number of households in the ith cell in the target area, n is the number of cells in the target area, and n is an integer greater than or equal to 1;

[0210] The average cell location cost k2 within the preset distance range is obtained by the following formula:

[0211]

[0212] Among them, k2 is the average value of the cell location within the preset distance range, A i is the location cost of the ith cell within the preset distance range, B i The number of households in the ith cell within the preset distance range, where m is the number of cells within the preset distance range;

[0213] m and n are both integers greater than or equal to 1, and m is greater than or equal to n;

[0214] The location influence factor of the target store is obtained by the following formula:

[0215] a1=k2 / k1

[0216] Among them, a1 is the location impact factor, k1 is the average cell location cost of the target area, and k2 is the average cell location cost within the preset distance range.

[0217] In another possible design of the embodiment of the present application, the object information includes: information about competitors of the target store;

[0218] The processing module 82 is used to process the object information within the preset distance range to obtain the store efficiency factor when opening a target store in the pre-selected geographical location, specifically:

[0219] The processing module 82 is specifically used for:

[0220] Determine at least one competitor type of the target store and the quantity of each competitor type according to competitor information of the target store within a preset distance range;

[0221] The store performance factor of the target store is determined according to at least one competitor type of the target store, the quantity of each competitor type, and a preset competition coefficient of each competitor type.

[0222] Optionally, the store effectiveness factor is obtained by the following formula:

[0223]

[0224] Among them, a2 is the store efficiency factor, x l is the number of the lth competitor type, y l is the competition coefficient of the lth competitor type, h is the number of the lth competitor type, and h is an integer greater than or equal to 1.

[0225] The device for processing geographic location information provided in this embodiment can be used to execute the solutions in the above embodiments. Its implementation principles and technical effects are similar and will not be described in detail here.

[0226] It should be noted that it should be understood that the division of the various modules of the above device is only a division of logical functions. In actual implementation, they can be fully or partially integrated into one physical entity, or they can be physically separated. And these modules can all be implemented in the form of software called by processing elements; they can also be all implemented in the form of hardware; some modules can also be implemented in the form of software called by processing elements, and some modules can be implemented in the form of hardware. For example, the processing module can be a separately established processing element, or it can be integrated in a chip of the above device. In addition, it can also be stored in the memory of the above device in the form of program code, and called and executed by a processing element of the above device. The function of the above-determined module. The implementation of other modules is similar. In addition, these modules can be fully or partially integrated together, or they can be implemented independently. The processing element here can be an integrated circuit with signal processing capabilities. In the implementation process, each step of the above method or each module above can be completed by an integrated logic circuit of hardware in the processor element or instructions in the form of software.

[0227] For example, the above modules may be one or more integrated circuits configured to implement the above methods, such as one or more application specific integrated circuits (ASIC), or one or more microprocessors (digital signal processors, DSP), or one or more field programmable gate arrays (FPGA), etc. For another example, when a module above is implemented in the form of a processing element scheduling program code, the processing element may be a general-purpose processor, such as a central processing unit (CPU) or other processor that can call program code. For another example, these modules may be integrated together and implemented in the form of a system-on-a-chip (SOC).

[0228] In the above embodiments, it can be implemented in whole or in part by software, hardware, firmware or any combination thereof. When implemented using software, it can be implemented in whole or in part in the form of a computer program product. The computer program product includes one or more computer instructions. When loading and executing computer program instructions on a computer, the process or function according to the embodiment of the present application is generated in whole or in part. The computer can be a general-purpose computer, a special-purpose computer, a computer network, or other programmable devices. The computer instructions can be stored in a computer-readable storage medium, or transmitted from one computer-readable storage medium to another computer-readable storage medium. For example, the computer instructions can be transmitted from a website site, a computer, a server or a data center by wired (e.g., coaxial cable, optical fiber, digital subscriber line (DSL)) or wireless (e.g., infrared, wireless, microwave, etc.) mode to another website site, computer, server or data center. The computer-readable storage medium can be any available medium that a computer can access or a data storage device such as a server or a data center that includes one or more available media integration. The available medium can be a magnetic medium, (e.g., a floppy disk, a hard disk, a tape), an optical medium (e.g., a DVD), or a semiconductor medium (e.g., a solid state disk (SSD)), etc.

[0229] Fig. 9 This is a schematic diagram of the structure of an electronic device provided in an embodiment of the present application. Fig. 9 As shown, the device may include: a processor 91 , a memory 92 , a display 93 , and a system bus 94 .

[0230] The processor 91 executes the computer-executable instructions stored in the memory, so that the processor 91 executes the solutions in the above embodiments.

[0231] The processor 91 can be a general-purpose processor, including a central processing unit CPU, a network processor (NP), etc.; it can also be a digital signal processor DSP, an application-specific integrated circuit ASIC, a field programmable gate array FPGA or other programmable logic devices, discrete gate or transistor logic devices, discrete hardware components.

[0232] The memory 92 stores computer execution instructions, and the display 93 is used to display the processing results of the processor 91 and interact with humans. The memory 92 and the display 93 are connected to the processor 92 through the system bus 94 and complete the communication between them.

[0233] The system bus 94 may be a peripheral component interconnect (PCI) bus or an extended industry standard architecture (EISA) bus, etc. The system bus may be divided into an address bus, a data bus, a control bus, etc. For ease of representation, only one thick line is used in the figure, but it does not mean that there is only one bus or one type of bus. The transceiver is used to realize the communication between the database access device and other devices (such as a client, a read-write library, and a read-only library). The memory may include a random access memory (RAM), and may also include a non-volatile memory (non-volatile memory), such as at least one disk storage.

[0234] The present application also provides a computer-readable storage medium in which computer instructions are stored. When the computer instructions are executed on a computer, the computer executes the solution of the above embodiment.

[0235] An embodiment of the present application also provides a chip for running instructions, which is used to execute the solution in the above embodiment.

[0236] An embodiment of the present application also provides a computer program product, which includes a computer program stored in a computer-readable storage medium. At least one processor can read the computer program from the computer-readable storage medium, and when at least one processor executes the computer program, the solution in the above embodiment can be implemented.

[0237] Finally, it should be noted that the above embodiments are only used to illustrate the technical solutions of the present application, rather than to limit it. Although the present application has been described in detail with reference to the aforementioned embodiments, those skilled in the art should understand that they can still modify the technical solutions described in the aforementioned embodiments, or replace some or all of the technical features therein with equivalents. However, these modifications or replacements do not cause the essence of the corresponding technical solutions to deviate from the scope of the technical solutions of the embodiments of the present application.

Claims

1. A method for processing geographic location information, It is characterized in that include: Obtaining a pre-selected geographic location of a target store and information about objects within a preset distance range centered on the pre-selected geographic location; Processing the object information within the preset distance range to obtain a location influence factor and a store efficiency factor when opening the target store at the preselected geographical location; Determine whether the pre-selected geographical location meets the target store opening requirements based on the attribute information of the target store, the location influence factor when opening the target store in the pre-selected geographical location, and the store effect factor, wherein the location influence factor is the influence of residents and community prices within a preset range on the target store, and the store effect factor is the influence of other competing stores within the preset range on the target store; The determining whether the preselected geographical location meets the target store opening requirements according to the attribute information of the target store, the location influence factor when opening the target store at the preselected geographical location, and the store efficiency factor includes: According to the attribute information of the target store, obtaining the flow of people, the area and the cost of the target store in a preset time period; Determine the transaction information of the target store in the preset time period according to the location influence factor, the store efficiency factor, the preset per capita consumption information and the traffic information; Determine location benefit information of the target store in the preset time period according to the transaction information and the target store area; Determining the revenue information of the target store in the preset period according to the transaction information and the cost of the target store; According to the location benefit information and the revenue information of the target store in the preset time period, it is determined whether the pre-selected geographical location meets the needs for store opening.

2. The method according to claim 1, It is characterized in that The transaction information of the target store in the preset period is obtained by the following formula: S=a1*a2*b*c Among them, S is the transaction information of the target store in the preset time period, a1 represents the location influence factor, a2 represents the store efficiency factor, b represents the preset per capita consumption information, and c represents the flow of people information.

3. The method according to claim 1 or 2, It is characterized in that The object information includes: population information and community information; Processing the object information within the preset distance range to obtain a location influence factor for opening the target store at the preselected geographical location includes: Determine the average location cost of the cell within the preset distance range and the population information and cell information of the target area within the preset distance range according to the population information and cell information within the preset distance range; Determine the average cell location cost of the target area according to the population information and cell information of the target area within the preset distance range; The location impact factor of the target store is determined according to the average location cost of the cell within the preset distance range and the average location cost of the cell in the target area.

4. The method according to claim 3, It is characterized in that The mean cell location cost of the target area is obtained using the following formula: Wherein, k1 is the mean value of the cell locations in the target area, A i is the location cost of the ith cell in the target area, B i is the number of households in the ith cell in the target area, n is the number of cells in the target area, and n is an integer greater than or equal to 1; The average cell location cost k2 within the preset distance range is obtained using the following formula: Wherein, k2 is the average value of the cell locations within the preset distance range, A i is the location cost of the ith cell within the preset distance range, B i is the number of households in the ith cell within the preset distance range, m is the number of cells within the preset distance range, both m and n are integers greater than or equal to 1, and m is greater than or equal to n; The location influence factor of the target store is obtained using the following formula: a1=k2 / k1 Wherein, a1 is the location impact factor, k1 is the average location cost of the cells in the target area, and k2 is the average location cost of the cells within the preset distance range.

5. The method according to claim 1 or 2, It is characterized in that The object information includes: information about competitors of the target store; Processing the object information within the preset distance range to obtain a store efficiency factor for opening the target store at the preselected geographical location includes: Determine at least one competitor type of the target store and the quantity of each competitor type according to competitor information of the target store within the preset distance range; The store performance factor of the target store is determined according to at least one competitor type of the target store, the quantity of each competitor type, and a preset competition coefficient of each competitor type.

6. The method according to claim 5, It is characterized in that The store efficiency factor is obtained by the following formula: Wherein, a2 is the store efficiency factor, and x l is the number of competitors of the lth type, the y l is the competition coefficient of the l-th competitor type, h is the number of types of the l-th competitor, and h is an integer greater than or equal to 1.

7. A device for processing geographic location information, It is characterized in that include: Acquisition module and processing module; The acquisition module is used to acquire a pre-selected geographical location of a target store and information about objects within a preset distance range centered on the pre-selected geographical location; The processing module is used to process the object information within the preset distance range to obtain the location influence factor and the store efficiency factor when opening the target store at the preselected geographical location, and determine whether the preselected geographical location meets the target store opening requirements based on the attribute information of the target store, the location influence factor and the store efficiency factor when opening the target store at the preselected geographical location, wherein the location influence factor is the influence of the residents and community prices within the preset range on the target store, and the store effect factor is the influence of other competing stores within the preset range on the target store; The processing module is specifically used for: According to the attribute information of the target store, obtaining the flow of people, the area and the cost of the target store in a preset time period; Determine the transaction information of the target store in the preset time period according to the location influence factor, the store efficiency factor, the preset per capita consumption information and the traffic information; Determine location benefit information of the target store in the preset time period according to the transaction information and the target store area; Determining the revenue information of the target store in the preset period according to the transaction information and the cost of the target store; According to the location benefit information and the revenue information of the target store in the preset time period, it is determined whether the pre-selected geographical location meets the needs for store opening.

8. An electronic device, It is characterized in that include: Processor, memory, display and system bus; The memory stores computer-executable instructions; The processor executes the computer-executable instructions stored in the memory, so that the processor performs the method according to any one of claims 1 to 6.

9. A computer-readable storage medium, It is characterized in that The computer-readable storage medium stores computer-executable instructions, and when the computer-executable instructions are executed by a processor, they are used to implement the method according to any one of claims 1 to 6.

Images