WO2023040883A1 - 区域识别方法和装置 - Google Patents

区域识别方法和装置 Download PDF

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Publication number
WO2023040883A1
WO2023040883A1 PCT/CN2022/118687 CN2022118687W WO2023040883A1 WO 2023040883 A1 WO2023040883 A1 WO 2023040883A1 CN 2022118687 W CN2022118687 W CN 2022118687W WO 2023040883 A1 WO2023040883 A1 WO 2023040883A1
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Prior art keywords
target
area
grid
latitude
feature data
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PCT/CN2022/118687
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English (en)
French (fr)
Inventor
赵芮
蒋宁宁
康宁轩
李熠鑫
陈莹
祝捷
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北京沃东天骏信息技术有限公司
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Publication of WO2023040883A1 publication Critical patent/WO2023040883A1/zh

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    • G—PHYSICS
    • G06—COMPUTING; CALCULATING OR COUNTING
    • G06F—ELECTRIC DIGITAL DATA PROCESSING
    • G06F16/00—Information retrieval; Database structures therefor; File system structures therefor
    • G06F16/20—Information retrieval; Database structures therefor; File system structures therefor of structured data, e.g. relational data
    • G06F16/29—Geographical information databases
    • G—PHYSICS
    • G06—COMPUTING; CALCULATING OR COUNTING
    • G06F—ELECTRIC DIGITAL DATA PROCESSING
    • G06F16/00—Information retrieval; Database structures therefor; File system structures therefor
    • G06F16/20—Information retrieval; Database structures therefor; File system structures therefor of structured data, e.g. relational data
    • G06F16/24—Querying
    • G06F16/245—Query processing
    • G06F16/2455—Query execution
    • G—PHYSICS
    • G06—COMPUTING; CALCULATING OR COUNTING
    • G06Q—INFORMATION AND COMMUNICATION TECHNOLOGY [ICT] SPECIALLY ADAPTED FOR ADMINISTRATIVE, COMMERCIAL, FINANCIAL, MANAGERIAL OR SUPERVISORY PURPOSES; SYSTEMS OR METHODS SPECIALLY ADAPTED FOR ADMINISTRATIVE, COMMERCIAL, FINANCIAL, MANAGERIAL OR SUPERVISORY PURPOSES, NOT OTHERWISE PROVIDED FOR
    • G06Q30/00—Commerce
    • G06Q30/02—Marketing; Price estimation or determination; Fundraising
    • G06Q30/0201—Market modelling; Market analysis; Collecting market data
    • G06Q30/0203—Market surveys; Market polls
    • G—PHYSICS
    • G06—COMPUTING; CALCULATING OR COUNTING
    • G06Q—INFORMATION AND COMMUNICATION TECHNOLOGY [ICT] SPECIALLY ADAPTED FOR ADMINISTRATIVE, COMMERCIAL, FINANCIAL, MANAGERIAL OR SUPERVISORY PURPOSES; SYSTEMS OR METHODS SPECIALLY ADAPTED FOR ADMINISTRATIVE, COMMERCIAL, FINANCIAL, MANAGERIAL OR SUPERVISORY PURPOSES, NOT OTHERWISE PROVIDED FOR
    • G06Q30/00—Commerce
    • G06Q30/02—Marketing; Price estimation or determination; Fundraising
    • G06Q30/0201—Market modelling; Market analysis; Collecting market data
    • G06Q30/0204—Market segmentation
    • G06Q30/0205—Location or geographical consideration

Definitions

  • the present disclosure relates to the field of computer technology, and in particular to an area identification method and device.
  • the address determines the amount of traffic, the purchasing power of customers, the consumption structure of customers, the degree of attraction to potential customers, and the strength of competitiveness.
  • Proper site selection will occupy the advantage of "geographical advantages". Therefore, site selection plays an important role in business operations.
  • enterprises in different industries select sites according to different site selection principles.
  • the catering industry generally chooses addresses in places with convenient transportation and high traffic.
  • the logistics industry will select locations based on transportation distance, transportation time and radiation range. The above-mentioned traditional site selection methods need to spend a lot of time and manpower for research in the early stage, which not only increases the cost, but also is not efficient.
  • the embodiments of the present disclosure provide an area identification method and device.
  • an area identification method including:
  • an area identification request where the area identification request includes address information and target statistical indicators of the target area;
  • a plurality of binary codes corresponding to the plurality of target latitude and longitude coordinates form a geographic interval;
  • the preset storage unit stores historical data in the form of key-value pairs, and the historical data includes historical address and historical feature data, the preset storage unit uses the binary code corresponding to the historical address as a key, and uses the historical feature data as a key;
  • the region identification request also includes a code length
  • Performing binary encoding processing on the target latitude and longitude coordinates of the target area respectively includes: performing binary encoding processing on the target latitude and longitude coordinates of the target area respectively based on the encoding length;
  • Calculating the target characteristic data, and determining the thermal region in the target region based on the calculation result includes: determining the grid width and height corresponding to the code length; based on the grid width and height, the The target area is divided into grids; for each grid in the target area, the target characteristic data in the grid is calculated, and the thermal area in the target area is determined based on the calculation results.
  • the region identification request also includes a thermal threshold
  • Calculating the target feature data in the grid, and determining the thermal area in the target area based on the calculation result includes: performing aggregation calculation on the target feature data in the grid, and determining the thermal value of the grid ; Determine that the grid whose heat value is greater than or equal to the heat threshold is a heat area in the target area.
  • the method further includes: acquiring store location conditions; wherein, the store location conditions include one or more of the following: location target positioning requirements, the maximum distance from the intersection is not greater than the distance threshold and within the predetermined Set the area within the range; determine the grid that meets the location selection condition from the thermal area, and use the location of the grid that meets the location selection condition as the candidate address of the store.
  • the store location conditions include one or more of the following: location target positioning requirements, the maximum distance from the intersection is not greater than the distance threshold and within the predetermined Set the area within the range; determine the grid that meets the location selection condition from the thermal area, and use the location of the grid that meets the location selection condition as the candidate address of the store.
  • obtaining the area identification request includes: receiving the name of the target area and the target statistical index input by the user through the first interactive interface; and generating the area identification request based on the name of the target area and the target statistical index.
  • obtaining the area identification request includes: receiving the target statistical index input by the user through the second interactive interface; in response to the user's area drawing operation on the map, determining multiple latitude and longitude coordinates of the area drawn by the user; based on the A plurality of longitude and latitude coordinates of the area drawn by the user and the target statistical index generate an area identification request.
  • the target statistical index includes a plurality of target categories, and the target feature data is the target feature data of each target category;
  • the method also includes: determining a color corresponding to each target category;
  • calculating the target feature data in the grid, and determining the thermal area in the target area based on the calculation result includes: for each grid in the target area grid, performing aggregation calculation on the target feature data of the target category in the grid, and determining the target category with the highest sales volume or total turnover in the grid; based on the color corresponding to the target category with the highest sales volume or total turnover,
  • the grid is rendered, and the rendered grid is used as a thermal region.
  • an area identification device including:
  • An acquisition module configured to acquire an area identification request, where the area identification request includes address information and target statistical indicators of the target area;
  • the transcoding module is used to analyze the address information of the target area, obtain multiple target latitude and longitude coordinates of the target area, respectively perform binary coding processing on the target latitude and longitude coordinates of the target area, and determine the coordinates corresponding to each target latitude and longitude coordinate.
  • binary code a geographical interval composed of multiple binary codes corresponding to the multiple target latitude and longitude coordinates;
  • the data query module is used to obtain the target feature data corresponding to the target statistical index within the geographic interval from a preset storage unit;
  • the preset storage unit stores historical data in the form of key-value pairs,
  • the historical data includes historical addresses and historical feature data, and the preset storage unit uses the binary code corresponding to the historical address as a key and the historical feature data as a key;
  • An identification module configured to calculate the target characteristic data, and determine the thermal region in the target area based on the calculation result.
  • the region identification request also includes a code length
  • the transcoding module is further configured to: perform binary coding processing on the target longitude and latitude coordinates of the target area based on the coding length;
  • the identification module is also used to: determine the grid width and height corresponding to the code length; based on the grid width and height, perform grid division on the target area; A grid, calculating the target characteristic data in the grid, and determining the thermal area in the target area based on the calculation result.
  • the region identification request also includes a thermal threshold
  • the identification module is also used to: aggregate and calculate the target feature data in the grid, and determine the thermal value of the grid; determine that the grid whose thermal value is greater than or equal to the thermal threshold is in the target area thermal region.
  • the device further includes a location selection module, configured to: acquire store location conditions; wherein, the store location conditions include one or more of the following: location target positioning requirements, maximum distance from intersections Greater than the distance threshold and within the preset area range; determine the grid that meets the location selection condition from the thermal area, and use the location of the grid that meets the location selection condition as the candidate address of the store.
  • the store location conditions include one or more of the following: location target positioning requirements, maximum distance from intersections Greater than the distance threshold and within the preset area range; determine the grid that meets the location selection condition from the thermal area, and use the location of the grid that meets the location selection condition as the candidate address of the store.
  • the obtaining module is further configured to: receive the name of the target area and the target statistical index input by the user through the first interactive interface; and generate an area identification request based on the name of the target area and the target statistical index.
  • the acquisition module is further configured to: receive the target statistical index input by the user through the second interactive interface; in response to the user's area drawing operation on the map, determine multiple latitude and longitude coordinates of the area drawn by the user;
  • An area identification request is generated based on the multiple latitude and longitude coordinates of the area drawn by the user and the target statistical index.
  • the target statistical index includes a plurality of target categories, and the target feature data is the target feature data of each target category;
  • the device also includes a color determination module for determining the color corresponding to each target category
  • the identification module is also used for: for each grid in the target area, respectively aggregate and calculate the target characteristic data of the target categories in the grid, and determine the highest sales volume or total turnover in the grid.
  • Target category based on the color corresponding to the target category with the highest sales volume or total turnover, the grid is rendered, and the rendered grid is used as a heat area.
  • an electronic device including: one or more processors; a storage device for storing one or more programs, when the one or more The program is executed by the one or more processors, so that the one or more processors implement the area identification method of the embodiment of the present disclosure.
  • a computer readable medium on which a computer program is stored, and when the program is executed by a processor, the area identification method of the embodiments of the present disclosure is implemented.
  • an embodiment of the above disclosure has the following advantages or beneficial effects: by obtaining an area identification request, the area identification request includes address information and target statistical indicators of the target area; analyzing the address information of the target area to obtain multiple target longitude and latitude coordinates, Determine the binary code corresponding to the latitude and longitude coordinates of each target; form a geographical interval by multiple binary codes corresponding to the latitude and longitude coordinates of multiple targets; obtain the target characteristic data corresponding to the statistical indicators of the target within the geographical interval from the preset storage unit ; Calculate the target characteristic data, and determine the thermal area in the target area based on the technical means of the calculation results, which realizes the use of online data to optimize the area recognition ability; by encoding the longitude and latitude coordinates of the target area, the corresponding binary code is obtained , the geographical interval is composed of binary codes, and then the target characteristic data in the geographical interval is obtained.
  • FIG. 1 is a schematic diagram of the main flow of an area identification method according to an embodiment of the present disclosure
  • FIG. 2 is a schematic diagram of a target area of an area identification method according to an embodiment of the present disclosure
  • FIG. 3 is a schematic diagram of a target area of an area identification method according to another embodiment of the present disclosure.
  • FIG. 4 is a schematic diagram of main modules of an area identification device according to an embodiment of the present disclosure.
  • FIG. 5 is an exemplary system architecture diagram to which embodiments of the present disclosure can be applied.
  • FIG. 6 is a schematic structural diagram of a computer system suitable for implementing a terminal device or a server according to an embodiment of the present disclosure.
  • the area identification method of the embodiment of the present disclosure can identify the thermal area in the specified area (ie target area), so that the regional distribution of relevant business data (such as sales data) can be observed.
  • This method uses the stored online data and the user-defined thermal value calculation method to calculate the thermal value of the midpoint of the target area, and draws a thermal map based on the thermal value to identify the thermal area in the target area.
  • the larger the heat value the darker the color.
  • FIG. 1 is a schematic flowchart of main steps of an area identification method according to an embodiment of the present disclosure. As shown in Figure 1, the method includes:
  • Step S101 Acquiring an area identification request, the area identification request including address information and target statistical indicators of the target area;
  • Step S102 Analyze the address information of the target area, obtain multiple target latitude and longitude coordinates of the target area, respectively perform binary coding processing on the target latitude and longitude coordinates of the target area, and determine the binary code corresponding to each target latitude and longitude coordinate ;
  • a plurality of binary codes corresponding to the plurality of target latitude and longitude coordinates form a geographic interval;
  • Step S103 Obtain the target characteristic data corresponding to the target statistical index within the geographic interval from a preset storage unit; the preset storage unit stores historical data in the form of key-value pairs, and the historical The data includes historical addresses and historical feature data, and the preset storage unit uses the binary code corresponding to the historical address as a key and the historical feature data as a key;
  • Step S104 Calculating the target characteristic data, and determining a thermal area in the target area based on the calculation result.
  • the area identification request includes address information and target statistical indicators of the target area.
  • the address information of the target area may be the name of the target area, such as XX city or Y county of XX city.
  • the name of the target area may be the name of the province, city, or county divided according to the administrative area, or the name of the area divided according to other methods, such as North China and Northeast China according to the geographical division.
  • the address information of the target area may also be latitude and longitude information of the target area.
  • Target stats are used to calculate thermal values for points in the target area.
  • the online sales data can be used to calculate the heat value of the target area midpoint.
  • the target statistical indicators can include target categories, historical sales periods, and business indicators.
  • Business indicators can be sales volume, GMV (GrossMerchandiseVolume, total turnover, including payment amount and unpaid amount), etc. It is worth noting that in practical applications, the granularity of the target category can be flexibly set, and can support multi-level categories and multiple granularity configurations of a single item (sku).
  • the area identification request defines the business requirement, that is, the area identification request can determine the sales distribution of the target item in the area that the user expects to view in the past period of time.
  • the area identification request may be obtained through the following process: receiving the name of the target area and the target statistical index input by the user through the first interactive interface; generating an area identification based on the name of the target area and the target statistical index ask.
  • the user can select or fill in the name of the area to be viewed through the visual interactive interface, such as xx district of xx city or xx county.
  • You can also select the target category, historical sales period, and business indicators through the visual interactive interface. For example, if you select electronic products for the item category, the historical sales period is 2020-2021, and the business indicator is sales volume.
  • the area identification request may also be obtained through the following process: receiving the target statistical index input by the user through the second interactive interface; in response to the user's area drawing operation on the map, determining the area drawn by the user Multiple latitude and longitude coordinates of the area drawn by the user and the target statistical index to generate an area identification request.
  • the user can select or fill in the required target statistical indicators through the visual interactive interface.
  • the user's area drawing operation on the map may be that the user draws a polygonal area (the polygonal area is defined by a series of coordinate point columns) on the map, or may draw a circular area by selecting a center point and setting a coverage radius.
  • the drawn polygonal area may be shown in FIG. 2
  • the drawn circular area may be shown in FIG. 3 .
  • the method of the embodiment of the present disclosure supports multiple ways of selecting the target area, which is flexible and convenient.
  • the embodiment of the present disclosure performs encoding processing by analyzing address information of the target area to obtain multiple target longitude and latitude coordinates of the target area. Coding processing is performed for each target latitude and longitude coordinate, and the binary code corresponding to each target latitude and longitude coordinate is determined, and the geographic interval is formed by the binary code. This geographic interval limits the scope of acquiring target feature data.
  • the region identification request also includes a code length. When encoding the target latitude and longitude coordinates, the target latitude and longitude coordinates can be encoded based on the encoding length to obtain a binary code whose length is equal to the encoding length.
  • the target area can be divided into grids, and the size of the grid can be determined according to the code length.
  • different address code lengths can be selected according to different display requirements, so as to adapt to various query volume and accuracy requirements. It can not only support users to conduct high-precision query to the community, but also support slightly lower precision but coverage to districts and counties High-efficiency user interactive query can be realized through address coding.
  • Geohash encoding may be performed on the target latitude and longitude coordinates of the target area.
  • Geohash encoding is an address encoding method that can encode two-dimensional spatial longitude and latitude data into a string.
  • Geohash encoding There are three steps in Geohash encoding: first, convert the latitude and longitude into binary; second, merge the latitude and longitude; and finally encode according to Base32.
  • Base32 encoding is a scheme that uses 32 printable characters (letters A-Z and numbers 2-7) to encode arbitrary byte data.
  • the encoded string is not case-sensitive and excludes confusing characters, which can be easily used by people. and processed by a computer.
  • the latitude range of point (39.923201, 116.390705) is (-90, 90), and the middle value is 0.
  • the middle value of the (0, 90) interval is 45 degrees
  • the latitude 39.923201 is less than 45, so a 0 is obtained, and the calculation is performed sequentially to obtain the latitude Binary representation, 10111000110001111001.
  • the binary representation of the longitude 116.390705 can be obtained as: 11010010110001000100, the longitude occupies even digits, and the latitude occupies odd digits.
  • Encode according to Base32 convert 5 binary digits into a base32 code, and obtain the code: w64g0ec1.
  • the historical data may be historical order data
  • the historical address may be historical delivery address
  • the historical feature data may be sales volume or GMV.
  • the historical order data can be processed and encoded in advance and stored in a storage unit such as a database, thereby improving the efficiency of data query.
  • a storage unit such as a database
  • different encoding lengths can be set.
  • the embodiments of the present disclosure process and encode massive historical order data and store them in a database, and support efficient query through specific coding design.
  • the embodiment of the present disclosure adopts the Geohash algorithm to divide the order into a grid and establish an index, that is, to find a spatial curve that fills the entire On the surface of the Earth, points are indexed according to their order on the curve.
  • the use of Geohash coding makes the codes all over the country follow the same specification. At the same time, because different code lengths correspond to different precisions, Geohash can support flexible retrieval of multiple precisions.
  • the aggregated data with the Geohash grid as the smallest unit can be obtained.
  • the corresponding index of the grid is the Geohash code (binary code). The smallest unit of storage and query is changed from the order granularity to the grid.
  • the code length and thermal threshold can also be obtained by analyzing the region identification request.
  • the width and height of the grid can be determined by the encoding length (see Table 1 above), and the target area can be divided into grids according to the width and height.
  • the target feature data (sales or GMV) in the grid is aggregated and calculated, that is, the target feature data in the grid is summed to obtain the thermal value.
  • the grid whose heat value is greater than the heat threshold is taken as the heat area of the target area.
  • it can be rendered in different colors according to the heat value.
  • the area identification request includes address information and target statistical indicators of the target area; analyzing the address information of the target area, obtaining multiple target longitude and latitude coordinates, and determining the relationship with each The binary code corresponding to the target longitude and latitude coordinates; the geographical interval is composed of multiple binary codes corresponding to the target longitude and latitude coordinates; the target feature data corresponding to the target statistical indicators within the geographic interval is obtained from the preset storage unit; the target feature Data is calculated, and the technical means of determining the thermal area in the target area based on the calculation results realizes the use of online data to optimize the area recognition ability; by encoding the longitude and latitude coordinates of the target area, the corresponding binary code is obtained, and the binary code Form a geographical interval, and then obtain the target feature data in the geographical interval.
  • the embodiments of the present disclosure can flexibly adapt to a variety of query volume and accuracy requirements by encoding the delivery address of historical order data.
  • efficient user interactive query can be realized by using geohash codes of different lengths at the bottom layer for calculation.
  • the area identification method of the embodiment of the present disclosure can also perform site selection, such as selecting a candidate address that meets the requirements from the thermal area according to a specific site selection strategy.
  • site selection such as selecting a candidate address that meets the requirements from the thermal area according to a specific site selection strategy.
  • the process can include:
  • the store location conditions include one or more of the following: location target positioning requirements, the maximum distance from the intersection is not greater than the distance threshold and within the preset area range;
  • the target positioning requirements for location selection refer to the functional positioning of the store and the requirements for achieving this function.
  • the functional positioning of a store can be promotion and display, and the requirement for achieving this function is that the candidate address is in a business circle (the scope of the business circle can be preset. ).
  • the functional positioning of the store can also be zero, and the requirement to meet this function can be that the candidate address is within the range of the living community (the range of multiple living communities can be preset).
  • the maximum distance from the intersection is not greater than the distance threshold, since the store is to provide convenient services to the target user group, the store is selected at a location closer to the intersection.
  • the condition within the preset area can be flexibly set according to the size and cost of the store.
  • the area identification method of the embodiments of the present disclosure can not only be used to identify hot areas for location selection, but also recommend hot-selling products to offline stores.
  • the specific process can be as follows:
  • a target area identification request is received, and the target area identification request includes address information of the target area, target statistical indicators, and code length; wherein, the target statistical indicators include multiple target categories, historical sales periods, and business indicators.
  • Business indicators can be sales volume, GMV, etc.;
  • the binary code a plurality of binary codes corresponding to the multiple target latitude and longitude coordinates form a geographic interval;
  • the preset storage unit stores historical data in the form of key-value pairs, and the historical data includes historical address and historical feature data, the preset storage unit uses the binary code corresponding to the historical address as a key, and uses the historical feature data as a key;
  • For each grid in the target area aggregate and calculate the target feature data of the target categories in the grid, and determine the target category with the highest sales volume or turnover in the grid;
  • the grid is rendered, and the rendered grid is used as a heat area.
  • This embodiment can determine the sales distribution of items of the target category in the target area, provide data support for store fabrics, and recommend hot-selling items.
  • the area identification method of the embodiment of the present disclosure can not only use online accumulation to drain offline, expand offline channels to achieve omni-channel layout, but also rely on fixed-point area data accumulation to recommend hot-selling products for designated stores and help stores Precise selection and distribution of goods will enable stores to have better dynamic sales, form a virtuous circle, and strengthen the layout of online and offline channels.
  • FIG. 4 is a schematic diagram of main modules of an area identification device 400 according to an embodiment of the present disclosure. As shown in Figure 4, the area identification device 400 includes:
  • Obtaining module 401 is used for obtaining area identification request, and described area identification request comprises the address information of target area and target statistical indicator;
  • the transcoding module 402 is configured to analyze the address information of the target area, obtain a plurality of target latitude and longitude coordinates of the target area, respectively perform binary coding processing on the target latitude and longitude coordinates of the target area, and determine the coordinates of each target latitude and longitude coordinate Corresponding binary codes; geographical intervals composed of multiple binary codes corresponding to the multiple target latitude and longitude coordinates;
  • the data query module 403 is used to obtain target characteristic data corresponding to the target statistical index within the geographic interval from a preset storage unit;
  • the preset storage unit stores historical data in the form of key-value pairs , the historical data includes historical addresses and historical feature data, the preset storage unit uses the binary code corresponding to the historical address as a key, and uses the historical feature data as a key;
  • the identification module 404 is configured to calculate the characteristic data of the target, and determine the thermal region in the target area based on the calculation result.
  • the region identification request also includes a code length
  • the transcoding module 402 is further configured to: perform binary encoding processing on the target longitude and latitude coordinates of the target area based on the encoding length;
  • the identification module 404 is further configured to: determine the grid width and height corresponding to the code length; based on the grid width and height, perform grid division on the target area; For each grid, calculate the target characteristic data in the grid, and determine the thermal region in the target area based on the calculation result.
  • the region identification request also includes a thermal threshold
  • the identification module 404 is further configured to: aggregate and calculate the target feature data in the grid, determine the thermal value of the grid; determine the grid whose thermal value is greater than or equal to the thermal threshold as the target area within the thermal region.
  • the device further includes a location selection module, configured to: acquire store location conditions; wherein, the store location conditions include one or more of the following: location target positioning requirements, maximum distance from intersections Greater than the distance threshold and within the preset area range; determine the grid that meets the location selection condition from the thermal area, and use the location of the grid that meets the location selection condition as the candidate address of the store.
  • the store location conditions include one or more of the following: location target positioning requirements, maximum distance from intersections Greater than the distance threshold and within the preset area range; determine the grid that meets the location selection condition from the thermal area, and use the location of the grid that meets the location selection condition as the candidate address of the store.
  • the obtaining module 401 is further configured to: receive the name of the target area and the target statistical index input by the user through the first interactive interface; and generate an area identification request based on the name of the target area and the target statistical index.
  • the acquisition module 401 is further configured to: receive the target statistical index input by the user through the second interactive interface; respond to the user's area drawing operation on the map, determine multiple latitude and longitude coordinates of the area drawn by the user;
  • An area identification request is generated based on the multiple latitude and longitude coordinates of the area drawn by the user and the target statistical index.
  • the target statistical index includes a plurality of target categories, and the target feature data is the target feature data of each target category;
  • the device also includes a color determination module for determining the color corresponding to each target category
  • the identification module 404 is further configured to: for each grid in the target area, perform aggregation calculation on the target feature data of the target category in the grid, and determine that the sales volume or total turnover in the grid is the highest The target category; based on the color corresponding to the target category with the highest sales or total turnover, the grid is rendered, and the rendered grid is used as a heat area.
  • the area identification device of the embodiment of the present disclosure uses online data to optimize the area identification ability; by encoding the latitude and longitude coordinates of the target area, the corresponding binary code is obtained, and the geographical interval is formed by the binary code, and then obtained within the geographical interval
  • different address encoding lengths can be selected according to different display requirements, so as to meet various query volume and accuracy requirements.
  • the above-mentioned device can execute the method provided by the embodiment of the present disclosure, and has corresponding functional modules and beneficial effects for executing the method.
  • the method provided by the embodiment of the present disclosure, and has corresponding functional modules and beneficial effects for executing the method.
  • FIG. 5 shows an exemplary system architecture 500 to which the area identification method or the area identification device of the embodiments of the present disclosure can be applied.
  • a system architecture 500 may include terminal devices 501 , 502 , and 503 , a network 504 and a server 505 .
  • the network 504 is used as a medium for providing communication links between the terminal devices 501 , 502 , 503 and the server 505 .
  • Network 504 may include various connection types, such as wires, wireless communication links, or fiber optic cables, among others.
  • Terminal devices 501 , 502 , 503 Users can use terminal devices 501 , 502 , 503 to interact with server 505 through network 504 to receive or send messages and the like.
  • Various communication client applications can be installed on the terminal devices 501, 502, and 503, such as shopping applications, web browser applications, search applications, instant messaging tools, email clients, social platform software, and the like.
  • the terminal devices 501, 502, 503 may be various electronic devices with display screens and supporting web browsing, including but not limited to smart phones, tablet computers, laptop computers, desktop computers and the like.
  • the server 505 may be a server that provides various services, such as a background management server that provides support for shopping websites browsed by users using the terminal devices 501 , 502 , and 503 .
  • the background management server can analyze and process the received data such as product information query requests, and feed back the processing results (such as target push information, product information) to the terminal device.
  • the area identification method provided by the embodiments of the present disclosure is generally executed by the server 505 , and accordingly, the area identification device is generally disposed in the server 505 .
  • terminal devices, networks and servers in Fig. 5 are only illustrative. According to the implementation needs, there can be any number of terminal devices, networks and servers.
  • FIG. 6 shows a schematic structural diagram of a computer system 600 suitable for implementing a terminal device according to an embodiment of the present disclosure.
  • the terminal device shown in FIG. 6 is only an example, and should not limit the functions and application scope of the embodiments of the present disclosure.
  • a computer system 600 includes a central processing unit (CPU) 601 that can be programmed according to a program stored in a read-only memory (ROM) 602 or a program loaded from a storage section 608 into a random-access memory (RAM) 603 Instead, various appropriate actions and processes are performed.
  • ROM read-only memory
  • RAM random-access memory
  • various programs and data required for the operation of the system 600 are also stored.
  • the CPU 601, ROM 602, and RAM 603 are connected to each other through a bus 604.
  • An input/output (I/O) interface 605 is also connected to the bus 604 .
  • the following components are connected to the I/O interface 605: an input section 606 including a keyboard, a mouse, etc.; an output section 607 including a cathode ray tube (CRT), a liquid crystal display (LCD), etc., and a speaker; a storage section 608 including a hard disk, etc. and a communication section 609 including a network interface card such as a LAN card, a modem, or the like.
  • the communication section 609 performs communication processing via a network such as the Internet.
  • a drive 610 is also connected to the I/O interface 605 as needed.
  • a removable medium 611 such as a magnetic disk, optical disk, magneto-optical disk, semiconductor memory, etc. is mounted on the drive 610 as necessary so that a computer program read therefrom is installed into the storage section 608 as necessary.
  • embodiments of the present disclosure include a computer program product, which includes a computer program carried on a computer-readable medium, where the computer program includes program codes for executing the methods shown in the flowcharts.
  • the computer program may be downloaded and installed from a network via the communication portion 609 and/or installed from a removable medium 611 .
  • this computer program is executed by a central processing unit (CPU) 601, the above-described functions defined in the system of the present disclosure are performed.
  • CPU central processing unit
  • the computer-readable medium shown in the present disclosure may be a computer-readable signal medium or a computer-readable storage medium or any combination of the above two.
  • a computer readable storage medium may be, for example, but not limited to, an electrical, magnetic, optical, electromagnetic, infrared, or semiconductor system, apparatus, or device, or any combination thereof. More specific examples of computer-readable storage media may include, but are not limited to, electrical connections with one or more wires, portable computer diskettes, hard disks, random access memory (RAM), read-only memory (ROM), erasable Programmable read-only memory (EPROM or flash memory), optical fiber, portable compact disk read-only memory (CD-ROM), optical storage device, magnetic storage device, or any suitable combination of the above.
  • a computer-readable storage medium may be any tangible medium that contains or stores a program that can be used by or in conjunction with an instruction execution system, apparatus, or device.
  • a computer-readable signal medium may include a data signal propagated in baseband or as part of a carrier wave, carrying computer-readable program code therein. Such propagated data signals may take many forms, including but not limited to electromagnetic signals, optical signals, or any suitable combination of the foregoing.
  • a computer-readable signal medium may also be any computer-readable medium other than a computer-readable storage medium, which can send, propagate, or transmit a program for use by or in conjunction with an instruction execution system, apparatus, or device.
  • Program code embodied on a computer readable medium may be transmitted using any appropriate medium, including but not limited to wireless, wireline, optical fiber cable, RF, etc., or any suitable combination of the foregoing.
  • each block in a flowchart or block diagram may represent a module, program segment, or portion of code that includes one or more logical functions for implementing specified executable instructions.
  • the functions noted in the block may occur out of the order noted in the figures. For example, two blocks shown in succession may, in fact, be executed substantially concurrently, or they may sometimes be executed in the reverse order, depending upon the functionality involved.
  • each block in the block diagrams or flowchart illustrations, and combinations of blocks in the block diagrams or flowchart illustrations can be implemented by a dedicated hardware-based system that performs the specified function or operation, or can be implemented by a A combination of dedicated hardware and computer instructions.
  • the modules involved in the embodiments described in the present disclosure may be implemented by software or by hardware.
  • the described modules may also be set in a processor.
  • a processor includes a sending module, an acquiring module, a determining module, and a first processing module.
  • the names of these modules do not limit the unit itself under certain circumstances, for example, the sending module can also be described as "a module that sends a picture acquisition request to the connected server".
  • the present disclosure also provides a computer-readable medium, which may be included in the device described in the above embodiments, or may exist independently without being assembled into the device.
  • the above-mentioned computer-readable medium carries one or more programs, and when the above-mentioned one or more programs are executed by the device, the device includes:
  • an area identification request where the area identification request includes address information and target statistical indicators of the target area;
  • a plurality of binary codes corresponding to the plurality of target latitude and longitude coordinates form a geographical interval;
  • the preset storage unit stores historical data in the form of key-value pairs, and the historical data includes historical address and historical feature data, the preset storage unit uses the binary code corresponding to the historical address as a key, and uses the historical feature data as a key;
  • the technical solution of the embodiment of the present disclosure realizes the use of online data to optimize the area recognition ability; by encoding the latitude and longitude coordinates of the target area, the corresponding binary code is obtained, and the geographic interval is formed by the binary code, and then the geographical interval is obtained.
  • the target characteristic data in the system can select different address encoding lengths according to different display requirements when encoding the latitude and longitude coordinates, so as to meet various query volume and accuracy requirements, and can support users to conduct high-precision queries to the community. It can also support queries with slightly lower accuracy but coverage up to the district and county level. Efficient user interactive query can be realized through address coding; after identifying the hot area, combined with the location selection strategy, the candidate address of the store can be determined from the hot area. It provides strong support for the expansion of offline channels, does not need to spend a lot of manpower and time for research, reduces costs, and improves efficiency.

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Abstract

本公开提供了一种区域识别方法和装置。该方法的一具体实施方式包括：获取区域识别请求，区域识别请求包括目标区域的地址信息和目标统计指标；解析目标区域的地址信息，获得多个目标经纬度坐标，确定与每一目标经纬度坐标对应的二进制码；由多个目标经纬度坐标对应的多个二进制码组成地理区间；从预设的存储单元中获取在地理区间内、与目标统计指标对应的目标特征数据；对目标特征数据进行计算，并基于计算结果确定目标区域中的热力区域。

Description

区域识别方法和装置
相关申请的交叉引用
本申请要求享有2021年9月15日提交的申请号为202111080088.9的中国发明专利申请的优先权，其全部内容通过引用并入本文。
技术领域
本公开涉及计算机技术领域，尤其涉及一种区域识别方法和装置。
背景技术
地址在某种程度上决定了客流量的多少、顾客购买力的大小、顾客的消费结构、对潜在顾客的吸引程度以及竞争力的强弱等。选址适当便占据了“地利”的优势，因此，选址在企业运营中起着重要的作用。目前，不同行业的企业根据不同的选址原则进行选址。例如，餐饮行业一般会将地址选在交通便利、人流量大的地方。物流行业会根据运输距离、运输时间和辐射范围等进行选址。上述传统的选址方法前期都需要花费大量的时间、人力进行调研，不仅提高了成本，且效率不高。
发明内容
有鉴于此，本公开的实施例提供一种区域识别方法和装置。
为实现上述目的，根据本公开的实施例的一个方面，提供了一种区域识别方法，包括：
获取区域识别请求，所述区域识别请求包括目标区域的地址信息和目标统计指标；
解析所述目标区域的地址信息，获得所述目标区域的多个目标经纬度坐标，分别对所述目标区域的目标经纬度坐标进行二进制编码处理，确定与每一目标经纬度坐标对应的二进制码；由所述多个目标经纬度坐标对应的多个二进制码组成地理区间；
从预设的存储单元中获取在所述地理区间内、与所述目标统计指标对应的目标特征数据；所述预设的存储单元以键值对的形式存储历史数据，所述历史数据包括历史地址和历史特征数据，所述预设的存储单元以所述历史地址对应的二进制码为键，以所述历史特征数据为键；
对所述目标特征数据进行计算，并基于计算结果确定所述目标区域中的热力区域。
可选地，所述区域识别请求还包括编码长度；
分别对所述目标区域的目标经纬度坐标进行二进制编码处理包括：基于所述编码长度，分别对所述目标区域的目标经纬度坐标进行二进制编码处理；
对所述目标特征数据进行计算，并基于计算结果确定所述目标区域中的热力区域包括：确定与所述编码长度对应的网格宽度和高度；基于所述网格宽度和高度，对所述目标区域进行网格化划分；针对所述目标区域中的每一网格，对所述网格内的目标特征数据进行计算，并基于计算结果确定所述目标区域中的热力区域。
可选地，所述区域识别请求还包括热力阈值；
对所述网格内的目标特征数据进行计算，并基于计算结果确定所述目标区域中的热力区域包括：对所述网格内的目标特征数据进行聚合计算，确定所述网格的热力值；确定热力值大于或等于所述热力阈值的网格为所述目标区域内的热力区域。
可选地，所述方法还包括：获取门店选址条件；其中，所述门店选址条件包括以下一种或多种：选址目标定位要求、与路口的最大距离不大于距离阈值和在预设面积范围内；从所述热力区域中确定满足所述选址条件的网格，将满足所述选址条件的网格所在的位置作为门店的候选地址。
可选地，获取区域识别请求包括：接收用户通过第一交互界面输入的目标区域的名称和目标统计指标；基于所述目标区域的名称和目标统计指标，生成区域识别请求。
可选地，获取区域识别请求包括：接收用户通过第二交互界面输入的目标统计指标；响应于用户在地图上的区域绘制操作，确定所述用户绘制的区域的多个经纬度坐标；基于所述用户绘制的区域的多个经纬度坐标和所述目标统计指标，生成区域识别请求。
可选地，所述目标统计指标包括多个目标品类，所述目标特征数据为每个目标品类的目标特征数据；
所述方法还包括：确定与每一目标品类对应的颜色；
针对所述目标区域中的每一网格，对所述网格内的目标特征数据进行计算，并基于计算结果确定所述目标区域中的热力区域包括：针对所述目标区域中的每一网格，分别对所述网格内的目标品类的目标特征数据进行聚合计算，确定所述网格内销量或成交总额最高的目标品类；基于所述销量或成交总额最高的目标品类对应的颜色，对所述网格进行渲染，将渲染的网格作为热力区域。
为实现上述目的，根据本公开的实施例的另一个方面，提供了一种区域识别装置，包括：
获取模块，用于获取区域识别请求，所述区域识别请求包括目标区域的地址信息和目标统计指标；
转码模块，用于解析所述目标区域的地址信息，获得所述目标区域的多个目标经纬度坐标，分别对所述目标区域的目标经纬度坐标进行二进制编码处理，确定与每一目标经纬度坐标对应的二进制码；由所述多个目标经纬度坐标对应的多个二进制码组成的地理区间；
数据查询模块，用于从预设的存储单元中获取在所述地理区间内、与所述目标统计指标对应的目标特征数据；所述预设的存储单元以键值对的形式存储历史数据，所述历史数据包括历史地址和历史特征数 据，所述预设的存储单元以所述历史地址对应的二进制码为键，以所述历史特征数据为键；
识别模块，用于对所述目标特征数据进行计算，并基于计算结果确定所述目标区域中的热力区域。
可选地，所述区域识别请求还包括编码长度；
所述转码模块还用于：基于所述编码长度，分别对所述目标区域的目标经纬度坐标进行二进制编码处理；
所述识别模块还用于：确定与所述编码长度对应的网格宽度和高度；基于所述网格宽度和高度，对所述目标区域进行网格化划分；针对所述目标区域中的每一网格，对所述网格内的目标特征数据进行计算，并基于计算结果确定所述目标区域中的热力区域。
可选地，所述区域识别请求还包括热力阈值；
所述识别模块还用于：对所述网格内的目标特征数据进行聚合计算，确定所述网格的热力值；确定热力值大于或等于所述热力阈值的网格为所述目标区域内的热力区域。
可选地，所述装置还包括选址模块，用于：获取门店选址条件；其中，所述门店选址条件包括以下一种或多种：选址目标定位要求、与路口的最大距离不大于距离阈值和在预设面积范围内；从所述热力区域中确定满足所述选址条件的网格，将满足所述选址条件的网格所在的位置作为门店的候选地址。
可选地，所述获取模块还用于：接收用户通过第一交互界面输入的目标区域的名称和目标统计指标；基于所述目标区域的名称和目标统计指标，生成区域识别请求。
可选地，所述获取模块还用于：接收用户通过第二交互界面输入的目标统计指标；响应于用户在地图上的区域绘制操作，确定所述用 户绘制的区域的多个经纬度坐标；
基于所述用户绘制的区域的多个经纬度坐标和所述目标统计指标，生成区域识别请求。
可选地，所述目标统计指标包括多个目标品类，所述目标特征数据为每个目标品类的目标特征数据；
所述装置还包括颜色确定模块，用于确定与每一目标品类对应的颜色；
所述识别模块还用于：针对所述目标区域中的每一网格，分别对所述网格内的目标品类的目标特征数据进行聚合计算，确定所述网格内销量或成交总额最高的目标品类；基于所述销量或成交总额最高的目标品类对应的颜色，对所述网格进行渲染，将渲染的网格作为热力区域。
为实现上述目的，根据本公开的实施例的又一个方面，提供了一种电子设备，包括：一个或多个处理器；存储装置，用于存储一个或多个程序，当所述一个或多个程序被所述一个或多个处理器执行，使得所述一个或多个处理器实现本公开的实施例的区域识别方法。
为实现上述目的，根据本公开的实施例的一个方面，提供了一种计算机可读介质，其上存储有计算机程序，所述程序被处理器执行时实现本公开的实施例的区域识别方法。
上述公开中的一个实施例具有如下优点或有益效果：通过获取区域识别请求，所述区域识别请求包括目标区域的地址信息和目标统计指标；解析目标区域的地址信息，获得多个目标经纬度坐标，确定与每一目标经纬度坐标对应的二进制码；由多个目标经纬度坐标对应的多个二进制码组成地理区间；从预设的存储单元中获取在地理区间内、与目标统计指标对应的目标特征数据；对目标特征数据进行计算，并基于计算结果确定目标区域中的热力区域的技术手段，实现了利用线 上数据优化区域识别能力；通过对目标区域的经纬度坐标进行编码处理，获得对应的二进制码，由二进制码组成地理区间，然后获取在该地理区间内的目标特征数据，在对经纬度坐标进行编码处理时可以针对不同的展示需求选择不同的地址编码长度，从而适应多种查询量和准确性要求，既可支持用户进行高精度到小区的查询，也可支持精度略低但覆盖范围到区县级别的查询，通过地址编码可实现高效的用户交互式查询；在识别出热力区域之后，结合选址策略，可从热力区域中确定门店候选地址，为线下渠道拓展提供了有力的支持，不需要花费大量的人力和时间进行调研，降低了成本，且提升了效率。
上述的非惯用的可选方式所具有的进一步效果将在下文中结合具体实施方式加以说明。
附图说明
附图用于更好地理解本公开，不构成对本公开的不当限定。其中：
图1是本公开的实施例的区域识别方法的主要流程的示意图；
图2是本公开的实施例的区域识别方法的目标区域的示意图；
图3是本公开另一实施例的区域识别方法的目标区域的示意图；
图4是本公开的实施例的区域识别装置的主要模块的示意图；
图5是本公开的实施例可以应用于其中的示例性系统架构图；
图6是适于用来实现本公开的实施例的终端设备或服务器的计算机系统的结构示意图。
具体实施方式
以下结合附图对本公开的示范性实施例做出说明，其中包括本公开的实施例的各种细节以助于理解，应当将它们认为仅仅是示范性的。因此，本领域普通技术人员应当认识到，可以对这里描述的实施例做出各种改变和修改，而不会背离本公开的范围和精神。同样，为了清楚和简明，以下的描述中省略了对公知功能和结构的描述。
本公开的实施例的区域识别方法可以识别指定区域(即目标区域)中的热力区域，从而可以观察相关业务数据(如销量数据)的地区分布。该方法利用已存储的线上数据和用户定义的热力值计算方式计算目标区域中点的热力值，根据该热力值绘制热力图，从而识别目标区域中的热力区域。在可选的实施例中，在热力图中，热力值越大颜色越深。图1是本公开一实施例的区域识别方法的主要步骤的流程示意图。如图1所示，该方法包括：
步骤S101：获取区域识别请求，所述区域识别请求包括目标区域的地址信息和目标统计指标；
步骤S102：解析所述目标区域的地址信息，获得所述目标区域的多个目标经纬度坐标，分别对所述目标区域的目标经纬度坐标进行二进制编码处理，确定与每一目标经纬度坐标对应的二进制码；由所述多个目标经纬度坐标对应的多个二进制码组成地理区间；
步骤S103：从预设的存储单元中获取在所述地理区间内、与所述目标统计指标对应的目标特征数据；所述预设的存储单元以键值对的形式存储历史数据，所述历史数据包括历史地址和历史特征数据，所述预设的存储单元以所述历史地址对应的二进制码为键，以所述历史特征数据为键；
步骤S104：对所述目标特征数据进行计算，并基于计算结果确定所述目标区域中的热力区域。
对于步骤S101，区域识别请求包括目标区域的地址信息和目标统计指标。其中，目标区域的地址信息可以是目标区域的名称，如XX市或XX市Y县。在本公开的实施例中目标区域的名称可以是按照行政区域划分的省市县的名称，也可以是按照其他方式划分的区域名称，如按照地理划分的华北地区、东北地区等。在可选的实施例中，目标区域的地址信息也可以是目标区域的经纬度信息。
目标统计指标用于计算目标区域中点的热力值。在可选的实施例中，可以利用线上销售数据来计算目标区域中点的热力值，因此，该 目标统计指标可以包括目标品类、历史销售时段以及业务指标。业务指标可以是销量、GMV(GrossMerchandiseVolume，成交总额，包括付款金额和未付款金额)等。值得说明的是，在实际应用中目标品类的粒度可以灵活设置，可以支持多级品类和单一物品(sku)多种粒度配置。
在本实施例中，区域识别请求定义了业务需求，即通过区域识别请求可以确定用户期望查看的地区在过去一段时间内目标物品的销量分布情况。
在可选的实施例中，可以通过如下过程获取区域识别请求：接收用户通过第一交互界面输入的目标区域的名称和目标统计指标；基于所述目标区域的名称和目标统计指标，生成区域识别请求。具体的，用户可通过可视化交互界面选择或填写需要查看的地区的名称，如xx市xx区或xx县。也可以通过该可视化交互界面选择目标品类、历史销售时段以及业务指标，如物品类目选择电子产品，历史销售时段为2020年-2021年，业务指标为销量。
在其他可选的实施例中，也可以通过如下过程获取区域识别请求：接收用户通过第二交互界面输入的目标统计指标；响应于用户在地图上的区域绘制操作，确定所述用户绘制的区域的多个经纬度坐标；基于所述用户绘制的区域的多个经纬度坐标和所述目标统计指标，生成区域识别请求。具体的，用户可以通过可视化交互界面选择或填写需要的目标统计指标。用户在地图上的区域绘制操作可以是用户在地图上绘制多边形区域(该多边形区域由一系列坐标点列定义)，也可以是通过选中中心点，并设置覆盖半径绘制圆形区域。绘制的多边形区域可以如图2所示，绘制的圆形区域可以如图3所示。
本公开的实施例的方法支持多种选定目标区域的方式，灵活方便。
对于步骤S102，本公开的实施例通过解析目标区域的地址信息进行编码处理，获得目标区域的多个目标经纬度坐标。针对每一目标经纬度坐标进行编码处理，确定与每一目标经纬度坐标对应的二进制码，由该二进制码组成地理区间。该地理区间限定了获取目标特征数据的范围。在可选的实施例中，区域识别请求还包括编码长度。在对目标经纬度坐标进行编码处理时，可以基于该编码长度对目标经纬度坐标编码，得到长度与该编码长度相等的二进制码。在本实施例中，可以对目标区域进行网格化划分，而网格的大小可以根据编码长度确定。进而，可以针对不同的展示需求选择不同的地址编码长度，从而适应多种查询量和准确性要求，既可支持用户进行高精度到小区的查询，也可支持精度略低但覆盖范围到区县级别的查询，通过地址编码可实现高效的用户交互式查询。作为具体的示例，可以对目标区域的目标经纬度坐标进行Geohash编码。Geohash编码是一种地址编码方法，能够将二维的空间经纬度数据编码成一个字符串。Geohash编码一共有三步：首先将经纬度转变成二进制；其次将经纬度合并；最后按照Base32进行编码。Base32编码是使用32个可打印字符(字母A-Z和数字2-7)对任意字节数据进行编码的方案，编码后的字符串不用区分大小写并排除了容易混淆的字符，可以方便地由人使用并由计算机处理。
Geohash编码过程举例如下：
比如点(39.923201,116.390705)纬度的范围是(-90，90)，其中间值为0。对于纬度39.923201，在区间(0，90)中，因此得到一个1；(0，90)区间的中间值为45度，纬度39.923201小于45，因此得到一个0，依次计算下去，即可得到纬度的二进制表示，10111000110001111001。同理可以得到经度116.390705的二进制表示为：11010010110001000100，经度占偶数位，纬度占奇数位，将经纬度合并：11100 11101 00100 01111 00000 01101 01011 00001。按照Base32进行编码，将5个二进制位转换成一个base32码，得到编码：w64g0ec1。
在本实施例中，不同的编码长度对应不同大小的网格，编码长度越长，表示的范围越小，位置也越精确。不同编码长度对应的网格长度如下表1所示：
表1：
编码长度 网格宽度 网格高度
1 5009.4km 4992.6km
2 1252.3km 624.1km
3 156.5km 156km
4 39.1km 19.5km
5 4.9km 4.9km
6 1.2km 609.4m
7 152.9m 152.4m
8 38.2m 19m
9 4.8m 4.8m
10 1.2m 59.5cm
11 14.9cm 14.9cm
12 3.7cm 1.9cm
对于步骤S103，历史数据可以是历史订单数据，历史地址可以是历史收货地址，历史特征数据可以是销量或GMV。为进一步提高区域识别效率，可以预先对历史订单数据进行加工编码并存储在存储单元如数据库中，从而提高数据查询效率。在对历史订单数据进行编码时，可以设置不同的编码长度。本公开的实施例通过对海量历史订单数据进行加工编码并存储在数据库中，通过特定的编码设计支持高效查询。具体的，本公开的实施例根据历史订单数据携带的收货地的经纬度信息，采用Geohash算法对订单进行网格划分并建立索引，即寻找一条空间曲线，在指定的精度范围内，填满整个地球表面，各点根据在曲线上的顺序确定索引。采用Geohash编码使得全国各地编码都遵循同一规范，同时，由于不同的编码长度对应不同精度，Geohash可支持多 种精度的灵活检索。编码完成即可得到以Geohash网格为最小单位的聚合的数据，网格对应索引即为Geohash码(二进制码)，存储和查询的最小单位由订单粒度转变为网格。
对于步骤S104，解析区域识别请求还可以得到编码长度和热力阈值。通过编码长度可以确定网格的宽度和高度(参见上表1)，根据该宽度和高度可以对目标区域进行网格化划分。将目标区域网格化划分之后，针对每一网格，对网格内的目标特征数据(销量或GMV)进行聚合计算，即对网格内的目标特征数据进行求和计算，得到热力值。然后，将热力值大于热力阈值的网格作为目标区域的热力区域。对于热力区域，可以根据热力值的大小渲染成不同的颜色。
本公开的实施例的区域识别方法，通过获取区域识别请求，所述区域识别请求包括目标区域的地址信息和目标统计指标；解析目标区域的地址信息，获得多个目标经纬度坐标，确定与每一目标经纬度坐标对应的二进制码；由多个目标经纬度坐标对应的多个二进制码组成地理区间；从预设的存储单元中获取在地理区间内、与目标统计指标对应的目标特征数据；对目标特征数据进行计算，并基于计算结果确定目标区域中的热力区域的技术手段，实现了利用线上数据优化区域识别能力；通过对目标区域的经纬度坐标进行编码处理，获得对应的二进制码，由二进制码组成地理区间，然后获取在该地理区间内的目标特征数据，在对经纬度坐标进行编码处理时可以针对不同的展示需求选择不同的地址编码长度，从而适应多种查询量和准确性要求，既可支持用户进行高精度到小区的查询，也可支持精度略低但覆盖范围到区县级别的查询，通过地址编码可实现高效的用户交互式查询；在识别出热力区域之后，结合选址策略，可从热力区域中确定门店候选地址，为线下渠道拓展提供了有力的支持，不需要花费大量的人力和时间进行调研，降低了成本，且提升了效率。
本公开的实施例通过对历史订单数据的收货地址进行编码，可灵 活适应多种查询量和准确性要求，譬如，既可支持用户进行高精度到小区的查询，也可支持精度略低但覆盖范围到区县级别的查询，通过底层采用不同长度的geohash码进行运算可实现高效的用户交互式查询。
本公开的实施例的区域识别方法在识别出目标区域的热力区域之后，还可以进行选址，如根据特定的选址策略从热力区域中选出满足要求的候选地址，具体的，该过程可以包括：
获取门店选址条件；其中，所述门店选址条件包括以下一种或多种：选址目标定位要求、与路口的最大距离不大于距离阈值和在预设面积范围内；
从所述热力区域中确定满足所述选址条件的网格，将满足所述选址条件的网格所在的位置作为门店的候选地址。
其中，选址目标定位要求是指门店的功能定位和达到该功能的要求，例如门店的功能定位可以是推广展示，达到该功能的要求是候选地址在商业圈(该商业圈的范围可以预先设置)。门店的功能定位也可以是零，达到该功能的要求可以是候选地址在生活社区范围内(可以预先设置多个生活社区的范围)。对于与路口的最大距离不大于距离阈值这一条件，由于门店是为了给目标用户群体提供便利的服务，所以门店选在距离路口较近的位置。对于在预设面积范围内这一条件，可以根据门店规模和成本灵活设置。
本公开的实施例的区域识别方法不仅可以用于识别热力区域，以进行选址，还可以向线下门店推荐热销商品。具体的过程可以如下所示：
接收目标区域识别请求，该目标区域识别请求包括目标区域的地址信息、目标统计指标和编码长度；其中，目标统计指标包括多个目标品类、历史销售时段以及业务指标。业务指标可以是销量、GMV等；
解析所述目标区域的地址信息，获得所述目标区域的多个目标经 纬度坐标；基于所述编码长度，分别对所述目标区域的目标经纬度坐标进行二进制编码处理，确定与每一目标经纬度坐标对应的二进制码；由所述多个目标经纬度坐标对应的多个二进制码组成地理区间；
从预设的存储单元中获取在所述地理区间内、与所述目标统计指标对应的目标特征数据；所述预设的存储单元以键值对的形式存储历史数据，所述历史数据包括历史地址和历史特征数据，所述预设的存储单元以所述历史地址对应的二进制码为键，以所述历史特征数据为键；
确定与所述编码长度对应的网格宽度和高度；
基于所述网格宽度和高度，对所述目标区域进行网格化划分；
确定与每一目标品类对应的颜色；其中，可以预先对所有品类进行颜色配置，也可以在用户定义目标区域时通过交互界面自定义各目标品类的颜色；
针对所述目标区域中的每一网格，分别对所述网格内的目标品类的目标特征数据进行聚合计算，确定所述网格内销量或成交总额最高的目标品类；
基于所述销量或成交总额最高的目标品类对应的颜色，对所述网格进行渲染，将渲染的网格作为热力区域。
本实施例可以确定目标品类的物品在目标区域的销售分布情况，可以为门店布品提供数据支持以及推荐热销商品。
本公开的实施例的区域识别方法不仅可以利用线上积累向线下引流，拓展线下渠道，以实现全渠道布局，还可以依托于定点区域数据积累，为指定门店推荐热销商品，帮助门店精准选品布货，使门店有更好的动销，形成良性循环，加强线上线下渠道布局。
图4是本公开的实施例的区域识别装置400的主要模块的示意图。如图4所示，该区域识别装置400包括：
获取模块401，用于获取区域识别请求，所述区域识别请求包括目 标区域的地址信息和目标统计指标；
转码模块402，用于解析所述目标区域的地址信息，获得所述目标区域的多个目标经纬度坐标，分别对所述目标区域的目标经纬度坐标进行二进制编码处理，确定与每一目标经纬度坐标对应的二进制码；由所述多个目标经纬度坐标对应的多个二进制码组成的地理区间；
数据查询模块403，用于从预设的存储单元中获取在所述地理区间内、与所述目标统计指标对应的目标特征数据；所述预设的存储单元以键值对的形式存储历史数据，所述历史数据包括历史地址和历史特征数据，所述预设的存储单元以所述历史地址对应的二进制码为键，以所述历史特征数据为键；
识别模块404，用于对所述目标特征数据进行计算，并基于计算结果确定所述目标区域中的热力区域。
可选地，所述区域识别请求还包括编码长度；
所述转码模块402还用于：基于所述编码长度，分别对所述目标区域的目标经纬度坐标进行二进制编码处理；
所述识别模块404还用于：确定与所述编码长度对应的网格宽度和高度；基于所述网格宽度和高度，对所述目标区域进行网格化划分；针对所述目标区域中的每一网格，对所述网格内的目标特征数据进行计算，并基于计算结果确定所述目标区域中的热力区域。
可选地，所述区域识别请求还包括热力阈值；
所述识别模块404还用于：对所述网格内的目标特征数据进行聚合计算，确定所述网格的热力值；确定热力值大于或等于所述热力阈值的网格为所述目标区域内的热力区域。
可选地，所述装置还包括选址模块，用于：获取门店选址条件；其中，所述门店选址条件包括以下一种或多种：选址目标定位要求、与路口的最大距离不大于距离阈值和在预设面积范围内；从所述热力区域中确定满足所述选址条件的网格，将满足所述选址条件的网格所 在的位置作为门店的候选地址。
可选地，所述获取模块401还用于：接收用户通过第一交互界面输入的目标区域的名称和目标统计指标；基于所述目标区域的名称和目标统计指标，生成区域识别请求。
可选地，所述获取模块401还用于：接收用户通过第二交互界面输入的目标统计指标；响应于用户在地图上的区域绘制操作，确定所述用户绘制的区域的多个经纬度坐标；
基于所述用户绘制的区域的多个经纬度坐标和所述目标统计指标，生成区域识别请求。
可选地，所述目标统计指标包括多个目标品类，所述目标特征数据为每个目标品类的目标特征数据；
所述装置还包括颜色确定模块，用于确定与每一目标品类对应的颜色；
所述识别模块404还用于：针对所述目标区域中的每一网格，分别对所述网格内的目标品类的目标特征数据进行聚合计算，确定所述网格内销量或成交总额最高的目标品类；基于所述销量或成交总额最高的目标品类对应的颜色，对所述网格进行渲染，将渲染的网格作为热力区域。
本公开的实施例的区域识别装置，利用线上数据优化区域识别能力；通过对目标区域的经纬度坐标进行编码处理，获得对应的二进制码，由二进制码组成地理区间，然后获取在该地理区间内的目标特征数据，在对经纬度坐标进行编码处理时可以针对不同的展示需求选择不同的地址编码长度，从而适应多种查询量和准确性要求，既可支持用户进行高精度到小区的查询，也可支持精度略低但覆盖范围到区县级别的查询，通过地址编码可实现高效的用户交互式查询；在识别出热力区域之后，结合选址策略，可从热力区域中确定门店候选地址， 为线下渠道拓展提供了有力的支持，不需要花费大量的人力和时间进行调研，降低了成本，且提升了效率。
上述装置可执行本公开的实施例所提供的方法，具备执行方法相应的功能模块和有益效果。未在本实施例中详尽描述的技术细节，可参见本公开的实施例所提供的方法。
图5示出了可以应用本公开的实施例的区域识别方法或区域识别装置的示例性系统架构500。
如图5所示，系统架构500可以包括终端设备501、502、503，网络504和服务器505。网络504用以在终端设备501、502、503和服务器505之间提供通信链路的介质。网络504可以包括各种连接类型，例如有线、无线通信链路或者光纤电缆等等。
用户可以使用终端设备501、502、503通过网络504与服务器505交互，以接收或发送消息等。终端设备501、502、503上可以安装有各种通讯客户端应用，例如购物类应用、网页浏览器应用、搜索类应用、即时通信工具、邮箱客户端、社交平台软件等。
终端设备501、502、503可以是具有显示屏并且支持网页浏览的各种电子设备，包括但不限于智能手机、平板电脑、膝上型便携计算机和台式计算机等等。
服务器505可以是提供各种服务的服务器，例如对用户利用终端设备501、502、503所浏览的购物类网站提供支持的后台管理服务器。后台管理服务器可以对接收到的产品信息查询请求等数据进行分析等处理，并将处理结果(例如目标推送信息、产品信息)反馈给终端设备。
需要说明的是，本公开的实施例所提供的区域识别方法一般由服务器505执行，相应地，区域识别装置一般设置于服务器505中。
应该理解，图5中的终端设备、网络和服务器的数目仅仅是示意性的。根据实现需要，可以具有任意数目的终端设备、网络和服务器。
下面参考图6，其示出了适于用来实现本公开的实施例的终端设备的计算机系统600的结构示意图。图6示出的终端设备仅仅是一个示例，不应对本公开的实施例的功能和使用范围带来任何限制。
如图6所示，计算机系统600包括中央处理单元(CPU)601，其可以根据存储在只读存储器(ROM)602中的程序或者从存储部分608加载到随机访问存储器(RAM)603中的程序而执行各种适当的动作和处理。在RAM 603中，还存储有系统600操作所需的各种程序和数据。CPU 601、ROM 602以及RAM 603通过总线604彼此相连。输入/输出(I/O)接口605也连接至总线604。
以下部件连接至I/O接口605：包括键盘、鼠标等的输入部分606；包括诸如阴极射线管(CRT)、液晶显示器(LCD)等以及扬声器等的输出部分607；包括硬盘等的存储部分608；以及包括诸如LAN卡、调制解调器等的网络接口卡的通信部分609。通信部分609经由诸如因特网的网络执行通信处理。驱动器610也根据需要连接至I/O接口605。可拆卸介质611，诸如磁盘、光盘、磁光盘、半导体存储器等等，根据需要安装在驱动器610上，以便于从其上读出的计算机程序根据需要被安装入存储部分608。
特别地，根据本公开的实施例，上文参考流程图描述的过程可以被实现为计算机软件程序。例如，本公开的实施例包括一种计算机程序产品，其包括承载在计算机可读介质上的计算机程序，该计算机程序包含用于执行流程图所示的方法的程序代码。在这样的实施例中， 该计算机程序可以通过通信部分609从网络上被下载和安装，和/或从可拆卸介质611被安装。在该计算机程序被中央处理单元(CPU)601执行时，执行本公开的系统中限定的上述功能。
需要说明的是，本公开所示的计算机可读介质可以是计算机可读信号介质或者计算机可读存储介质或者是上述两者的任意组合。计算机可读存储介质例如可以是——但不限于——电、磁、光、电磁、红外线、或半导体的系统、装置或器件，或者任意以上的组合。计算机可读存储介质的更具体的例子可以包括但不限于：具有一个或多个导线的电连接、便携式计算机磁盘、硬盘、随机访问存储器(RAM)、只读存储器(ROM)、可擦式可编程只读存储器(EPROM或闪存)、光纤、便携式紧凑磁盘只读存储器(CD-ROM)、光存储器件、磁存储器件、或者上述的任意合适的组合。在本公开中，计算机可读存储介质可以是任何包含或存储程序的有形介质，该程序可以被指令执行系统、装置或者器件使用或者与其结合使用。而在本公开中，计算机可读的信号介质可以包括在基带中或者作为载波一部分传播的数据信号，其中承载了计算机可读的程序代码。这种传播的数据信号可以采用多种形式，包括但不限于电磁信号、光信号或上述的任意合适的组合。计算机可读的信号介质还可以是计算机可读存储介质以外的任何计算机可读介质，该计算机可读介质可以发送、传播或者传输用于由指令执行系统、装置或者器件使用或者与其结合使用的程序。计算机可读介质上包含的程序代码可以用任何适当的介质传输，包括但不限于：无线、电线、光缆、RF等等，或者上述的任意合适的组合。
附图中的流程图和框图，图示了按照本公开各种实施例的系统、方法和计算机程序产品的可能实现的体系架构、功能和操作。在这点上，流程图或框图中的每个方框可以代表一个模块、程序段、或代码的一部分，上述模块、程序段、或代码的一部分包含一个或多个用于实现规定的逻辑功能的可执行指令。也应当注意，在有些作为替换的实现中，方框中所标注的功能也可以以不同于附图中所标注的顺序发 生。例如，两个接连地表示的方框实际上可以基本并行地执行，它们有时也可以按相反的顺序执行，这依所涉及的功能而定。也要注意的是，框图或流程图中的每个方框、以及框图或流程图中的方框的组合，可以用执行规定的功能或操作的专用的基于硬件的系统来实现，或者可以用专用硬件与计算机指令的组合来实现。
描述于本公开的实施例中所涉及到的模块可以通过软件的方式实现，也可以通过硬件的方式来实现。所描述的模块也可以设置在处理器中，例如，可以描述为：一种处理器包括发送模块、获取模块、确定模块和第一处理模块。其中，这些模块的名称在某种情况下并不构成对该单元本身的限定，例如，发送模块还可以被描述为“向所连接的服务端发送图片获取请求的模块”。
作为另一方面，本公开还提供了一种计算机可读介质，该计算机可读介质可以是上述实施例中描述的设备中所包含的；也可以是单独存在，而未装配入该设备中。上述计算机可读介质承载有一个或者多个程序，当上述一个或者多个程序被一个该设备执行时，使得该设备包括：
获取区域识别请求，所述区域识别请求包括目标区域的地址信息和目标统计指标；
解析所述目标区域的地址信息，获得所述目标区域的多个目标经纬度坐标，分别对所述目标区域的目标经纬度坐标进行二进制编码处理，确定与每一目标经纬度坐标对应的二进制码；由所述多个目标经纬度坐标对应的多个二进制码组成地理区间；
从预设的存储单元中获取在所述地理区间内、与所述目标统计指标对应的目标特征数据；所述预设的存储单元以键值对的形式存储历史数据，所述历史数据包括历史地址和历史特征数据，所述预设的存储单元以所述历史地址对应的二进制码为键，以所述历史特征数据为键；
对所述目标特征数据进行计算，并基于计算结果确定所述目标区 域中的热力区域。
本公开的实施例的技术方案，实现了利用线上数据优化区域识别能力；通过对目标区域的经纬度坐标进行编码处理，获得对应的二进制码，由二进制码组成地理区间，然后获取在该地理区间内的目标特征数据，在对经纬度坐标进行编码处理时可以针对不同的展示需求选择不同的地址编码长度，从而适应多种查询量和准确性要求，既可支持用户进行高精度到小区的查询，也可支持精度略低但覆盖范围到区县级别的查询，通过地址编码可实现高效的用户交互式查询；在识别出热力区域之后，结合选址策略，可从热力区域中确定门店候选地址，为线下渠道拓展提供了有力的支持，不需要花费大量的人力和时间进行调研，降低了成本，且提升了效率。
上述具体实施方式，并不构成对本公开保护范围的限制。本领域技术人员应该明白的是，取决于设计要求和其他因素，可以发生各种各样的修改、组合、子组合和替代。任何在本公开的精神和原则之内所作的修改、等同替换和改进等，均应包含在本公开保护范围之内。

Claims (10)

  1. 一种区域识别方法，其特征在于，包括：
    获取区域识别请求，所述区域识别请求包括目标区域的地址信息和目标统计指标；
    解析所述目标区域的地址信息，获得所述目标区域的多个目标经纬度坐标，分别对所述目标区域的目标经纬度坐标进行二进制编码处理，确定与每一目标经纬度坐标对应的二进制码；由所述多个目标经纬度坐标对应的多个二进制码组成地理区间；
    从预设的存储单元中获取在所述地理区间内、与所述目标统计指标对应的目标特征数据；所述预设的存储单元以键值对的形式存储历史数据，所述历史数据包括历史地址和历史特征数据，所述预设的存储单元以所述历史地址对应的二进制码为键，以所述历史特征数据为键；
    对所述目标特征数据进行计算，并基于计算结果确定所述目标区域中的热力区域。
  2. 根据权利要求1所述的方法，其特征在于，所述区域识别请求还包括编码长度；
    分别对所述目标区域的目标经纬度坐标进行二进制编码处理包括：基于所述编码长度，分别对所述目标区域的目标经纬度坐标进行二进制编码处理；
    对所述目标特征数据进行计算，并基于计算结果确定所述目标区域中的热力区域包括：
    确定与所述编码长度对应的网格宽度和高度；
    基于所述网格宽度和高度，对所述目标区域进行网格化划分；
    针对所述目标区域中的每一网格，对所述网格内的目标特征数据进行计算，并基于计算结果确定所述目标区域中的热力区域。
  3. 根据权利要求2所述的方法，其特征在于，所述区域识别请求 还包括热力阈值；
    对所述网格内的目标特征数据进行计算，并基于计算结果确定所述目标区域中的热力区域包括：
    对所述网格内的目标特征数据进行聚合计算，确定所述网格的热力值；
    确定热力值大于或等于所述热力阈值的网格为所述目标区域内的热力区域。
  4. 根据权利要求3所述的方法，其特征在于，所述方法还包括：
    获取门店选址条件；其中，所述门店选址条件包括以下一种或多种：选址目标定位要求、与路口的最大距离不大于距离阈值和在预设面积范围内；
    从所述热力区域中确定满足所述选址条件的网格，将满足所述选址条件的网格所在的位置作为门店的候选地址。
  5. 根据权利要求1所述的方法，其特征在于，获取区域识别请求包括：
    接收用户通过第一交互界面输入的目标区域的名称和目标统计指标；
    基于所述目标区域的名称和目标统计指标，生成区域识别请求。
  6. 根据权利要求1所述的方法，其特征在于，获取区域识别请求包括：
    接收用户通过第二交互界面输入的目标统计指标；
    响应于用户在地图上的区域绘制操作，确定所述用户绘制的区域的多个经纬度坐标；
    基于所述用户绘制的区域的多个经纬度坐标和所述目标统计指标，生成区域识别请求。
  7. 根据权利要求2所述的方法，其特征在于，所述目标统计指标 包括多个目标品类，所述目标特征数据为每个目标品类的目标特征数据；
    所述方法还包括：确定与每一目标品类对应的颜色；
    针对所述目标区域中的每一网格，对所述网格内的目标特征数据进行计算，并基于计算结果确定所述目标区域中的热力区域包括：
    针对所述目标区域中的每一网格，分别对所述网格内的目标品类的目标特征数据进行聚合计算，确定所述网格内销量或成交总额最高的目标品类；
    基于所述销量或成交总额最高的目标品类对应的颜色，对所述网格进行渲染，将渲染的网格作为热力区域。
  8. 一种区域识别装置，其特征在于，包括：
    获取模块，用于获取区域识别请求，所述区域识别请求包括目标区域的地址信息和目标统计指标；
    转码模块，用于解析所述目标区域的地址信息，获得所述目标区域的多个目标经纬度坐标，分别对所述目标区域的目标经纬度坐标进行二进制编码处理，确定与每一目标经纬度坐标对应的二进制码；由所述多个目标经纬度坐标对应的多个二进制码组成的地理区间；
    数据查询模块，用于从预设的存储单元中获取在所述地理区间内、与所述目标统计指标对应的目标特征数据；所述预设的存储单元以键值对的形式存储历史数据，所述历史数据包括历史地址和历史特征数据，所述预设的存储单元以所述历史地址对应的二进制码为键，以所述历史特征数据为键；
    识别模块，用于对所述目标特征数据进行计算，并基于计算结果确定所述目标区域中的热力区域。
  9. 一种电子设备，其特征在于，包括：
    一个或多个处理器；
    存储装置，用于存储一个或多个程序，
    当所述一个或多个程序被所述一个或多个处理器执行，使得所述 一个或多个处理器实现如权利要求1-7中任一所述的方法。
  10. 一种计算机可读介质，其上存储有计算机程序，其特征在于，所述程序被处理器执行时实现如权利要求1-7中任一所述的方法。
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CN113792107A (zh) * 2021-09-15 2021-12-14 北京沃东天骏信息技术有限公司 区域识别方法和装置

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CN117932133A (zh) * 2024-03-22 2024-04-26 中国电建集团西北勘测设计研究院有限公司 数据采集方法、装置、介质及设备
CN118586950A (zh) * 2024-08-02 2024-09-03 志鸿软件科技(深圳)有限公司 一种项目用地选址辅助决策方法、装置和计算机设备

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