KR102681203B1 - Electronic apparatus and method for providing information related to delivery service - Google Patents

Abstract

This disclosure relates to an electronic device and method for providing information related to delivery work. In the method of providing information related to delivery work by an electronic device according to an embodiment of the present disclosure, the method for providing information related to delivery work includes the target area ( Confirming a plurality of unit areas included in a target region, confirming characteristic information for each of the plurality of unit areas based on store information corresponding to each of the plurality of unit areas, Identifying a sub-region containing at least one unit area selected from among the plurality of unit areas based on characteristic information for each of the plurality of unit areas and generating the sub-region based on the information about the sub-region It includes providing delivery-related information to the delivery person terminal.

Description

Electronic device and method for providing delivery service-related information {ELECTRONIC APPARATUS AND METHOD FOR PROVIDING INFORMATION RELATED TO DELIVERY SERVICE}

This disclosure relates to an electronic device and method for providing information related to delivery work. More specifically, the present disclosure is an electronic device that divides a target area into a plurality of sub-areas based on past delivery history information and provides delivery-related information generated based on information corresponding to the divided sub-areas to the delivery worker terminal. and methods thereof.

Recently, the food delivery brokerage service market is expanding due to the spread of infectious diseases and the widespread use of the Internet. In food delivery brokerage services, providing quick delivery and setting low delivery costs are essential to improve the competitiveness of the service. To this end, changes in delivery demand according to time and location are accurately observed and predicted, and the supply of delivery personnel accordingly is timely. It must be done.

Currently, food delivery relay services can allocate delivery tasks based on administrative districts and provide information related to delivery tasks. However, simply providing delivery services based on administrative districts has limitations in increasing the efficiency of delivery services because it provides services without considering fluid factors such as delivery demand in the area, supply and demand of delivery personnel, store information, and customer information. .

In relation to this, prior literature such as KR1020170027177A and KR102385838B1 may be referred to.

In order to solve the above-described problems, the present disclosure aims to provide an electronic device and method for providing delivery work-related information corresponding to divided compartments based on past delivery history information.

Specifically, the purpose of the present disclosure is to divide the target area into a plurality of sub-areas based on past delivery history information and provide delivery-related information corresponding to the divided sub-areas to the delivery person terminal.

In addition, the present disclosure aims to derive sub-areas including areas with similar characteristics based on past delivery history information and provide delivery-related information reflecting the characteristics of the sub-area to the delivery person terminal.

The technical problems to be achieved by the present disclosure are not limited to the technical problems described above, and other technical problems can be inferred from the following embodiments.

In a method of providing information related to delivery work by an electronic device according to an embodiment of the present disclosure, the method of providing information related to delivery work includes the steps of identifying a plurality of unit areas included in a target region; Confirming characteristic information for each of the plurality of unit areas based on store information corresponding to each of the plurality of unit areas, the plurality of unit areas based on the characteristic information for each of the plurality of unit areas It includes the step of identifying a sub-region including at least one selected unit area and providing delivery-related information generated based on the information about the sub-region to the delivery person terminal.

As an example, characteristic information for each of the plurality of unit areas is confirmed by further considering customer information corresponding to each of the plurality of unit areas.

As an example, checking characteristic information for each of the plurality of unit areas may include checking delivery history information for each of the plurality of unit areas including the store information and the customer information and a machine learning framework. and confirming characteristic information for each of the plurality of unit areas based on delivery history information for each of the plurality of unit areas through a (machine learning framework).

As an example, the machine learning framework is a word2vec framework, and confirming characteristic information for each of the plurality of unit areas based on delivery history information for each of the plurality of unit areas. Corresponding a set of unit areas corresponding to the store information and a unit area corresponding to the customer information to a sentence, and the word-to-vector framework learned based on delivery history information for each of the plurality of unit areas It includes the step of confirming a characteristic vector value for each of the plurality of unit areas according to .

For example, the step of identifying the sub-area may include identifying a set of unit areas with similar characteristics among the plurality of unit areas based on the characteristic vector value for each of the plurality of unit areas, and the set of unit areas. and confirming the sub-area including the at least one unit area selected based on the proximity between unit areas included in the sub-area.

By way of example, the set of unit areas includes at least one unit area with the feature vector value within a threshold range.

For example, the number of sub-areas included in the target area is set by the administrator of the electronic device.

As an example, the threshold range is set corresponding to the number of sub-areas set by the administrator.

As an example, if a first unit area and a second unit area adjacent to the first unit area are identified as different sets of unit areas, then the first sub-area and the second sub-area are the first unit area and the second unit area. It is divided based on the boundary.

As an example, when adjacent unit areas for a first unit area are included in a first unit area set, and the first unit area is included in a second unit area set, the sub-area is comprised of the adjacent unit areas and the second unit area. It is formed by including 1 unit area.

For example, the delivery history information further includes at least some of delivery time information, delivery distance information, and order time information.

For example, the plurality of unit areas included in the target area are set based on at least a portion of a minimum diameter and a maximum diameter set by an administrator of the electronic device.

For example, the plurality of unit areas included in the target area are divided into a hexagon shape.

For example, the size of the sub-region is formed based on at least some of the minimum size and maximum size set by the administrator of the electronic device.

An electronic device for providing information related to delivery work according to an embodiment of the present disclosure, wherein the electronic device includes a transceiver, a memory for storing instructions, and a processor, and the processor connected to the transceiver and the memory is connected to a target area. Check a plurality of unit areas included in, check characteristic information for each of the plurality of unit areas based on store information corresponding to each of the plurality of unit areas, and determine characteristics for each of the plurality of unit areas. Based on the information, a sub-area including at least one unit area selected from among the plurality of unit areas is identified, and delivery-related information generated based on the information on the sub-area is provided to the delivery person terminal.

An electronic device and method for providing delivery work-related information according to an embodiment of the present disclosure provide delivery work-related information to a delivery person terminal based on zone information derived by reflecting past delivery history information, thereby It is possible to provide more efficient delivery work that reflects the characteristics of delivery work.

In addition, the electronic device and method for providing information related to delivery work according to an embodiment of the present disclosure can calculate an optimized delivery cost by reflecting the characteristics of delivery work for each zone, and can calculate delivery work for each zone with similar characteristics. By assigning them, you can promote more efficient management of delivery personnel.

The effects of the present disclosure are not limited to the effects described above, and other effects not mentioned may be clearly understood by those skilled in the art from the description of the claims.

1 is a diagram illustrating a system for providing information related to delivery work according to an embodiment of the present disclosure.
Figure 2 is a flowchart illustrating a method of providing information related to delivery work according to an embodiment of the present disclosure.
FIG. 3 is a diagram illustrating a method of identifying a plurality of unit areas included in a target area according to an embodiment of the present disclosure.
FIG. 4 is a flowchart illustrating a method of checking characteristic information for each of a plurality of unit areas according to an embodiment of the present disclosure.
FIG. 5 is a flowchart illustrating a method for identifying a sub-region according to an embodiment of the present disclosure.
FIG. 6 is a diagram illustrating a method for identifying a set of unit areas with similar characteristics according to an embodiment of the present disclosure.
FIG. 7 is a diagram illustrating a method of confirming a sub-area from a set of confirmed unit areas according to an embodiment of the present disclosure.
FIG. 8 is a diagram illustrating an electronic device for providing information related to delivery work according to an embodiment of the present disclosure.

Hereinafter, embodiments of the present disclosure will be described clearly and in detail so that those skilled in the art can easily practice the present invention.

The terms used in this specification are for describing embodiments and are not intended to limit the present disclosure. Unless otherwise defined, all terms (including technical and scientific terms) used in this specification may be used with meanings that can be commonly understood by those skilled in the art to which this disclosure pertains. It may vary depending on the intentions or precedents of engineers working in the field, the emergence of new technologies, etc.

Additionally, terms defined in commonly used dictionaries are not to be interpreted ideally or excessively unless clearly specifically defined. In certain cases, there are terms arbitrarily selected by the applicant, and in this case, the meaning will be described in detail in the relevant description section. Therefore, the terms used in this disclosure should be defined based on the meaning of the term and the overall content of this disclosure, rather than simply the name of the term.

Throughout this specification, when a part “includes” a certain component, this does not mean that other components are excluded, but may further include other components, unless specifically stated to the contrary. Additionally, as used herein, the singular form also includes the plural form unless specifically stated otherwise in the phrase. In addition, the expression “at least one of a, b, and c” described throughout the specification means ‘a alone’, ‘b alone’, ‘c alone’, ‘a and b’, ‘a and c’, ‘b and c', or 'all of a, b, and c'.

Meanwhile, terms such as “first and/or second” used in this specification may be used to describe various components, but are only used for the purpose of distinguishing one component from other components. It is not intended to be limited to the components referred to by that term. For example, without departing from the scope of the present invention, a first component may be named a second component, and the second component may also be named a first component.

In addition, “…” described in this specification. wealth", "… Terms such as “module” refer to a unit that processes at least one function or operation, which may be implemented as hardware or software, or as a combination of hardware and software. Additionally, embodiments of the present disclosure may be represented by functional block configurations and various processing steps. These functional blocks may be implemented in various numbers of hardware or/and software configurations that execute specific functions. For example, embodiments of the present disclosure include memory, processing, logic, look-up tables, etc. that can execute various functions under the control of one or more microprocessors or other control devices. Direct circuit configurations can be employed.

Similar to the fact that the components disclosed herein can be implemented as software programming or software elements, embodiments of the present disclosure include various algorithms implemented as combinations of data structures, processes, routines or other programming constructs, including: It can be implemented in a programming or scripting language such as C, C++, Java, assembler, etc. Functional aspects may be implemented as algorithms running on one or more processors. Additionally, the present embodiment may employ prior art for at least one of electronic environment setting, signal processing, and data processing. Terms such as “mechanism,” “element,” “means,” and “configuration” are broadly used. It can be used and is not limited to mechanical and physical components. The term may include the meaning of a series of software routines in connection with a processor, etc.

Each block of the processing flow diagrams attached to this specification and combinations of the flow diagram diagrams may be performed by computer program instructions. These computer program instructions can be mounted on a processor of a general-purpose computer, special-purpose computer, or other programmable data processing equipment, so that the instructions performed through the processor of the computer or other programmable data processing equipment are described in the flow chart block(s). It creates the means to perform functions.

These computer program instructions may be stored in computer-usable or computer-readable memory that can be directed to a computer or other programmable data processing equipment to implement a function in a particular manner. The instructions stored in may also produce manufactured items containing instruction means that perform the functions described in the flow diagram block(s).

Computer program instructions can also be mounted on a computer or other programmable data processing equipment, so that a series of operational steps are performed on the computer or other programmable data processing equipment to create a process that is executed by the computer, thereby generating a process that is executed by the computer or other programmable data processing equipment. Instructions that perform processing equipment may also provide steps for executing the functions described in the flow diagram block(s).

Additionally, each block may represent a module, segment, or portion of code that includes one or more executable instructions for executing specified logical function(s). Additionally, in some alternative execution examples, it may be possible for the functions mentioned in the blocks to occur out of order. For example, it is possible for two blocks shown in succession to be performed substantially at the same time, or it is possible for the blocks to be performed in reverse order depending on the corresponding function.

The “electronic device” or “terminal” referred to in this specification may be implemented as a computer or portable terminal that can connect to a server or other terminal through a network. Here, the computer includes, for example, a laptop, desktop, laptop, etc. equipped with a web browser, and the portable terminal is, for example, a wireless communication device that guarantees portability and mobility. , all types of communication-based terminals such as IMT (International Mobile Telecommunication), CDMA (Code Division Multiple Access), W-CDMA (W-Code Division Multiple Access), and LTE (Long Term Evolution), smartphones, tablet PCs, etc. It may include a handheld-based wireless communication device. In addition, the "electronic device" or "terminal" referred to in this specification includes a processor, memory for storing and executing program data, permanent storage such as a disk drive, a communication port for communicating with an external device, a touch panel, User interface devices such as keys, buttons, etc. may also be included.

In the present disclosure, methods implemented as software modules or algorithms may be stored on a computer-readable recording medium as computer-readable codes or program instructions executable on a processor. Here, computer-readable recording media include magnetic storage media (e.g., ROM (read-only memory), RAM (random-access memory), floppy disk, hard disk, etc.) and optical read media (e.g., CD-ROM). ), DVD (Digital Versatile Disc), etc. Computer-readable recording media can be distributed and executed on networked computer systems.

Hereinafter, various embodiments of the present disclosure will be described in detail with reference to the attached drawings. In describing the embodiments, description will be omitted for technical content that is well known in the technical field to which the present invention belongs and that is not directly related to the present invention. This is to convey the gist of the present invention more clearly without obscuring it by omitting unnecessary explanation. For the same reason, some components are exaggerated, omitted, or schematically shown in the accompanying drawings. Additionally, the size of each component does not entirely reflect its actual size. In this specification, the same reference numerals throughout may refer to the same or corresponding elements.

1 is a diagram illustrating a system 10 for providing information related to delivery work according to an embodiment of the present disclosure. Referring to FIG. 1, the system 10 for providing information related to delivery work according to an embodiment of the present disclosure may include an electronic device 110 and a delivery person terminal 120, and the electronic device 110 and the delivery person The terminals 120 can communicate with each other and exchange information through the network 130.

By way of example, the network 130 may include a personal area network (PAN), a local area network (LAN), a campus area network (CAN), a metropolitan area network (MAN), a wide area network (WAN), a broad band network (BBN), It may include at least one network among the Internet. Additionally, the network 130 may include at least one of network topologies including a bus network, star network, ring network, mesh network, star-bus network, tree, or hierarchical network. In an embodiment of the present disclosure, the mutual communication method between the electronic device 110 and the delivery person terminal 120 is not limited to the type of network described above, and is not limited to a communication method utilizing a communication network that the network may include, as well as a short distance communication method between devices. Wireless communications may also be included.

In an embodiment of the present disclosure, the electronic device 110 may include a transceiver, memory, and processor. Additionally, the electronic device 110 refers to a unit that processes at least one function or operation, and may be implemented with hardware, software, or a combination of hardware and software. In an embodiment, the electronic device 110 may include multiple computer systems or computer software implemented as a network server. As an example, the electronic device 110 is a computer that is connected to a lower-level device that can communicate with another network server through a computer network such as an intranet or the Internet, receives a request to perform a task, performs the task, and provides a performance result. It can refer to systems and computer software.

In addition, the electronic device 110 can be understood as a broad concept that includes a series of application programs that can operate on a network server and various databases built therein. For example, the electronic device 110 uses a network server program provided in various ways depending on the operating system, such as DOS, Windows, Linux, Unix, or MacOS. This can be implemented.

The electronic device 110 can provide services by organizing various information into pages. For example, the service provided by the electronic device 110 may be a food delivery relay service. Although not shown, the electronic device 110 can provide food information and store information relayed through the service to the user terminal through a network, and perform delivery tasks to the delivery person terminal 120 based on order information obtained from the user terminal. Relevant information can be provided. Delivery task-related information provided from the electronic device 110 to the delivery person terminal 120 may include at least some of delivery task occurrence information, food pickup location information, food delivery location information, and delivery cost information.

The electronic device 110 may provide the delivery person terminal 120 with location information obtained from the delivery person terminal 120 and delivery work-related information for the corresponding area. According to an embodiment of the present disclosure, the electronic device 110 may generate section information for delivery task allocation for more efficient delivery work processing, and the section information generated according to an embodiment of the present disclosure is based on administrative district. It may be different from compartment information. The electronic device 110 may generate compartment information for delivery task allocation based on past delivery history information. The division information derived from the electronic device 110 divides the target area into a plurality of sub-regions by considering the characteristic information of each of a plurality of unit areas included in the target region based on past delivery history information. It can be created by dividing into (sub regions).

The system 10 for providing delivery work-related information according to an embodiment of the present disclosure provides delivery work-related information to the delivery worker terminal 120 based on zone information derived by reflecting past delivery history information, for each zone. It is possible to provide more efficient delivery work that reflects the characteristics of the delivery work that occurs. In addition, optimized delivery costs can be calculated by reflecting the delivery work characteristics of each zone, and delivery work can be assigned to zones with similar characteristics to promote more efficient delivery man management. A more detailed description of the method of providing delivery work-related information based on compartment information derived according to an embodiment of the present disclosure will be described later with reference to FIGS. 2 to 8.

Figure 2 is a flowchart illustrating a method of providing information related to delivery work according to an embodiment of the present disclosure.

In step S210, the electronic device 110 according to an embodiment of the present disclosure may identify a plurality of unit areas included in the target area. In an embodiment, the target area may be an area for which section information is to be generated, or may be a specific area in an administrative district selected by the manager of the electronic device 110. Specifically, the target area may be a city-level area or a district-level area in the administrative district. The manager of the electronic device 110 may set information related to the unit area included in the target area, and the information related to the unit area may include at least some of the shape information of the unit area and the size information of the unit area. The method of identifying a plurality of unit areas included in the target area will be explained in more detail with reference to FIG. 3, which will be described later.

In step S220, the electronic device 110 according to an embodiment of the present disclosure may check characteristic information for each of a plurality of unit areas included in the target area. When checking characteristic information for each of the plurality of unit areas, the electronic device 110 may consider store information included in each of the plurality of unit areas and customer information corresponding to each of the plurality of unit areas. Additionally, when checking characteristic information for each of a plurality of unit areas, the electronic device 110 may additionally consider delivery history information including at least some of delivery time information, delivery distance information, and order time information.

The electronic device 110 according to an embodiment of the present disclosure provides characteristic information for each of a plurality of unit areas using a machine learning framework based on delivery history information for each of the plurality of unit areas. You can check it. In an embodiment, the electronic device 110 may use the word2vec framework for natural language processing. The word-to-vector framework can express words as numerical vectors, and through word embedding operations, it can detect words with similarities through operations between vectorized words, or predict the optimal word at a specific position in a sentence. You can. The electronic device 110 according to an embodiment of the present disclosure may derive characteristic information by expressing delivery history information corresponding to each of a plurality of unit areas as a numerical vector based on the above-described characteristics of word-to-vector. A method of deriving characteristic information for each of a plurality of unit areas according to an embodiment of the present disclosure will be described in detail with reference to FIG. 4 to be described later.

Meanwhile, in the embodiment, the word-to-vector framework is an example, and other frameworks can be used to derive the similarity for each unit area. As an example, based on the delivery history information previously performed within the service, information on the unit area where the store for each delivery is located and information on the unit area where the customer is located are acquired, and the information on each delivery is used as learning data to build on this. The similarity of each unit area can be derived. In this way, by performing machine learning based on a pair of unit areas corresponding to the store included in the delivery and unit areas corresponding to the customer, the similarity of the unit areas related to the delivery can be determined to be high, and through this, areas with similar delivery characteristics can be selected. By clustering together, it is possible to manage delivery information more efficiently when setting delivery-related information differently for each region.

In step S230, the electronic device 110 according to an embodiment of the present disclosure may identify a divided sub-area based on characteristic information for each of a plurality of unit areas. The electronic device 110 identifies a set of unit areas with similar characteristics based on characteristic information for each of a plurality of unit areas, and additionally considers the proximity between unit areas based on the set of unit areas to determine at least one sub-area. can confirm. A method of identifying at least one sub-area included in a target area according to an embodiment of the present disclosure will be described in detail with reference to FIG. 5, which will be described later.

In step S240, the electronic device 110 according to an embodiment of the present disclosure may provide delivery-related information for the first sub-area corresponding to the location of the delivery person based on the location information acquired from the delivery person terminal 120. . In an embodiment, the delivery-related information provided to the delivery person terminal 120 may be generated based on information about the first sub-area corresponding to the location of the delivery person, and specifically, delivery work occurrence information, food pickup location information, and food It may include at least part of delivery address information and delivery cost information. Additionally, in some embodiments, the electronic device 110 may additionally provide delivery-related information about the second to Nth sub-areas adjacent to the first sub-area corresponding to the location of the delivery person to the delivery person's terminal 120.

FIG. 3 is a diagram illustrating a method of identifying a plurality of unit areas included in a target area according to an embodiment of the present disclosure. The electronic device 110 according to an embodiment of the present disclosure can identify a plurality of unit areas included in the target area, and settings for each of the plurality of unit areas can be obtained from the administrator of the electronic device 110. Settings for each of the plurality of unit areas may include settings for at least some of the shape of the unit area, the minimum diameter of the unit area, the maximum diameter of the unit area, and the number of unit areas included in the target area.

In FIG. 3, the shape of the unit area is shown in a hexagon shape, but this is only an example according to the present disclosure and does not limit the shape of the unit area identified according to the embodiment of the present disclosure. In another embodiment, the shape for the unit area may be triangular or square. In addition, in FIG. 3, the shape of each of the plurality of unit areas is shown as being set in a unified manner, but this is also only one embodiment according to the present disclosure. In another embodiment, the shape of each of the plurality of unit areas is It can be set in multiple forms. It may be set in any shape that can cover all spots included in the target area. For example, a plurality of unit areas may be set in a mixture of hexagon shapes and triangle shapes.

Additionally, the electronic device 110 may identify a plurality of unit areas for the target area by considering at least some of the minimum diameter of the unit area and the maximum diameter of the unit area. In an embodiment, when the minimum diameter is set, a plurality of unit areas Each of the unit areas may be identified as a polygonal shape having a diameter equal to or greater than the minimum diameter, and when the maximum diameter is set, each of the plurality of unit regions may be identified as a polygonal shape having a diameter equal to or less than the maximum diameter. Each of the plurality of unit areas identified from the electronic device 110 may be arranged regardless of the division in the administrative district. Additionally, in this specification, adjacent unit areas may mean unit areas that are adjacent on one side, such as the first unit area (UA_1) and the second unit area (UA_2).

Additionally, in an embodiment, a plurality of unit areas may be confirmed based on a setting for the number of unit areas included in the target area set by the administrator of the electronic device 110. For example, if the size of the target area is 100 and the number of a plurality of unit areas set by the administrator is 10, the electronic device 10 derives 10 unit areas of a random shape with a size of 10 and uses them as the target. It can be placed relative to the region.

FIG. 4 is a flowchart illustrating a method of checking characteristic information for each of a plurality of unit areas according to an embodiment of the present disclosure.

In step S410, the electronic device 110 according to an embodiment of the present disclosure may check delivery history information for each of the plurality of unit areas identified in step S210 described above. In an embodiment, the delivery history information may include store information included in each of the plurality of unit areas and customer information corresponding to each of the plurality of unit areas, and may include delivery tasks performed in the past in each of the plurality of unit areas. It may further include some of related delivery time information, delivery distance information, and order time information.

In step S420, the electronic device 110 according to an embodiment of the present disclosure may map detailed information included in delivery history information. Specifically, the electronic device 110 can map store information and customer information to words, and map delivery-related information delivered from the store to the customer to sentences, for natural language processing using a machine learning framework. there is.

In step S430, the electronic device 110 according to an embodiment of the present disclosure may check the feature vector value through a machine learning framework based on the mapping result corresponding to each of the plurality of unit areas. A machine learning framework for deriving feature vector values can be learned based on delivery history information. In some embodiments, the machine learning framework used to derive feature vector values may be a word-to-vector framework. In an embodiment of the present disclosure, the electronic device 110 may derive a characteristic vector value corresponding to each of a plurality of unit areas, and characteristic information for each of the plurality of unit areas may be generated for each of the plurality of unit areas. May include derived feature vector values. Meanwhile, for convenience of explanation, it has been explained that the characteristic information about unit areas is expressed as vector values, but the present invention is not limited to this, and characteristic information in various expression formats that can compare the similarity of each unit area can be used.

FIG. 5 is a flowchart illustrating a method for identifying a sub-region according to an embodiment of the present disclosure.

In step S510, the electronic device 110 according to an embodiment of the present disclosure may check the error range for the feature vector value. The error range for feature vector values may mean the range of feature vector values that can be confirmed to have similar characteristics. In an embodiment, the error range for the feature vector value may be confirmed differently depending on the number of sub-regions set by the administrator of the electronic device 110. Specifically, when the number of sub-areas included in the target area set by the administrator of the electronic device 110 is relatively small, the error range for the characteristic vector value, which is a standard for determining the similar range, may be large, and the electronic device ( If the number of sub-regions included in the target region set by the manager of 110) is relatively large, the error range for the feature vector value may be small.

Meanwhile, although the error range is explained in the embodiment, a unit area corresponding to a vector value within a specific range can be judged as a similar area. If the vector value for the characteristic information of each unit area is within a certain distance in space, each unit area can be clustered together, where the error range may be the distance range in the vector space for clustering in this way. Meanwhile, in the embodiment, the distance range of clustering may vary for each cluster. For example, in areas with a high delivery volume, the range of distances between vector spaces for clustering may be short, and in areas with a high delivery volume, the range of distances between vector spaces for clustering may be relatively long. In this way, depending on the characteristics of the region for clustering, the degree of similarity between each unit area may be judged using different criteria.

For example, if the target area is set to be divided into 10 sub-areas by the manager of the electronic device 110, the error range for the characteristic vector value can be confirmed on a relatively rough basis, and the target area If it is set to divide into 100 sub-regions, the error range for the feature vector value can be confirmed with a relatively tight standard. That is, the error range for the feature vector value may be flexible depending on the number of sub-regions to be distinguished, and based on the range for the feature vector value for each of the plurality of unit vectors derived by the electronic device 110, It can be confirmed.

In step S520, the electronic device 110 according to an embodiment of the present disclosure may identify a set of unit areas having similar characteristics. The set of unit areas having similar characteristics may include at least one unit area having a characteristic vector value within the error range confirmed in step S510 described above. The number of at least one unit zone included in the unit zone set is not limited. According to an embodiment of the present disclosure, a method of identifying a unit zone set will be described in detail with reference to FIG. 6 to be described later.

In step S530, the electronic device 110 according to an embodiment of the present disclosure may check the sub-area by considering the proximity between unit areas based on the confirmation result for the unit area set. The sub-area can be confirmed based on the unit area set derived in step S520, but if at least one unit area included in the unit area set is not adjacent, the electronic device 110 determines whether the unit area includes a sub-area. You can judge. Whether or not some unit area includes a sub-area may be determined by considering the characteristic information of the unit area and adjacent unit areas. According to an embodiment of the present disclosure, a method for identifying a sub-area will be described in detail with reference to FIG. 7, which will be described later.

FIG. 6 is a diagram illustrating a method for identifying a set of unit areas with similar characteristics according to an embodiment of the present disclosure. Figure 6 shows the results of classifying a plurality of unit areas into seven unit area sets. The electronic device 110 according to an embodiment of the present disclosure may classify feature vector values based on the error range identified in step S510, and divide at least one unit zone corresponding to the classified feature vector value into a unit zone set. You can check it.

Specifically, in FIG. 6, when the feature vector value for each of a plurality of unit areas has a range of 0 to 7 and the confirmed error range is 1, at least one feature vector value has a feature vector value of 0 to 1. A unit area is set as a first unit area set, at least one unit area with a characteristic vector value of 1 or more and less than 2 is a second unit area set, and at least one unit area with a characteristic vector value of 6 or more and less than 7 is provided. It can be identified as a set of 7 units. Expressing feature vector values in numbers is intended to aid understanding of the present disclosure, and in implementing the present disclosure, feature vector values may have size, direction, and dimension. Meanwhile, in the embodiment, the numerical values included in the vector values are described arbitrarily, but this is not limited to this, and the values of the numerical values corresponding to the sub-characteristic information that constitutes each characteristic information can be normalized and determined, even if the vector values have the same size. Depending on the configuration of the sub-characteristic information, the direction of the corresponding vector may vary between vector spaces.

FIG. 7 is a diagram illustrating a method of confirming a sub-area from a set of confirmed unit areas according to an embodiment of the present disclosure.

The electronic device 110 according to an embodiment of the present disclosure may identify a sub-area based on a unit area set. Since the unit area set includes at least one unit area with similar characteristics, the boundary of the sub-area may be formed according to the boundary of the unit area set. In Figure 7, the first unit area (UA_1) is included in the second unit area set, the second unit area (UA_2) is included in the third unit area set, and the second unit area set and the third unit area set are Since they are classified into different sets of unit areas, sub-areas may be formed by considering the boundaries of the first unit area (UA_1) and the second unit area (UA_2).

In addition, in FIG. 7, the unit areas included in the first unit area set form two clusters, but the electronic device 110 considers the proximity of the two clusters to perform more efficient delivery work, and divides the unit areas into two sub-clusters. Regions can be formed. Meanwhile, the third unit area (UA_3) is included in the fourth unit area set, but all unit areas adjacent to the third unit area (UA_3) are included in the third unit area set, and some of the unit areas included in the third unit area set Since the unit areas form a cluster, the electronic device 110 according to an embodiment of the present disclosure may include some units included in the third unit area set even if the third unit area UA_3 is not included in the third unit area set. A first sub-region (SR_1) may be formed by including the regions.

The number of sub-regions shown in FIG. 7 is 20, but this does not limit the number of sub-regions formed according to the embodiment of the present disclosure, and the number of sub-regions dividing the target area is determined by the number of sub-regions of the electronic device 110. Can be set by the administrator. In addition, at least one of the minimum and maximum sizes of the sub-regions dividing the target area may be set by the administrator of the electronic device 110, and the minimum number of unit areas and the maximum number of unit areas included in one sub-area may also be set. can be set. The electronic device 110 according to an embodiment of the present disclosure may identify a sub-area that divides the target area based on setting information obtained from the administrator.

FIG. 8 is a diagram illustrating an electronic device 110 for providing information related to delivery work according to an embodiment of the present disclosure. Referring to FIG. 8, the electronic device 110 according to an embodiment of the present disclosure may include a transceiver 810, a processor 820, and a memory 830.

The electronic device 110 is connected to an external terminal through the transceiver 810 and can exchange data. As an example, the electronic device 110 may be connected to the deliveryman terminal 120 through the transceiver 810.

The processor 820 may include at least one device described above with reference to FIGS. 1 to 7 or may store information for performing at least one method described with reference to FIGS. 1 to 7 . Additionally, the processor 820 may execute a program and control the electronic device 110 to provide information related to delivery work.

Memory 830 may be volatile memory or non-volatile memory. Additionally, the memory 830 may store the code of a program executed by the processor 820. Meanwhile, although not shown, the electronic device 110 may further include an interface for providing information from the electronic device 110 to an external terminal.

The above-described contents are specific embodiments for carrying out the present disclosure. The present disclosure will include not only the above-described embodiments, but also embodiments that are simply designed or can be easily changed. Additionally, the present disclosure will also include technologies that can be easily modified and implemented using the above-described embodiments. Therefore, the scope of the present disclosure should not be limited to the above-described embodiments, but should be determined by the claims and equivalents of the present disclosure as well as the claims described later.

Claims (15)

In a method of providing information related to delivery work by electronic device,
Identifying a plurality of unit areas included in a target region;
Confirming characteristic information for each of the plurality of unit areas based on delivery history information including store information and customer information corresponding to each of the plurality of unit areas;
identifying a sub-region including at least one unit area selected from among the plurality of unit areas based on characteristic information for each of the plurality of unit areas; and
Comprising the step of providing delivery-related information generated based on the information about the sub-area to the delivery person terminal,
The step of checking characteristic information for each of the plurality of unit areas includes determining a characteristic vector value for each of the plurality of unit areas according to the word2vec framework based on the delivery history information. Including the step of obtaining,
The step of checking the sub-area is,
Confirming setting information on the number of sub-areas to be included in the target area and information on the delivery volume of the target area;
determining an error range for a feature vector value based on the setting information and the information about the delivery quantity;
determining at least one unit area having a feature vector value within the determined error range as a unit area set; and
Comprising the step of determining the sub-area based on the proximity between unit areas included in the unit area set,
The error range is determined to be larger as the number of sub-regions decreases or the delivery volume decreases,
The word-to-vector framework is a method of providing delivery work-related information included in a machine learning framework for confirming characteristic information for each of the plurality of unit areas based on the delivery history information.
delete delete According to claim 1,
The step of obtaining a feature vector value for each of the plurality of unit areas includes:
A method of providing information related to delivery work, comprising the step of matching a set of unit areas corresponding to the store information and a set of unit areas corresponding to the customer information to a sentence.
delete delete delete delete According to clause 4,
If a first unit area and a second unit area adjacent to the first unit area are identified as different sets of unit areas, the first sub-area and the second sub-area define the boundaries of the first unit area and the second unit area. Methods of providing information related to delivery work classified based on.
According to clause 4,
When adjacent unit areas to a first unit area are included in a first unit area set, and the first unit area is included in a second unit area set, the sub-area is comprised of the adjacent unit areas and the first unit area. Method of providing information related to delivery work, including.
According to claim 1,
The delivery history information may further include at least some of delivery time information, delivery distance information, and order time information.
According to claim 1,
A method of providing information related to delivery work, wherein the plurality of unit areas included in the target area are set based on at least a portion of a minimum diameter and a maximum diameter set by an administrator of the electronic device. According to claim 1,
A method of providing information related to delivery work in which the plurality of unit areas included in the target area are divided into a hexagon shape. According to claim 1,
A method of providing information related to delivery work, wherein the size of the sub-area is formed based on at least a portion of a minimum size and a maximum size set by an administrator of the electronic device. An electronic device for providing information related to delivery work,
Includes a transceiver, memory for storing instructions, and a processor;
The processor connected to the transceiver and the memory,
Identify a plurality of unit areas included in the target region,
Confirming characteristic information for each of the plurality of unit areas based on delivery history information including store information and customer information corresponding to each of the plurality of unit areas,
Identifying a sub-region containing at least one unit area selected from among the plurality of unit areas based on characteristic information for each of the plurality of unit areas,
Provide delivery-related information generated based on information about the sub-area to the delivery person terminal,
When checking the characteristic information for each of the plurality of unit areas, obtain a characteristic vector value for each of the plurality of unit areas according to the word2vec framework based on the delivery history information, and ,
When checking the above sub-area,
Confirm setting information regarding the number of sub-areas to be included in the target area and information regarding the delivery volume of the target area,
Based on the setting information and the information about the delivery quantity, determine an error range for the feature vector value,
Determining at least one unit area having a feature vector value within the determined error range as a unit area set,
Determining the sub-area based on the proximity between unit areas included in the unit area set,
The error range is determined to be larger as the number of sub-regions decreases or the delivery volume decreases,
The word-to-vector framework is an electronic device included in a machine learning framework for confirming characteristic information for each of the plurality of unit areas based on the delivery history information.

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