KR102448463B1 - Electronic apparatus for processing delivery-related information and method thereof - Google Patents

Abstract

According to the present disclosure, disclosed is a method for processing information in an electronic apparatus to provide an item delivery service, which includes the steps of: obtaining at least one adding input to a shopping cart; obtaining expected order information corresponding to the at least one adding input to the shopping cart based on one of at least one piece of information that the at least one adding input to the shopping cart includes; determining at least one candidate deliverer based on the expected order information and at least one piece of store information that the at least one adding input to the shopping cart includes; and providing the expected order information to the at least one candidate deliverer.

Description

ELECTRONIC APPARATUS FOR PROCESSING DELIVERY-RELATED INFORMATION AND METHOD THEREOF

The present disclosure relates to an electronic device and method for processing delivery related information. More specifically, the present disclosure relates to a method of obtaining a shopping cart addition input, obtaining expected order information corresponding to the shopping cart addition input based on the input, and providing it to one or more candidate delivery agents, and an electronic device using the same.

As the use of the Internet becomes common, the e-commerce market is expanding. In particular, with the spread of infectious diseases, interest in e-commerce/online purchase where non-face-to-face product purchases are possible is rapidly increasing. This trend has a positive impact on the food delivery market, and food delivery services based on customer terminals such as smartphones are becoming very active.

In the delivery food service, speed delivery to maintain freshness and warmth is particularly important compared to delivery of general items. Therefore, the delivery person arrives at the store in advance before completing the cooking of the ordered food at the store (e.g. restaurant), or by arriving at the store as soon as possible after the ordered food is cooked, the ordered food is delivered to the customer quickly. Needs to be.

On the other hand, delivery food service tends to concentrate delivery work at specific times (e.g. universal meal times) and specific locations (e.g. densely populated areas) due to its characteristics. If it is not located nearby, delivery efficiency may decrease and delivery may be delayed.

This problem may be the same for a variety of items that require expedited delivery in addition to food (e.g. flowers, parcels ordered for expedited delivery, etc.).

In this regard, reference may be made to prior documents such as KR101870190B1 gun or KR20050108168A gun.

The problem to be solved by this embodiment is to obtain one or more shopping cart addition inputs including store information and item information, respectively, and to at least one of the one or more information included in the one or more shopping cart addition inputs in order to solve the above-mentioned problems. based on obtaining expected order information corresponding to the one or more shopping cart addition inputs, determining one or more candidate shipping sources based on the expected order information and one or more store information included in the one or more shopping cart addition inputs, and one or more candidate shipments An electronic device and method for providing expected order information to a circle are provided.

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

According to an embodiment, a method for processing information in an electronic device providing an item delivery service includes: obtaining one or more shopping cart addition inputs, wherein the one or more shopping cart addition inputs include store information and item information, respectively; obtaining expected order information corresponding to the one or more shopping cart addition inputs, based on at least one of the one or more pieces of information included in the one or more shopping cart addition inputs; determining one or more candidate delivery sources based on the expected order information and one or more store information included in the one or more shopping cart addition inputs; and providing the expected order information to the one or more candidate delivery agents.

According to an embodiment, the obtaining of the expected order information may include: obtaining probability information including a result of calculating a probability value of converting into an actual order with respect to at least a portion of the one or more shopping cart addition inputs; and obtaining the expected order information based on the probability information.

According to one embodiment, the obtaining of the probability information may include: classifying at least some of the one or more shopping cart addition inputs into one or more groups based on one or more store information included in the one or more shopping cart addition inputs; and calculating a probability of conversion to an actual order for each of the one or more groups, respectively.

According to an embodiment, the one or more groups are set for each specific regional range, and the classifying into the one or more groups includes location information for one or more stores included in the one or more store information and corresponding to the one or more groups. The method may include classifying at least a portion of the one or more shopping cart addition inputs into the one or more groups based on a result of comparing regional ranges.

According to an embodiment, the acquiring of the probability information may include: determining an order history for each store corresponding to the one or more store information, based on one or more store information included in the one or more shopping cart addition inputs; and obtaining the probability information based on the order history.

According to an embodiment, in the determining of the order history for each store, for at least a part of the one or more shopping cart addition inputs, an item corresponding to the item information included in the specific shopping cart input is store information that the specific shopping cart input includes. and determining a history of ordering from a store corresponding to .

According to an embodiment, the acquiring of the probability information may include: determining an order history for each user corresponding to the one or more shopping cart addition inputs; and obtaining the probability information based on the order history.

According to an embodiment, the obtaining of the expected order information based on the probability information may include: for each one or more probability values included in the probability information, the number of shopping cart addition inputs corresponding to the corresponding probability value and the corresponding probability value. multiplying; and generating the order expected value information based on a result of the multiplication operation.

According to an embodiment, the determining of the one or more candidate delivery sources may include: determining one or more location information corresponding to the expected order information based on the one or more store information; and obtaining information on one or more delivery sources located in a certain radius range based on the one or more location information.

According to an embodiment, the determining of the one or more candidate delivery sources may include: determining whether the one or more delivery sources can be assigned the actual order when an actual order corresponding to the expected order information occurs; and determining the one or more candidate delivery sources among the one or more delivery sources based on a result of determining whether the actual order can be assigned.

According to an embodiment, determining whether the actual order can be assigned may include: determining whether the one or more delivery sources are in a delivery available state; determining whether a movement path from the location of the one or more delivery sources to one or more locations corresponding to the expected order information satisfies a preset condition; determining information on the transportation means used by the one or more delivery personnel; And when the actual order occurs, it may include at least one of determining whether the time to allocate the actual order is included in a preset time interval.

According to an embodiment, the providing of the expected order information may include providing a page including a map displaying the expected order information to the one or more candidate delivery agents.

According to an embodiment, the map displaying the expected order information may be displayed based on coordinate information generated based on a result of determining the density of expected orders for each predetermined regional range.

According to an embodiment, the providing of the expected order information may include proposing to the one or more candidate delivery agents to move to one or more locations corresponding to the expected order information.

According to an embodiment, the information processing method may further include requesting the store to prepare an item based on the expected order information.

An electronic device for processing information to provide an item delivery service according to an embodiment includes a transceiver, a memory for storing instructions, and a processor, wherein the processor is connected to the transceiver and the memory to input one or more shopping cart additions and - the one or more shopping cart addition inputs include store information and item information, respectively; based on at least one of one or more pieces of information included in the one or more shopping cart addition inputs, corresponding to the one or more shopping cart addition inputs Obtain expected order information, determine one or more candidate delivery sources based on the expected order information and one or more store information included in the one or more shopping cart addition inputs, and provide the expected order information to the one or more candidate delivery sources do.

Specific details of other embodiments are included in the detailed description and drawings.

According to the present disclosure, an electronic device and method for processing delivery-related information predict the occurrence of future orders based on a shopping cart addition input and provide the prediction results to one or more candidate delivery agents, thereby providing demand for delivery services and delivery services can narrow the gap between the supply of Through this, since the delivery person can move in advance to an area where a lot of delivery orders are expected, the gap between the time when the item is ready and the time when the delivery person arrives at the store to pick up the item is reduced, thereby performing fast and timely delivery and can handle more shipping tasks.

Effects of the invention are not limited to the effects mentioned above, and other effects not mentioned will be clearly understood by those skilled in the art from the description of the claims.

1 is a schematic configuration diagram illustrating a system for processing delivery-related information according to an embodiment.
2 is an operation flowchart of a delivery order processing method of an electronic device in a system for processing delivery-related information according to an exemplary embodiment.
3 is a diagram for explaining an operation of classifying at least a portion of one or more shopping cart addition inputs into one or more groups according to an exemplary embodiment.
4 is a diagram for illustratively explaining an operation of determining a candidate delivery source according to an embodiment.
5 is a diagram for illustratively explaining a result of determining whether a delivery person can receive an actual order according to an embodiment;
6 is a view for explaining a map for displaying expected order information according to an exemplary embodiment.
7 is an operation flowchart of an information processing method of an electronic device according to an exemplary embodiment.
8 is a diagram illustrating a configuration of an electronic device for processing delivery related information according to an embodiment.

Terms used in the embodiments are selected as currently widely used general terms as possible while considering functions in the present disclosure, but may vary depending on intentions or precedents of those of ordinary skill in the art, emergence of new technologies, and the like. In addition, in certain cases, there are also terms arbitrarily selected by the applicant, and in this case, the meaning will be described in detail in the corresponding description. Therefore, the terms used in the present disclosure should be defined based on the meaning of the term and the contents of the present disclosure, rather than the simple name of the term.

In the entire specification, when a part “includes” a certain component, it means that other components may be further included, rather than excluding other components, unless otherwise stated. In addition, terms such as “…unit” and “…module” described in the specification mean a unit that processes at least one function or operation, which is implemented as hardware or software, or a combination of hardware and software. can be

The expression “at least one of a, b, and c” described throughout the specification is, 'a alone', 'b alone', 'c alone', 'a and b', 'a and c', 'b and c ', or 'all of a, b, and c'.

The "terminal" referred to below may be implemented as a computer or a portable terminal capable of accessing a server or other terminal through a network. Here, the computer includes, for example, a laptop, a desktop, and a laptop equipped with a web browser (WEB Browser), and the portable terminal is, for example, a wireless communication device that ensures portability and mobility. , IMT (International Mobile Telecommunication), CDMA (Code Division Multiple Access), W-CDMA (W-Code Division Multiple Access), LTE (Long Term Evolution) and other communication-based terminals, smartphones, tablet PCs, etc. It may include a handheld-based wireless communication device.

Hereinafter, with reference to the accompanying drawings, embodiments of the present disclosure will be described in detail so that those of ordinary skill in the art to which the present disclosure pertains can easily implement them. However, the present disclosure may be implemented in several different forms and is not limited to the embodiments described herein.

Hereinafter, embodiments of the present invention will be described in detail with reference to the accompanying drawings.

In describing the embodiments, descriptions of technical contents that are well known in the technical field to which the present invention pertains and are not directly related to the present invention will be omitted. This is to more clearly convey the gist of the present invention by omitting unnecessary description.

For the same reason, some components are exaggerated, omitted, or schematically illustrated in the accompanying drawings. In addition, the size of each component does not fully reflect the actual size. In each figure, the same or corresponding elements are assigned the same reference numerals.

Advantages and features of the present invention, and a method of achieving them will become apparent with reference to the embodiments described below in detail in conjunction with the accompanying drawings. However, the present invention is not limited to the embodiments disclosed below, but may be implemented in various different forms, and only these embodiments allow the disclosure of the present invention to be complete, and common knowledge in the art to which the present invention pertains. It is provided to fully inform the possessor of the scope of the invention, and the present invention is only defined by the scope of the claims. Like reference numerals refer to like elements throughout.

At this time, it will be understood that each block of the flowchart diagrams and combinations of the flowchart diagrams may be performed by computer program instructions. These computer program instructions may be embodied in a processor of a general purpose computer, special purpose computer, or other programmable data processing equipment, such that the instructions performed by the processor of the computer or other programmable data processing equipment are not described in the flowchart block(s). It creates a means to perform functions. These computer program instructions may also be stored in a computer-usable or computer-readable memory that may direct a computer or other programmable data processing equipment to implement a function in a particular manner, and thus the computer-usable or computer-readable memory. It is also possible for the instructions stored in the flowchart block(s) to produce an article of manufacture containing instruction means for performing the function described in the flowchart block(s). The computer program instructions may also be mounted on a computer or other programmable data processing equipment, such that a series of operational steps are performed on the computer or other programmable data processing equipment to create a computer-executed process to create a computer or other programmable data processing equipment. It is also possible that instructions for performing the processing equipment provide steps for performing the functions described in the flowchart 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). It should also be noted that in some alternative implementations it is also possible for the functions recited in the blocks to occur out of order. For example, it is possible that two blocks shown in succession are actually performed substantially simultaneously, or that the blocks are sometimes performed in the reverse order according to the corresponding function.

1 is a schematic configuration diagram illustrating a system for processing delivery-related information according to an embodiment.

According to various embodiments, the system 100 for processing delivery-related information includes an electronic device 110 , a user device 120 , and a delivery source device 130 , and according to an embodiment, the store device 140 is further may include According to an embodiment, the system 100 for processing delivery-related information is a network that supports transmission and reception of information between at least some of the electronic device 110 , the user device 120 , the delivery source device 130 , and the store device 140 . It may further include a network.

Each of the electronic device 110 , the user device 120 , the delivery person device 130 , and the store device 140 may include a transceiver, a memory, and a processor. In addition, each of the electronic device 110 , the user device 120 , the delivery source device 130 , and the store device 140 means a unit that processes at least one function or operation, which is hardware, software, or hardware. and a combination of software. Meanwhile, throughout the embodiments, the electronic device 110 , the user device 120 , the delivery source device 130 , and the store device 140 are each referred to as separate devices or servers, but they may have a logically divided structure. At least some of them may be implemented by a separate function in one device or server.

The user device 120 , the delivery source device 130 , and the store device 140 are not limited to a single device, but may encompass a plurality of devices. For example, the user device 120 may be a concept that collectively refers to a device used to provide an item delivery service for one or more users. Also, the delivery source device 130 may be a concept that collectively refers to devices used for each of one or more candidate delivery sources determined by the electronic device 110 . Also, the store device 140 may be a concept that collectively refers to devices used by one or more sellers performing at least one of preparing an item and selling an item.

According to an embodiment, the electronic device 110 , the user device 120 , the delivery service device 130 , and the store device 140 may include a plurality of computer systems or computer software implemented as a network server. For example, at least some of the electronic device 110 , the user device 120 , the delivery person device 130 , and the store device 140 may communicate with other network servers through a computer network such as an intranet or the Internet. It may refer to a computer system and computer software that is connected to a device to receive a request for performing a task, perform a task thereon and provide a result of the task. In addition, at least some of the electronic device 110 , the user device 120 , the delivery person device 130 , and the store device 140 are built with a series of application programs that can operate on the network server and other nodes connected internally or connected to it. It can be understood as a concept in a broad sense including various types of databases. For example, at least some of the electronic device 110 , the user device 120 , the delivery device 130 , and the store device 140 are DOS, Windows, Linux, UNIX, Alternatively, it may be implemented using a network server program that is variously provided according to an operating system such as MacOS.

The electronic device 110 is a device that configures and provides various types of information. The electronic device 110 may provide the configured information as a web page or an application screen. The electronic device 110 may be a device that transmits/receives various information including information related to delivery, such as a shopping cart addition input and expected order information, to a user, a delivery person, and a seller.

The electronic device 110 obtains one or more shopping cart addition inputs. The one or more shopping cart addition inputs may be obtained from one or more users via the user device 120 . Here, the shopping cart corresponds to an interface that supports a user to put an item desired to be purchased on the purchase candidate list, and input to add a shopping cart may correspond to an operation of placing a specific item on the purchase candidate list.

The one or more shopping cart addition inputs include store information and item information, respectively. The item information may correspond to information on a specific item to be uploaded to the purchase candidate list. The store information may correspond to information on a store operated by a seller who performs at least one of preparing an item and selling the item. Store information according to an embodiment may include location information of the store.

According to an embodiment, when there is an input to add to the shopping cart, it may be determined that the items added to the shopping cart have a higher probability of leading to the purchase on average than the items not added to the shopping cart.

The one or more add to cart inputs obtained from the user may include add to cart inputs for food. In this case, the food may include various types of food, such as solid food, liquid food (eg, beverage or sauce), and gel-type food.

Meanwhile, in the embodiment, the shopping cart addition input is related to not only the shopping cart addition input for food, but also a service in which the electronic device 110 assigns a delivery person to deliver an item from another entity according to a user's request through a relay to perform delivery. You can comprehensively include the Add to Cart input. More specifically, in the present invention, the shopping cart addition input obtained from the user is not limited to the shopping cart addition input for food. For example, the input to add to the shopping cart obtained from the user may include input to add to the shopping cart for items requiring rapid delivery, such as flowers, feed, and other living things, in addition to food. According to an embodiment, the shopping cart addition input obtained from the user is not limited to items requiring rapid delivery, and may include shopping cart addition input for industrial products, etc. In this case, the delivery order requesting rapid delivery from the user is obtained may be, but is not limited thereto. However, for convenience of explanation, an embodiment in which an input for adding food to a shopping cart is obtained from a user will be described below, but throughout the specification, the description related to “food” will be broadly understood as a description of various items to be delivered. can

The electronic device 110 obtains expected order information corresponding to one or more shopping cart addition inputs, based on at least one of one or more pieces of information included in the one or more shopping cart addition inputs. The expected order information may be information including a result of predicting an actual order to occur in the future based on one or more shopping cart addition inputs.

The electronic device 110 determines one or more candidate delivery sources based on the obtained expected order information and one or more store information included in the one or more shopping cart addition inputs. One or more candidate delivery sources may be determined based on a result of determining whether or not they can be assigned when an actual order is generated later.

The electronic device 110 provides expected order information to one or more candidate delivery agents. The electronic device 110 may provide a page including a map displaying expected order information to the delivery source device 130 .

More details related to the operation of the electronic device 110 will be described later in FIG. 2 and the like.

A user may correspond to a customer who is a subject who orders delivery of food. The user device 120 may be a concept encompassing devices operated and managed by one or more users. The user device 120 may receive a user input from one or more users, or receive information from the electronic device 110 or the like, and may perform an operation corresponding thereto. For example, the user device 120 may receive a shopping cart addition input from the user and transmit it to the electronic device 110 . Alternatively, the user device 120 may obtain an order request and transmit a delivery order corresponding thereto to the electronic device 110 . In addition, the user device 120 may receive an input from the user and transmit it to the electronic device 110 or provide information received from the electronic device 110 to the user.

The delivery person may include various entities that take over the food from the seller and deliver the food from the seller to the user. Delivery sources include various operators that provide delivery services in a specific geographic area, and operators may include businesses and individuals. In addition, the delivery source may include a business operator that delivers regardless of the region. In addition, the delivery source may include various entities that provide delivery services in the range of a specific delivery means, and the specific delivery means may include walking, two-wheeled vehicles, bicycles, and automobiles. In addition, according to embodiments, the specific delivery means may include various types of delivery means, such as drones and railroads.

The delivery agent device 130 may be a concept encompassing devices operated and managed by one or more delivery agents. The delivery person device 130 may receive a user input from the delivery agent or the like or receive information from the electronic device 110 and the like, and may perform an operation corresponding thereto. For example, the delivery agent device 130 may receive expected order information from the electronic device 110 and provide a user interface including the received expected order information to the delivery agent.

The seller is a subject that sells food, and may correspond to a subject who operates a store or works in the store. The store device 140 may be a concept encompassing devices operated and managed by one or more vendors. The store device 140 may receive a user input from a seller or the like or may receive information from the electronic device 110 or the like and perform an operation corresponding thereto. For example, the store device 140 may receive expected order information from the electronic device 110 and provide a user interface for requesting item preparation to the seller in response thereto. Alternatively, the store device 140 may receive an expected food cooking time from the seller and transmit it to the electronic device 110 . The store device 140 of the embodiment may include a terminal used by a seller, and may be implemented in the form of installing an application on a smartphone, or may be implemented as a form of installing an application on a POS device.

In this regard, the user device 120 , the delivery source device 130 , and the store device 140 include information received from the electronic device 110 , etc. or output a user interface generated based on the received information, such as a screen. It can be converted into a form that can be output to the device and provided to a user, a delivery person, and a seller. Alternatively, the user device 120 , the delivery service device 130 , and the store device 140 may provide the information received from the electronic device 110 or the like through an output device such as a screen as it is without conversion.

The user device 120 , the delivery source device 130 , and the store device 140 may include a computer device, a mobile communication terminal, a server, and the like. The user device 120 , the delivery service device 130 , and the store device 140 may include an input device such as a touch pad, a mouse, or a keyboard for receiving a user input, or may be connected to the input device. In addition, the user device 120 , the delivery source device 130 , and the store device 140 may include an output device such as a screen, a speaker, and an interface device for providing information to the user, or may be connected to the output device. Furthermore, the input device and output device of the user device 120 , the delivery agent device 130 or the store device 140 may be integrally configured or interrelated, for example, the user device 120 or the delivery agent device 130 . may display an interface for receiving a user input.

Operations related to a series of information processing methods according to various embodiments may be implemented by a single physical device, or may be implemented in a manner in which a plurality of physical devices are organically coupled. For example, some of the components included in the system 100 for processing delivery-related information may be implemented by one physical device, and the remaining part may be implemented by another physical device. For example, any one physical device may be implemented as a part of the electronic device 110 , and another physical device may be implemented as a part of the user device 120 or other external devices. In some cases, each of the components included in the system 100 for processing delivery-related information is distributed and disposed in different physical devices, and the distributed components are organically combined to process delivery-related information. It may be implemented to perform the functions and operations of the system 100 . For example, the electronic device 110 of the present specification includes at least one sub device, some operations described as being performed by the electronic device 110 are performed by the first sub device, and some operations are performed by the second sub device. It may also be performed by the device.

2 is an operation flowchart of a delivery order processing method of an electronic device in a system for processing delivery-related information according to an exemplary embodiment.

Referring to FIG. 2 , the electronic device 110 according to an embodiment obtains one or more shopping cart addition inputs from the user device 120 ( 201 ). As described above, an embodiment in which the item to be delivered is food is described, but throughout the specification, a description related to “food” may be broadly understood as a description of various items to be delivered. The one or more shopping cart addition inputs include store information and item information, respectively.

Based on at least one of the one or more pieces of information included in the one or more shopping cart addition inputs, the electronic device 110 obtains expected order information corresponding to the one or more shopping cart addition inputs ( 202 ). Specifically, the electronic device 110 obtains probability information including a result of calculating a probability value of converting into an actual order with respect to at least a part of one or more shopping cart addition inputs, and obtains the probability information based on the probability information. can be obtained.

According to an embodiment, the electronic device 110 classifies at least some of the one or more shopping cart addition inputs into one or more groups based on one or more store information included in the one or more shopping cart addition inputs, and performs an actual order for each one or more groups. The probability of conversion can be calculated for each. For example, one or more groups are set for each specific regional range, and the electronic device 110 sets one or more locations based on a result of comparing one or more store-specific location information included in the one or more store information and a regional range corresponding to one or more groups. At least some of the shopping cart addition input may be classified into one or more groups. In this case, the electronic device 110 may classify one or more shopping cart addition inputs corresponding to one or more stores located within a certain geographic range into the same group based on location information of stores corresponding to each shopping cart addition input. For example, referring further to FIG. 3 , 11 shopping cart addition inputs corresponding to the first store 301 and 3 shopping cart addition inputs corresponding to the second store 302 are classified into the first group 310 , , 7 shopping cart addition inputs corresponding to the third store 303 and 2 shopping cart addition inputs corresponding to the fourth store 304 are classified into the second group 320 , and corresponding to the fifth store 305 . Four shopping cart addition inputs and four shopping cart addition inputs corresponding to the sixth store 306 may be classified into the third group 330 ( 300 ).

In addition to this, each add-to-cart input can be grouped into one or more groups according to various methods. For example, the electronic device 110 may classify one or more shopping cart addition inputs into one or more groups by further considering item information included in each shopping cart addition input. For example, the first store 301 is a large store in which a large number of orders are made, and a shopping cart addition input related to the first store 301 is a representative item (eg, chicken rice bowl) sold in the first store 301 . etc.), when the probability of conversion to the order is significantly different depending on whether or not the order is included, the electronic device 110 includes an input including a representative item among the shopping cart addition input related to the first store 301 and the first store 301 . It is possible to classify inputs that do not include a representative item among the shopping cart addition inputs related to , into different groups.

The electronic device 110 determines, based on the one or more store information, an order history for each store corresponding to the one or more store information, and determines a probability value that one or more shopping cart addition inputs are converted into an actual order based on the order history for each store. Probability information including the calculated result may be obtained. For example, if there were 1500 shopping cart addition inputs corresponding to the first store 301 in the past month, and 600 orders among them were actually ordered, one or more orders corresponding to the first store 301 were actually received. The probability of being converted into a spell can be calculated as 0.4. By calculating the probability value of conversion to an actual order based on the order history for each store in addition to the input of one or more shopping cart additions, the demand for the delivery service can be predicted in advance, thereby reducing the gap between the demand for the delivery service and the supply of the delivery service can

According to an embodiment, the electronic device 110 may determine one or more order histories for each user corresponding to one or more shopping cart addition inputs, and obtain probability information based on the order histories. In this case, the electronic device 110 considers the user's propensity (whether a preference for a specific store and a specific item is high, whether a rate of converting an input to add a shopping cart to an actual order is relatively high or low compared to other customers) is considered. information can be obtained.

The above-described method of obtaining probability information is exemplary, and in addition to the above-described obtaining method, the electronic device 110 considers a specific ordered item or integrates and calculates the probability of conversion into an actual order for a plurality of chain stores having the same headquarters. Alternatively, the probability that the shopping cart addition input will be converted into an actual order may be calculated based on various methods, such as calculating the probability of conversion to an actual order by time. For example, according to an embodiment, with respect to at least a part of one or more shopping cart addition inputs, an item corresponding to item information included in a specific shopping cart input is a store corresponding to store information included in a specific shopping cart input. Probability information can be obtained by judging the order history. For example, in the electronic device 110 , the history including the representative item and the history not including the representative item among the shopping cart addition history or order history related to the first store 301 are distinguished and identified, and based on this, each shopping cart is identified. The conversion probability to an actual order may be calculated by further considering whether the additional input includes the shopping cart addition input for the representative item.

According to an embodiment, the electronic device 110 may calculate a probability that the shopping cart addition input is converted into an actual order based on a calculation model based on a machine learning algorithm. In this case, the computational model may be in a pre-trained state. The calculation model can be learned based on past order history, and the learning parameters include the time when the previous shopping cart addition input was input, the actual order input time, store information and item information corresponding to the shopping cart addition input or order, and store information. Various factors may be considered, such as an attribute, one or more user-specific order histories corresponding to one or more shopping cart addition inputs.

According to an embodiment, the electronic device 110 may multiply the number of shopping cart addition inputs corresponding to the corresponding probability value and the corresponding probability value for each one or more probability values included in the probability information. Thereafter, the electronic device 110 may generate order expected value information based on the result of the multiplication operation. For example, if there are 100 shopping cart addition inputs corresponding to the X store and item A, and the probability information corresponding to the corresponding shopping cart addition input is 0.6, the expected order information corresponds to the X store and item A It may contain information about the expected value of the order of 60 (=100*0.6).

The electronic device 110 determines one or more candidate delivery sources based on the expected order information and one or more store information included in the one or more shopping cart addition inputs ( 203 ). Specifically, the electronic device 110 determines one or more pieces of location information corresponding to the expected order information based on one or more store information, and receives information on one or more delivery sources located in a certain radius based on the one or more location information. can be obtained In this regard, the one or more location information corresponding to the expected order information may include location information of the store. Alternatively, the one or more pieces of location information corresponding to the expected order information may include address information of one or more users.

Hereinafter, for convenience of description, an embodiment in which one or more location information corresponding to expected order information includes location information of a store will be described.

A more detailed description related to the operation of determining one or more candidate delivery sources will be described later with reference to FIGS. 4 and 5 .

The electronic device 110 provides expected order information to the determined one or more candidate delivery agents ( 204 ). The electronic device 110 may provide expected order information to one or more candidate delivery agents by providing the expected order information to the delivery agent device 130 . In relation to this, the electronic device 110 according to an embodiment may provide the expected order information by providing a page including a map displaying the expected order information to the delivery source device 130 .

An example of a map displaying expected order information may be displayed based on coordinate information generated based on a result of determining the density of expected orders for each predetermined regional range. An example of a map displayed based on coordinate information generated based on a result of determining the density of expected orders for each predetermined regional range may include, but is not limited to, a heat map.

For example, referring further to FIG. 6 , the electronic device 110 divides the density of the expected order into four levels, and does not separately display the area corresponding to the lowest density, but does not separately display the density of the next three levels. Coordinate information for displaying different shades in each corresponding region may be generated, and a map displayed based on this may be provided to one or more candidate delivery agents ( 600 ). In relation to this, when the delivery agent device 130 supports color output, the electronic device 110 may generate coordinate information to display different colors capable of distinguishing the density of expected orders instead of shades (in this case). , shades and different colors may be mixed).

Furthermore, when the delivery source device 130 supports the display of more than a certain number of colors, the electronic device 110 classifies the density in stages according to a predetermined condition and displays them in different colors as the density changes. It is also possible to generate coordinate information that causes the color to change continuously. In this case, there may be an advantage that a map displayed based on the coordinate information can more accurately reflect the density of expected orders.

There is a technical effect that, when expected order information is provided by displaying a map based on the result of judging the density of each region in this way, it is possible to intuitively and easily grasp how many orders will be concentrated in which region. .

According to an embodiment, the electronic device 110 providing the expected order information may propose to one or more candidate delivery agents to move to one or more locations corresponding to the expected order information. In this case, the interface proposing movement to the delivery person may be displayed together with a map displaying expected order information.

According to an embodiment, when it is proposed to move to one or more locations corresponding to the expected order information, the electronic device 110 determines the total number of expected delivery orders and how many people are located nearby the stores when there are delivery orders. It is possible to compare whether there is a delivery person, calculate how many delivery people should move to nearby locations of the stores as a result of the comparison, and determine how many candidate delivery agents to propose to move based on the calculated result. Furthermore, the electronic device 110 may specifically determine to which one of the one or more candidate delivery agents to propose the movement based on the calculated result.

According to an embodiment, when a movement to one or more locations corresponding to the expected order information is proposed, the electronic device 110 minimizes the total movement distance for the delivery person receiving the movement proposal to move to the vicinity of the store or prevents movement. Calculating which courier should move to which location to minimize the total travel time for the proposed carrier to move to the vicinity of the store, and based on the calculated result, which of the one or more candidate carriers to propose a move; and It is also possible to decide to which location specifically to propose movement to each delivery person who will propose movement.

According to an embodiment, the electronic device 110 may request one or more stores to prepare an item based on expected order information. According to one embodiment, since the preparation of a specific item requires more accurate prediction than the movement of the delivery person (when the delivery person moves to a nearby area, even if the predicted order does not occur, other items or other orders related to other stores) On the other hand, for items such as food, a specific item to be ordered by the user must be prepared within a specific time range), the electronic device 110 uses a smaller amount than the amount of food predicted by the expected order information. You can ask the store to prepare your food. For example, when there are 11 shopping cart addition inputs corresponding to the first store 301 and including item A, and the expected number of orders is 8, the electronic device 110 sets 50 of the expected number of orders. You can ask the store to prepare only 4 A items that are %. In relation to this, the electronic device 110 may request the store to prepare an item by further considering a result of determining whether the corresponding item actually leads to an order for each item sold by the store.

In this way, when the store requests the preparation of the item, the time between the user ordering the item and the actual delivery of the item can be further reduced, which increases user satisfaction, and the store and the delivery person prepare the item in advance during a leisurely time. Delivery can be started, which can help increase work efficiency or reduce work intensity.

4 is a diagram for illustratively explaining an operation of determining a candidate delivery source according to an embodiment.

Referring to FIG. 4 , the electronic device 110 according to an embodiment determines one or more pieces of location information corresponding to expected order information based on one or more pieces of store information, and is located within a certain radius based on the one or more pieces of location information. It is possible to obtain information of one or more delivery sources that do (400). In this regard, one example of the one or more location information corresponding to the expected order information is the first location information including the first store 301 and the second store 302 , the third store 303 and the fourth store ( 304 , and third location information including a fifth store 305 and a sixth store 306 . In addition, a predetermined radius range based on the first position information is indicated in reference number 410, a predetermined radius range based on the second position information is indicated in reference number 420, and a predetermined radius based on the third position information The range may be indicated by reference numeral 430 .

In the example of FIG. 4 , it is expressed as if a certain radius range is determined based on the first group 310 , the second group 320 , and the third group 330 , but classifying one or more shopping cart addition inputs into groups is a group For each calculation of the probability of conversion to an actual order, the location information in the example of FIG. 4 is for obtaining delivery source information, and the criterion does not need to correspond. In addition, in the example of FIG. 4, a certain radius range based on the first location information, a certain radius range based on the second location information, and a certain radius range based on the third location information are all the same radius range Although shown as having, the radius range may be set differently depending on various conditions, such as order density, traffic congestion, and preference of a delivery person.

In addition, in the example of FIG. 4, the radius range is farther than the first distance and shorter than the second distance (that is, in a donut-shaped range) because there is no need to provide expected order information to a delivery person located closer than a certain distance to the restaurant. Although set, the radius range is not necessarily limited to this form, for example, the radius range may be set as a donut-shaped range including all ranges shorter than the third distance.

In FIG. 4 , a delivery person located in the indicated radius range may be determined as a candidate delivery source. For example, with respect to delivery workers of reference numbers 401 to 406, the electronic device 110 expects delivery workers corresponding to reference numbers 401, 402, 405, and 406 belonging to at least one radius range. Order information can be provided. On the other hand, the delivery source corresponding to the reference number 403 and the delivery source corresponding to the reference number 404 do not belong to any radius range, so they may not be determined as candidate delivery sources.

According to an embodiment, the electronic device 110 may provide expected order information customized for each individual according to which radius range each candidate delivery source belongs to. For example, the electronic device 110 provides expected order information corresponding to the first location information and expected order information corresponding to the second location information to a delivery person corresponding to reference number 401 and a delivery person corresponding to reference number 402, , may provide expected order information corresponding to the first location information to a delivery person corresponding to reference number 405, and provide expected order information corresponding to the third location information to a delivery person corresponding to reference number 406 .

According to an embodiment, the electronic device 110 determines whether one or more delivery sources can be assigned an actual order when an actual order corresponding to the expected order information occurs, and based on the determination result, one or more delivery One or more candidate delivery sources among the circles may be determined.

According to an embodiment, the electronic device 110 may determine whether a delivery agent is in a delivery available state, and may prevent a delivery person not in a delivery available state from being included in one or more candidate delivery sources. In this regard, whether the delivery person is available for delivery may be determined by taking into account at least one of whether the delivery person is at work if the delivery person is employed by the service provider and whether the delivery person has expressed an intention to be assigned a delivery task if the delivery person is a freelancer. . In addition, whether the delivery is possible is determined by considering at least one of whether the delivery service is the delivery service being performed by the delivery person and whether there is a task that the delivery agent is planning to perform at the time when the shopping cart addition input is converted to an actual order. can

According to an embodiment, the electronic device 110 determines whether a movement path from the location of one or more delivery sources to one or more location information satisfies a preset condition, and if the preset condition is satisfied, the may be excluded from being included in one or more candidate carriers. The preset condition may include a case where there is an obstacle condition that makes it difficult to move on the moving path, such as having to move across a river or over a mountain. In addition, the preset condition may include whether a time taken for a delivery person to move to one or more location information through a movement route exceeds a preset time.

According to an embodiment, the electronic device 110 may determine information on a means of transportation used by one or more delivery sources, and determine one or more candidate delivery sources based thereon. For example, the electronic device 110 may determine a radius for allocating a delivery order for each transportation means in consideration of the movement speed of a transportation means used by one or more delivery personnel, and assign a delivery order to delivery agents within the radius. can determine whether For example, in relation to a delivery person who moves on foot, the electronic device 110 determines whether a delivery order can be processed for a delivery person located within a 1 km radius from one or more location information, and a delivery person who moves by bicycle In relation to, it is determined whether a delivery order can be processed for a delivery person located within a 1.8 km radius from one or more location information, and in relation to a delivery person moving by car, a delivery person located within a 4 km radius of one or more location information It can be determined whether the delivery order can be processed for In addition, the electronic device 110 determines whether a delivery order can be processed with respect to a delivery source within a fixed radius, but sets a lower probability of determining a candidate delivery source as a delivery agent using a slower moving means, such as one or more Various embodiments may exist for determining one or more candidate delivery agents based on the vehicle information used by the delivery person.

According to an embodiment, the electronic device 110 may determine whether the time at which the candidate delivery agent will actually perform delivery is included in a preset time interval, and determine one or more candidate delivery agents based thereon. The preset time period may include, for example, a rush hour period such as a commuting time period in which traffic is concentrated.

FIG. 5 is a case in which the electronic device 110 generates an actual order corresponding to the expected order information from one or more delivery sources in relation to the first store 301 and the second store 302 in the embodiment shown in FIG. 4 . It is determined whether an actual order can be assigned, and an example of a result of determining one or more candidate delivery sources among one or more delivery sources based on the determination result is shown ( 500 ). Specifically, referring to FIG. 5 , among the delivery workers of drawing numbers 401 to 406, the delivery person corresponding to the drawing number 405 is not in a delivery available state because the delivery service is being performed, and the delivery person corresponding to the drawing number 406 is Since it is expected that it will be difficult to arrive at the first location information at the time when the bar order, which is a delivery source moving on foot, is expected to occur, the delivery person corresponding to drawing number 405 and the delivery person corresponding to drawing number 406 are candidate delivery sources. may not be decided.

7 is an operation flowchart of an information processing method of an electronic device according to an exemplary embodiment.

Referring to FIG. 7 , the electronic device 110 according to an embodiment obtains one or more shopping cart addition inputs from one or more users ( 710 ). The one or more shopping cart addition inputs include store information and item information, respectively. One or more shopping cart addition inputs may be obtained through the user device 120 .

Based on at least one of the one or more pieces of information included in the one or more shopping cart addition inputs, the electronic device 110 acquires expected order information corresponding to the one or more shopping cart addition inputs (operation 720). The electronic device 110 may obtain probability information including a result of calculating a probability value of converting into an actual order with respect to at least a portion of one or more shopping cart addition inputs, and obtain expected order information based on the obtained probability information. have.

The electronic device 110 determines one or more candidate delivery sources based on the expected order information and one or more store information included in the one or more shopping cart addition inputs ( 730 ). The electronic device 110 determines one or more location information corresponding to the expected order information based on one or more store information, and obtains information on one or more delivery sources located in a certain radius based on the one or more location information to obtain one More than one candidate delivery source may be determined.

The electronic device 110 provides expected order information to the determined one or more candidate delivery agents ( 740 ). The electronic device 110 may provide a page including a map displaying expected order information to one or more candidate delivery agents.

8 is a diagram illustrating a configuration of an electronic device for processing delivery related information according to an embodiment.

Referring to FIG. 8 , the electronic device 110 includes a transceiver 810 , a processor 820 , and a memory 830 . The electronic device 110 may be connected to the user device 120 , the delivery person device 130 , and other external devices through the transceiver 810 , and may exchange data.

The processor 820 may include at least one of the devices described above with reference to FIGS. 1 to 7 , or perform at least one method described above with reference to FIGS. 1 to 7 . The memory 830 may store information for performing at least one method described above with reference to FIGS. 1 to 7 . The memory 830 may be a volatile memory or a non-volatile memory.

The processor 820 may control the electronic device 110 for executing a program and providing information. The code of the program executed by the processor 820 may be stored in the memory 830 .

In addition, the electronic device 110 according to an embodiment may further include an interface capable of providing information to a user.

On the other hand, in the present specification and drawings, preferred embodiments of the present invention have been disclosed, and although specific terms are used, these are only used in a general sense to easily explain the technical content of the present invention and help the understanding of the present invention, It is not intended to limit the scope of the invention. It will be apparent to those of ordinary skill in the art to which the present invention pertains that other modifications based on the technical spirit of the present invention can be implemented in addition to the embodiments disclosed herein.

The electronic device or terminal according to the above-described embodiments includes a processor, a memory for storing and executing program data, a permanent storage such as a disk drive, a communication port for communicating with an external device, a touch panel, and a key (key). ), user interface devices such as buttons, and the like. 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 the processor. Here, the computer-readable recording medium includes a magnetic storage medium (eg, read-only memory (ROM), random-access memory (RAM), floppy disk, hard disk, etc.) and an optically readable medium (eg, CD-ROM). ), DVD (Digital Versatile Disc), and the like. The computer-readable recording medium is distributed among network-connected computer systems, so that the computer-readable code can be stored and executed in a distributed manner. The medium may be readable by a computer, stored in a memory, and executed on a processor.

This embodiment may be represented by functional block configurations and various processing steps. These functional blocks may be implemented in any number of hardware and/or software configurations that perform specific functions. For example, an embodiment may be an integrated circuit configuration, such as memory, processing, logic, look-up table, etc., capable of executing various functions by the control of one or more microprocessors or other control devices. can be hired Similar to how components may be implemented as software programming or software components, this embodiment includes various algorithms implemented in a combination of data structures, processes, routines or other programming constructs, including C, C++, Java ( Java), assembler, Python, etc. may be implemented in a programming or scripting language. Functional aspects may be implemented in an algorithm running on one or more processors. In addition, the present embodiment may employ the prior art for electronic environment setting, signal processing, and/or data processing. Terms such as “mechanism”, “element”, “means” and “configuration” may be used broadly and are not limited to mechanical and physical configurations. The term may include the meaning of a series of routines of software in connection with a processor or the like.

The above-described embodiments are merely examples, and other embodiments may be implemented within the scope of the claims to be described later.

Claims (17)

A method for processing information in an electronic device providing an item delivery service, the method comprising:
obtaining at least one add to cart input, wherein the at least one add to cart input includes store information and item information, respectively;
obtaining, based on the one or more shopping cart addition inputs, expected order information corresponding to the one or more shopping cart addition inputs;
determining one or more candidate delivery sources based on the expected order information and one or more store information included in the one or more shopping cart addition inputs; and
providing shipping-related information including the expected order information to the one or more candidate shipping agents;
The delivery-related information includes one or more location information corresponding to the expected order information and expected order quantity information corresponding to the expected order information,
The step of determining the one or more candidate delivery sources is
determining the expected number of delivery orders for each one or more stores based on the expected order information;
obtaining information on delivery sources located nearby for each of the one or more stores;
determining how many delivery agents need to move in the vicinity for each of the one or more stores based on a result of determining the number of delivery orders and information on the delivery agents;
Proposing a movement to at least some of the one or more candidate delivery agents based on the confirmation result and the information of the delivery sources,
The electronic device is an information processing method for determining, by the electronic device, a candidate delivery source as a target of a movement proposal and a store serving as a destination of the movement proposal so that a sum of movement distances for each candidate delivery source who is proposed to move is minimized.
According to claim 1,
The step of obtaining the expected order information is
obtaining probability information including a result of calculating one or more probability values indicating a probability that the one or more shopping cart addition inputs are converted into an actual order; and
and obtaining the expected order information based on the probability information.
3. The method of claim 2,
The step of obtaining the probability information is
classifying at least some of the one or more shopping cart addition inputs into one or more groups based on one or more store information included in the one or more shopping cart addition inputs; and
and calculating a probability of being converted into an actual order for each of the one or more groups.
4. The method of claim 3,
The one or more groups are set for each regional range,
The step of classifying into one or more groups comprises:
Classifying at least some of the one or more shopping cart addition inputs into the one or more groups based on a result of comparing location information for each one or more stores included in the one or more store information and a regional range corresponding to each of the one or more groups Information processing method comprising a.
3. The method of claim 2,
The step of obtaining the probability information is
determining an order history for each store corresponding to the one or more store information based on one or more store information included in the one or more shopping cart addition inputs; and
Information processing method comprising the step of obtaining the probability information based on the order history.
6. The method of claim 5,
The step of determining the order history for each store is
and determining a history of ordering an item corresponding to the item information included in the specific shopping cart addition input included in the one or more shopping cart addition inputs from the store corresponding to the store information included in the specific shopping cart addition input. information processing method.
3. The method of claim 2,
The step of obtaining the probability information is
determining one or more user-specific activity information corresponding to the one or more shopping cart addition inputs; and
Comprising the step of obtaining the probability information based on the activity information,
The activity information is
An information processing method comprising at least one of a history of adding an item to a shopping cart for each of the one or more users and a history of actually ordering the item.
3. The method of claim 2,
The step of obtaining the expected order information based on the probability information
and multiplying the number of shopping cart addition inputs corresponding to the corresponding probability value and the corresponding probability value for each of the one or more probability values.
According to claim 1,
The step of determining the one or more candidate delivery sources is
determining one or more location information corresponding to the expected order information based on the one or more store information; and
The information processing method further comprising the step of obtaining information on the one or more delivery sources located in a certain radius range based on the one or more location information.
10. The method of claim 9,
The step of determining the one or more candidate delivery sources is
determining, for each of the one or more delivery sources, whether the actual order can be allocated when an actual order corresponding to the expected order information occurs; and
and determining the one or more candidate delivery sources among the one or more delivery sources based on a result of determining whether the actual order can be assigned.
11. The method of claim 10,
The step of determining whether the actual order can be assigned
determining whether the one or more delivery sources are in a delivery possible state;
determining whether a movement path from the location of the one or more delivery sources to one or more locations corresponding to the expected order information satisfies a preset condition;
determining information on the transportation means used by the one or more delivery personnel; and
When the actual order occurs, the information processing method further comprising at least one of determining whether the time to allocate the actual order is included in a preset time interval.
According to claim 1,
The step of providing the expected order information is
and providing a page including a map displaying the expected order information to the one or more candidate delivery agents.
13. The method of claim 12,
The map for displaying the expected order information is displayed based on coordinate information generated based on a result of determining the density of expected orders for each predetermined regional range.
According to claim 1,
The step of providing the expected order information is
and proposing to the one or more candidate delivery agents to move to one or more locations corresponding to the expected order information.
According to claim 1,
The method of claim 1, further comprising the step of requesting the store to prepare the item based on the expected order information.
A computer-readable non-transitory recording medium in which a program for executing the method of claim 1 in a computer is recorded.
An electronic device for processing information to provide an item delivery service, the electronic device comprising:
a transceiver, memory for storing instructions, and a processor;
The processor is connected to the transceiver and the memory,
obtain one or more add to cart inputs, wherein each of the one or more add to cart inputs includes store information and item information, respectively;
Based on the one or more shopping cart addition inputs, obtaining expected order information corresponding to the one or more shopping cart addition inputs,
determining one or more candidate delivery sources based on the expected order information and one or more store information included in the one or more shopping cart addition inputs;
providing shipping-related information including the expected order information to the one or more candidate shipping agents;
The delivery-related information includes one or more location information corresponding to the expected order information and expected order quantity information corresponding to the expected order information,
To determine the one or more candidate delivery sources, the processor comprises:
Based on the expected order information, determining the number of expected delivery orders for each one or more stores,
For each of the one or more stores, information of a delivery person located nearby is obtained,
Based on the result of determining the number of delivery orders and the information of the delivery person, check how many delivery agents need to move in the vicinity for each of the one or more stores,
Based on the confirmation result and the information of the delivery source, propose a movement to at least some of the one or more candidate delivery sources,
The processor is configured to determine a candidate delivery source that is a target of a movement proposal and a store that is a destination of the movement proposal so that a sum of movement distances for each candidate delivery source who is proposed to move is minimized.

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