Electronic device for providing information, and method therefor

Abstract

According to the present disclosure, a method by which an electronic device provides information is disclosed, the method comprising the steps of: identifying delivery history information related to a delivery service; identifying a prediction model on the basis of the delivery history information; identifying state information related to the delivery service; identifying delivery allocation delay prediction information of a set time period on the basis of the prediction model and the state information; and determining policy information of the delivery service for adjusting delivery demand and / or delivery supply on the basis of the delivery allocation delay prediction information of the set time period.

Description

Electronic device and method for providing information

[0001] The present disclosure relates to an electronic device and a method for providing information. More specifically, the present disclosure relates to an electronic device and a method for determining policy information by identifying delivery allocation delay prediction information for a set time interval based on a prediction model and state information.

[0002] As demand in the e-commerce sector grows, the number of users purchasing products through e-commerce platforms is increasing exponentially. For example, e-commerce platforms can support users' product purchases through various features to enhance user convenience.

[0003] For example, e-commerce platforms may utilize various algorithms to assign delivery tasks to couriers upon receiving a shipping request from a user. In this process, minimizing the time spent assigning tasks to couriers to ensure faster delivery of items to users is emerging as a critical issue.

[0004] Meanwhile, situations may arise where delivery supply is insufficient, such as when delivery requests suddenly increase, or where delivery demand is insufficient, such as when the number of delivery requests is low compared to the number of delivery personnel capable of performing delivery tasks. Therefore, there is a need to develop technology that minimizes surplus resources and provides optimal delivery services by establishing policies to regulate delivery supply and delivery demand.

[0005] The problem that the present embodiment aims to solve is to provide an electronic device and method that, in order to solve the aforementioned problem, verifies a prediction model based on delivery history information, predicts delivery allocation delay information based on the prediction model and status information, and determines policy information.

[0006] The technical problems to be solved by the present disclosure are not limited to those described above, and other technical problems can be inferred from the following embodiments.

[0007] A method for providing information performed by an electronic device related to a delivery service according to an embodiment of the present disclosure may include: a step of verifying delivery history information related to the delivery service; a step of verifying a prediction model based on the delivery history information; a step of verifying status information related to the delivery service; a step of verifying delivery allocation delay prediction information for a set time interval based on the prediction model and the status information; and a step of determining policy information for the delivery service to adjust at least one of delivery demand and delivery supply based on the delivery allocation delay prediction information for the set time interval.

[0008] According to one embodiment, the delivery history information may include at least one of the total number of delivery requests in a designated past time interval where the delivery service was provided, the number of delivery requests that were not assigned, the amount of change in delivery requests, the delivery assignment time, the number of delivery personnel capable of performing delivery tasks, the number of delivery personnel currently performing delivery tasks, whether an event occurred, and weather information.

[0009] According to one embodiment, the status information may include at least one of the following: the number of delivery requests confirmed based on the time interval corresponding to the time of the set time interval, the number of delivery requests not assigned for delivery, the amount of change in delivery requests, the delivery assignment time, the number of delivery personnel capable of performing delivery tasks, the number of delivery personnel currently performing delivery tasks, whether an event has occurred, and weather information.

[0010] According to one embodiment, the delivery allocation delay prediction information may include first delivery allocation delay prediction information, second delivery allocation delay prediction information, and third delivery allocation delay prediction information corresponding to a first time interval among the set time intervals, a second time interval after the first time interval, and a third time interval after the second time interval, respectively. For example, the first time interval may be shorter than the second time interval, and the second time interval may be shorter than the third time interval.

[0011] According to one embodiment, the delivery allocation delay prediction information can be determined based on the delivery request time and delivery allocation time through the delivery service.

[0012] According to one embodiment, the information providing method can determine the delivery allocation delay prediction time of the first time interval based on a weighted average calculated by applying a high weight to the delivery allocation delay prediction time at a time close to the present among the first delivery allocation delay prediction information.

[0013] According to one embodiment, the information providing method may further include the step of confirming a first trend of the delivery allocation delay prediction time of the second time interval based on the second delivery allocation delay prediction information, and the step of determining the policy information based on the result of comparison between the first trend and the first reference value.

[0014] According to one embodiment, the information providing method may further include the steps of: checking the difference between the length of the longest increasing subsequence (LIS) and the length of the longest decreasing subsequence (LDS) of the delivery allocation delay prediction time of the second time interval based on the first trend; determining first policy information to increase the delivery supply of the second time interval when the difference exceeds the first reference value; and determining second policy information to increase the delivery demand of the second time interval when the difference is less than or equal to the first reference value.

[0015] According to one embodiment, the information providing method may further include the step of confirming a second trend of the delivery allocation delay prediction time of the third time interval based on the third delivery allocation delay prediction information, and the step of determining the policy information based on the result of comparison between the second trend and a second reference value. For example, the second reference value may be greater than the first reference value.

[0016] According to one embodiment, the information providing method may further include the step of determining first policy information for controlling the delivery supply. For example, the first policy information may include a policy that performs at least one of increasing the delivery fee and hiding at least one store exposed for the delivery service if the delivery allocation delay prediction information satisfies a first condition regarding a shortage of the delivery supply.

[0017] According to one embodiment, the information providing method may further include the step of performing the shipping cost increase processing preferentially when the shipping allocation delay prediction information satisfies the first condition, and the step of further performing the hiding processing for the at least one store when the shipping allocation delay prediction information continues to satisfy the first condition after a specified time has elapsed.

[0018] According to one embodiment, the information providing method may further include the step of determining second policy information for controlling the delivery demand. For example, the second policy information may include a policy to perform at least one of a delivery fee reduction process and an exposure process for at least one hidden store if the delivery allocation delay prediction information satisfies a second condition regarding a lack of delivery demand.

[0019] According to one embodiment, the information providing method may further include the step of performing the shipping cost reduction processing preferentially when the shipping allocation delay prediction information satisfies the second condition, and the step of further performing the exposure processing for the at least one store when the shipping allocation delay prediction information continues to satisfy the second condition after a specified time has elapsed.

[0020] According to one embodiment, the information providing method may further include the step of identifying a target store among the at least one store whose order volume exceeds a specified order volume based on the delivery history information, and the step of preferentially performing the hiding process on the target store among the at least one store.

[0021] According to one embodiment, the information providing method may further include the steps of identifying a target store among the at least one store whose average delivery allocation delay time exceeds a specified delay time based on the delivery history information, and performing the hiding process preferentially on the target store among the at least one store.

[0022] According to one embodiment, a computer-readable non-transient recording medium may be disclosed, which stores a program for executing an information provision method according to at least one of the methods described above on a computer.

[0023] According to one embodiment, an electronic device providing information may include a memory storing at least one instruction and a processor operatively connected to said memory. For example, said at least one instruction may be configured such that, when executed by said processor, the electronic device checks delivery history information related to a delivery service, checks a prediction model based on said delivery history information, checks status information related to said delivery service, checks delivery allocation delay prediction information for a set time interval based on said prediction model and said status information, and determines policy information for said delivery service to adjust at least one of delivery demand and delivery supply based on said delivery allocation delay prediction information for the set time interval.

[0024] According to one embodiment, the delivery allocation delay prediction information may include first delivery allocation delay prediction information, second delivery allocation delay prediction information, and third delivery allocation delay prediction information corresponding to a first time interval among the set time intervals, a second time interval after the first time interval, and a third time interval after the second time interval, respectively. For example, the first time interval may be shorter than the second time interval, and the second time interval may be shorter than the third time interval.

[0025] Specific details of other embodiments are included in the detailed description and drawings.

[0026] According to the present disclosure, changes in delivery demand and delivery supply can be predicted, and an efficient delivery service can be provided based on policy information determined through the prediction results.

[0027] The effects of the invention are not limited to those mentioned above, and other unmentioned effects will be clearly understood by a person skilled in the art from the description in the claims.

[0028] FIG. 1 is a configuration diagram showing a system for providing information according to one embodiment.

[0029] FIG. 2 is a flowchart illustrating a method of providing information by an electronic device according to one embodiment.

[0030] FIG. 3a is a table showing delivery history information according to one embodiment.

[0031] FIG. 3b is a table for explaining how an electronic device according to one embodiment outputs delivery allocation delay prediction information using a prediction model.

[0032] FIG. 4 is a configuration diagram illustrating a method for an electronic device to determine policy information according to one embodiment.

[0033] FIG. 5 is a flowchart illustrating a method of providing information by an electronic device according to one embodiment.

[0034] FIG. 6 is a flowchart illustrating a method of providing information by a user terminal according to one embodiment.

[0035] FIG. 7 is a flowchart illustrating a method of providing information by a user terminal according to one embodiment.

[0036] FIG. 8 is an example diagram of the configuration of an electronic device according to one embodiment.

[0037] The terms used in the embodiments have been selected to be as widely used as possible, taking into account their functions in the present disclosure; however, these may vary depending on the intent of those skilled in the art, case law, the emergence of new technologies, etc. Additionally, in specific cases, terms have been arbitrarily selected by the applicant, and in such cases, their meanings will be described in detail in the relevant explanatory section. Therefore, terms used in the present disclosure should be defined not merely by their names, but based on their meanings and the overall content of the present disclosure.

[0038] When a part of a specification is described as “comprising” a certain component, this means that, unless specifically stated otherwise, it does not exclude other components but may include additional components. Furthermore, terms such as “...part” or “...module” as used in the specification refer to a unit that processes at least one function or operation, and this may be implemented in hardware or software, or as a combination of hardware and software.

[0039] The expression “at least one of a, b, and c” described throughout the specification may include ‘a alone’, ‘b alone’, ‘c alone’, ‘a and b’, ‘a and c’, ‘b and c’, or ‘a, b, and c all’.

[0040] The "terminal" mentioned below may be implemented as a computer or portable terminal capable of connecting to a server or other terminal via a network. Here, the computer includes, for example, a notebook, desktop, or laptop equipped with a web browser, and the portable terminal may include, for example, a wireless communication device that ensures portability and mobility, and may include all types of handheld-based wireless communication devices such as IMT (International Mobile Telecommunication), CDMA (Code Division Multiple Access), W-CDMA (W-Code Division Multiple Access), LTE (Long Term Evolution), communication-based terminals, smartphones, tablet PCs, etc.

[0041] Embodiments of the present disclosure are described below with reference to the attached drawings so that those skilled in the art can easily implement them. However, the present disclosure may be embodied in various different forms and is not limited to the embodiments described herein.

[0042] Hereinafter, embodiments of the present invention will be described in detail with reference to the attached drawings.

[0043] In describing the embodiments, technical details that are well known in the technical field to which the present invention belongs and are not directly related to the present invention are omitted. This is intended to convey the essence of the present invention more clearly without obscuring it by omitting unnecessary explanations.

[0044] For the same reason, some components in the attached drawings have been exaggerated, omitted, or schematically depicted. Additionally, the size of each component does not entirely reflect its actual dimensions. Identical or corresponding components in each drawing have been assigned the same reference numbers.

[0045] The advantages and features of the present invention and the methods for achieving them will become clear by referring to the embodiments described below in detail together with the accompanying drawings. However, the present invention is not limited to the embodiments disclosed below but can be implemented in various different forms. These embodiments are provided merely to ensure that the disclosure of the present invention is complete and to fully inform those skilled in the art of the scope of the invention, and the present invention is defined only by the scope of the claims. Throughout the specification, the same reference numerals refer to the same components.

[0046] At this time, it will be understood that each block of the process flow diagrams and combinations of the flow diagrams can be executed by computer program instructions. Since these computer program instructions can be loaded into the processor of a general-purpose computer, a special-purpose computer, or other programmable data processing equipment, the instructions executed through the processor of the computer or other programmable data processing equipment create means to perform the functions described in the flow diagram block(s). Since these computer program instructions can also be stored in computer-available or computer-readable memory that can be directed toward the computer or other programmable data processing equipment to implement the function in a specific way, the instructions stored in computer-available or computer-readable memory can also produce a manufactured item containing instruction means to perform the function described in the flow diagram block(s). Since computer program instructions can be loaded onto a computer or other programmable data processing equipment, instructions that perform a series of operation steps on the computer or other programmable data processing equipment to create a process executed by the computer can also provide steps for executing the functions described in the flowchart block(s).

[0047] Additionally, each block may represent a module, segment, or part of code containing one or more executable instructions for executing a specified logical function(s). It should also be noted that in some alternative execution examples, the functions mentioned in the blocks may occur out of order. For instance, two blocks described in succession may actually be executed substantially simultaneously, or the blocks may be executed in reverse order according to their corresponding functions.

[0048]

[0049] FIG. 1 is a configuration diagram showing a system for providing information according to one embodiment.

[0050] According to various embodiments, a system for providing information includes an electronic device (110). According to one embodiment, a system for providing information may further include a delivery terminal (120). A system for providing information according to one embodiment may further include a network that supports the transmission and reception of information between the electronic device (110) and the delivery terminal (120).

[0051] The electronic device (110) and the delivery terminal (120) may include a processor (e.g., the processor (810) of FIG. 8) and a memory (e.g., the memory (820) of FIG. 8), and may further include a communication device (e.g., the communication device (830) of FIG. 8). Additionally, the electronic device (110) and the delivery terminal (120) each represent a unit that processes at least one function or operation, which may be implemented in hardware or software, or a combination of hardware and software.

[0052] Meanwhile, throughout the embodiments, the electronic device (110) and the delivery terminal (120) are each referred to as separate devices or servers, but they may have a logically separated structure, and at least some of them may be implemented by functions separated from a single device or a single server. For example, throughout the disclosure, the electronic device (110) and the delivery terminal (120) may be implemented by a single device, and in this case, at least some of the processes of transmitting and receiving information between the electronic device (110) and the delivery terminal (120) can be understood as processes of exchanging data within a single device. For example, the process of the delivery terminal (120) outputting information provided by the electronic device (110) can be understood as a process in which a single device verifies, acquires, and configures information and provides it to a user.

[0053] In addition, depending on the embodiment, some of the operations of the electronic device (110) and the delivery terminal (120) described below may be performed together with or by other devices not shown in FIG. 1. For example, the operation of the electronic device (110) storing information may include the operation of transmitting information to another device (e.g., a storage device) that interacts with the electronic device (110) so that the information is stored in the other device.

[0054] The "delivery history information" described in this disclosure may include a history of delivery services provided through a delivery service or requested by a user during a specified time interval in the past.

[0055] The "delivery allocation delay prediction information" described in this disclosure may include time information required to allocate delivery tasks for each delivery request confirmed during a set time interval. That is, the delivery allocation delay prediction information may be determined based on the delivery request time and delivery allocation time confirmed through the delivery service. For example, the delivery allocation delay prediction information may include time information corresponding to each of a plurality of time intervals included in the set time interval.

[0056] The "delivery demand" described in this disclosure may include information regarding delivery requests corresponding to the number of items purchased by a user through a delivery service. For example, the delivery demand may be proportional to the number of delivery requests. That is, delivery requests may increase as the number of items to be delivered increases with increasing item purchase volume, and decrease as the number of items to be delivered decreases with decreasing item purchase volume.

[0057] The "delivery supply" described in this disclosure may include information regarding resources capable of performing a delivery service. For example, the delivery supply may be proportional to the number of delivery personnel logged into the delivery service. For example, the delivery supply may be proportional to the number of delivery personnel capable of performing delivery tasks to deliver items corresponding to delivery requests to users. That is, the delivery supply may increase as the number of delivery personnel capable of performing delivery tasks for current items increases, and decrease as the number of delivery personnel capable of performing delivery tasks decreases.

[0058] The “hiding process” described in the present disclosure may be an algorithm that prevents a store exposed by a software platform from being displayed any further among at least one store providing sales and delivery services for items.

[0059] The “exposure processing” described in the present disclosure may be an algorithm that causes a store to which “hiding processing” is applied among at least one store providing sales and delivery services for items to be displayed on a software platform.

[0060] According to one embodiment, the electronic device (110) and / or delivery terminal (120) may include a number of computer systems or computer software implemented as network servers. For example, the electronic device (110) and / or delivery terminal (120) may refer to computer systems and computer software that are connected to a sub-device capable of communicating with other network servers via a computer network such as an intranet or the Internet, receive requests for work execution, perform the work thereon, and provide the results of the execution. In addition, the electronic device (110) and / or delivery terminal (120) may be understood in a broad sense as including a series of applications capable of operating on a network server and various databases built on internal or other connected nodes. For example, the electronic device (110) and / or delivery terminal (120) may be implemented using network server programs provided in various ways depending on operating systems such as DOS, Windows, Linux, UNIX, or MacOS, at least in part.

[0061] Meanwhile, for the sake of convenience of explanation, each operating entity has been referred to as an electronic device (110) or a delivery terminal (120), but these should be understood as a comprehensive type of device that corresponds to, includes, or can be included in, various types of devices such as a server, a computer device, and a mobile communication terminal.

[0062] The electronic device (110) may include a device that processes and provides various information. The electronic device (110) may perform various tasks to provide information. For example, the electronic device (110) may include components according to FIG. 4, which will be described later, and may be a device (or server) that provides and supports software (or application) that performs policy information determined based on information according to FIG. 3a and FIG. 3b.

[0063] The electronic device (110) can check and provide information related to the delivery service. The electronic device (110) can check status information related to the delivery service and check delivery allocation delay prediction information for a set time interval based on the status information. The electronic device (100) can determine policy information for the delivery service based on delivery allocation delay prediction information for a set time interval.

[0064] The delivery terminal (120) may be a user terminal that performs software provided by the electronic device (110) and transmits information obtained from the electronic device (110) to the delivery person. The delivery terminal (120) may be implemented, for example, as a mobile communication terminal that the delivery person can carry (e.g., PDA (personal digital assistant), mobile phone, tablet, etc.).

[0065] The above-described embodiments may be implemented as artificial intelligence (AI) through the processor (810) and memory (820) of the electronic device (110). The "prediction model" described in this disclosure may be one of the artificial intelligence models stored in the memory (820). The processor (810) may be composed of one or more processors, and the one or more processors may be general-purpose processors such as a CPU, AP, DSP (digital signal processor), etc., graphics-dedicated processors such as a GPU, VPU (vision processing unit), or artificial intelligence-dedicated processors such as an NPU. The one or more processors may be controlled to process input data according to predefined operation rules or artificial intelligence models stored in the memory (820). Alternatively, if the one or more processors are artificial intelligence-dedicated processors, the artificial intelligence-dedicated processors may be designed with a hardware structure specialized for processing a specific artificial intelligence model.

[0066] The predefined operation rules or artificial intelligence models are characterized by being created through learning. Here, being created through learning means that a predefined operation rules or artificial intelligence models are created by a basic artificial intelligence model being trained using a number of learning data by a learning algorithm to perform a desired characteristic (or purpose). Such learning may be performed within the electronic device (110) itself where the artificial intelligence according to the present disclosure is performed, or through a separate server and / or system. Examples of learning algorithms include supervised learning, unsupervised learning, semi-supervised learning, or reinforcement learning, but are not limited to the examples described above.

[0067] An artificial intelligence model may be composed of multiple neural network layers. Each of the multiple neural network layers has multiple weight values ​​and can perform neural network operations through operations between the results of previous layers and the multiple weights. The multiple weights possessed by the multiple neural network layers can be optimized based on the learning results of the artificial intelligence model. For example, the multiple weights can be updated so that the loss value or cost value obtained from the artificial intelligence model during the learning process is reduced or minimized. The artificial neural network may include, but is not limited to, deep neural networks (DNN), convolutional neural networks (CNN), recurrent neural networks (RNN), restricted Boltzmann machines (RBM), deep belief networks (DBN), bidirectional recurrent deep neural networks (BRDNN), or deep Q-networks.

[0068] According to one embodiment, the electronic device (110) can verify (or learn) a prediction model based on delivery history information related to a delivery service.

[0069] For example, delivery history information may include at least one of the total number of delivery requests in a past time period in which delivery services were provided, the number of delivery requests that were not assigned, the amount of change in delivery requests, the delivery assignment time, the number of delivery personnel capable of performing delivery tasks, the number of delivery personnel currently performing delivery tasks, whether an event occurred, and weather information.

[0070] According to one embodiment, the electronic device (110) can check delivery allocation delay prediction information for a set time interval based on state information according to a predefined rule or artificial intelligence model stored in memory (820).

[0071] For example, status information may include at least one of the following: the number of delivery requests confirmed based on the time interval corresponding to the time of the set time interval, the number of delivery requests not assigned for delivery, the amount of change in delivery requests, the delivery assignment time, the number of delivery personnel capable of performing delivery tasks, the number of delivery personnel currently performing delivery tasks, whether an event has occurred, and weather information. The time interval corresponding to the time of the set time interval may correspond to a future specified time interval (e.g., 30 minutes) based on the current time.

[0072]

[0073] FIG. 2 is a flowchart illustrating a method of providing information by an electronic device according to one embodiment.

[0074] According to one embodiment, the electronic device (110) can perform the operations disclosed in FIG. 2. For example, at least some of the components included in the electronic device (110) (e.g., the processor (810), memory (820), and communication device (830) of FIG. 8) may be configured to perform the operations of FIG. 2.

[0075] In the following embodiments, the operations S210 to S250 may be performed sequentially, but are not necessarily performed sequentially. For example, the order of each operation may be changed, and at least two operations may be performed in parallel. Additionally, content corresponding to or overlapping with the above description in relation to FIG. 2 may be briefly explained or omitted.

[0076] According to one embodiment, the electronic device (110) can check delivery history information related to the delivery service (S210).

[0077] The electronic device (110) can check delivery history information for a designated past time period in which delivery services were provided.

[0078] The electronic device (110) can check delivery history information for a designated past time interval that includes a past time related to the current time among the entire delivery history information stored in the memory (820).

[0079] Delivery history information may include, for example, at least one of the total number of delivery requests in a designated past time interval where delivery services were provided, the number of delivery requests that were not assigned, the amount of change in delivery requests, the delivery assignment time, the number of delivery personnel capable of performing delivery tasks, the number of delivery personnel currently performing delivery tasks, whether an event occurred, and weather information.

[0080] According to one embodiment, the electronic device (110) can verify a prediction model based on delivery history information (S220).

[0081] The electronic device (110) can verify a prediction model learned based on delivery history information. For example, the electronic device (110) can train a prediction model based on delivery history information according to FIG. 3a, which will be described later.

[0082] According to one embodiment, the electronic device (110) can check status information related to the delivery service (S230).

[0083] The electronic device (110) can check state information for a time interval corresponding to the time point of the set time interval. The time point of the set time interval may be, for example, the current time point at which the state information is checked. The time interval corresponding to the time point of the set time interval may be, for example, a future designated time interval (e.g., 30 minutes) based on the current time point at which the state information is checked.

[0084] Status information may include, for example, at least one of the number of delivery requests confirmed based on the time interval corresponding to the time of the set time interval, the number of delivery requests not assigned for delivery, the amount of change in delivery requests, the delivery assignment time, the number of delivery personnel capable of performing delivery tasks, the number of delivery personnel currently performing delivery tasks, whether an event has occurred, and weather information.

[0085] According to one embodiment, the electronic device (110) can check delivery allocation delay prediction information for a set time interval based on a prediction model and state information (S240).

[0086] The electronic device (110) can input state information into a prediction model. The electronic device (110) can check delivery allocation delay prediction information output from the prediction model in correspondence with the state information.

[0087] Delivery allocation delay prediction information may include first delivery allocation delay prediction information, second delivery allocation delay prediction information, and third delivery allocation delay prediction information corresponding to a first time interval included in a set time interval, a second time interval after the first time interval, and a third time interval after the second time interval, respectively. The first time interval may be shorter than the second time interval, and the second time interval may be shorter than the third time interval. For example, if the set time interval corresponds to 30 minutes, the first time interval may correspond to 3 minutes, the second time interval to 12 minutes, and the third time interval to 15 minutes. The numerical limitation of the time intervals is provided as an example for illustrative purposes, and the embodiments of the present disclosure are not limited to the numerical limitation described above.

[0088] Delivery allocation delay prediction information can be determined based on the delivery request time and delivery allocation time through the delivery service. For example, delivery allocation delay prediction information may include a delivery allocation delay prediction time proportional to the difference between the delivery request time and the delivery allocation time.

[0089] According to one embodiment, the electronic device (110) can determine policy information for a delivery service to adjust at least one of delivery demand and delivery supply based on delivery allocation delay prediction information of a set time interval (S250).

[0090] The electronic device (110) can determine the delivery allocation delay prediction time of the first time interval based on a weighted average of the first delivery allocation delay prediction information corresponding to the first time interval. For example, the electronic device (110) can determine the delivery allocation delay prediction time of the first time interval based on a weighted average calculated by applying a high weight to the delivery allocation delay prediction time of the first delivery allocation delay prediction information that is close to the present time. Based on the delivery allocation delay prediction time of the first time interval, the electronic device (110) can determine policy information for adjusting at least one of the delivery demand and delivery supply for the first time interval.

[0091] The electronic device (110) can identify a first trend of the delivery allocation delay prediction time of the second time interval based on the second delivery allocation delay prediction information, and determine policy information based on the result of comparison between the first trend and the first reference value. For example, the electronic device (110) can identify a first trend including the amount of change of the delivery allocation delay prediction time predicted for the second time interval based on the second delivery allocation delay prediction information. For example, the electronic device (110) can identify a first difference between the length of the LIS (longest increasing subsequence) and the length of the LDS (longest decreasing subsequence) of the delivery allocation delay prediction time of the second time interval based on the first trend, and determine policy information based on the result of comparison between the first difference and the first reference value.

[0092] For example, the case where the first difference exceeds the first reference value can be defined as a case where the delivery supply of the second time zone is insufficient. When the electronic device (110) confirms that the first difference exceeds the first reference value, it can determine first policy information to increase the delivery supply of the second time zone.

[0093] For example, the case where the first difference is less than or equal to the first reference value can be defined as a case where the delivery demand for the second time zone is insufficient. When the electronic device (110) confirms that the first difference is less than or equal to the first reference value, it can determine second policy information to increase the delivery demand for the second time zone.

[0094] The electronic device (110) can identify a second trend of the delivery allocation delay prediction time of the third time interval based on the third delivery allocation delay prediction information, and determine policy information for the third time interval based on the result of comparing the second trend and the second reference value. For example, the electronic device (110) can identify a second trend including the amount of change of the predicted delivery allocation delay time for the third time interval based on the third delivery allocation delay prediction information. For example, the electronic device (110) can identify a second difference between the LIS length and the LDS length of the delivery allocation delay prediction time of the third time interval based on the second trend, and determine policy information based on the result of comparing the second difference and the second reference value.

[0095] For example, the case where the second difference exceeds the second reference value can be defined as a case where the delivery supply of the third time zone is insufficient. When the electronic device (110) confirms that the second difference exceeds the second reference value, it can determine first policy information to increase the delivery supply of the third time zone.

[0096] For example, the case where the second difference is less than or equal to the second reference value can be defined as a case where there is insufficient delivery demand in the third time zone. When the electronic device (110) confirms that the second difference is less than or equal to the second reference value, it can determine second policy information to increase delivery demand in the third time zone.

[0097] For example, the second reference value (e.g., 3) may be greater than the first reference value (e.g., 2).

[0098] The electronic device (110) can determine first policy information for regulating delivery supply based on delivery allocation delay prediction information.

[0099] For example, the first policy information may include a shipping supply increase policy that performs at least one of a shipping fee increase processing and a hiding processing for at least one store exposed for shipping services when the shipping allocation delay prediction information satisfies a first condition regarding a shortage of shipping supply. That is, if the electronic device (110) identifies a time interval with a shortage of shipping supply based on the shipping allocation delay prediction information of a set time interval, it may determine the first policy information for increasing the shipping supply of the identified time interval.

[0100] For example, if the delivery allocation delay prediction information satisfies the first condition, the electronic device (110) may prioritize the processing of the increase in delivery costs. If, after a specified time has elapsed, the delivery allocation delay prediction information continues to satisfy the first condition, the electronic device (110) may further perform a hiding process for at least one store.

[0101] For example, the electronic device (110) can identify a delivery terminal (120) corresponding to at least one delivery person who is not currently performing delivery work, and provide a notification to the identified delivery terminal (120) requesting delivery work and a notification regarding an increase in delivery fees.

[0102] The electronic device (110) can determine second policy information for adjusting delivery demand based on delivery allocation delay prediction information.

[0103] For example, the second policy information may include a delivery demand increase policy that performs at least one of delivery cost reduction processing and exposure processing for at least one hidden store if the delivery allocation delay prediction information satisfies the second condition regarding a lack of delivery demand. That is, if the electronic device (110) identifies a time interval with insufficient delivery demand based on the delivery allocation delay prediction information of a set time interval, it may determine the second policy information for increasing delivery demand in the identified time interval.

[0104] For example, if the shipping allocation delay prediction information satisfies the second condition, the electronic device (110) may prioritize the shipping cost reduction processing. If, after a specified time has elapsed, the shipping allocation delay prediction information continues to satisfy the second condition, the electronic device (110) may further perform exposure processing for at least one store.

[0105] The electronic device (110) can preferentially perform hiding or exposure processing for the target store identified based on the delivery history information.

[0106] For example, the electronic device (110) can perform a hiding or exposure process preferentially for target stores where the order volume of past time intervals exceeds a specified order volume (or, the highest order volume) based on delivery history information.

[0107] For example, the electronic device (110) can perform a hiding or exposure process preferentially for a target store where the average delivery allocation delay time of the past time interval exceeds the specified delay time (or, the average delivery allocation delay time is the highest) based on delivery history information.

[0108] In FIGS. 3a and 3b below, information used by the electronic device (110) to train a prediction model or to check delivery allocation delay prediction information using the prediction model is described.

[0109]

[0110] FIG. 3a is a table showing delivery history information according to one embodiment.

[0111] FIG. 3b is a table (350) for explaining how an electronic device according to one embodiment checks delivery allocation delay prediction information using a prediction model.

[0112] According to one embodiment, the electronic device (110) can verify a prediction model learned based on delivery history information according to reference number 300 of FIG. 3a.

[0113] The electronic device (110) can train a prediction model based on delivery history information from the past time intervals of t1 to t3 of the first region corresponding to a delivery area identification number of 1.

[0114] The electronic device (110) can train a prediction model based on delivery history information from the past time intervals of t4 to t5 in the second region corresponding to a delivery area identification number of 2.

[0115] According to one embodiment, the electronic device (110) can check delivery allocation delay prediction information according to reference number 350 of FIG. 3b based on delivery history information.

[0116] The electronic device (110) can confirm that the delivery allocation delay prediction times for each of the past time intervals of t1 to t3 in the first region included in reference number 350 are 97 seconds, 142 seconds, and 136 seconds, respectively, based on the delivery history information and prediction model of the past time intervals of t1 to t3 in the first region included in reference number 300.

[0117] The electronic device (110) can confirm that the delivery allocation delay prediction times for each of the t4 and t5 of the second region included in reference number 350 are 201 seconds and 289 seconds, respectively, based on the delivery history information and prediction model of the past time intervals of t4 to t5 of the second region included in reference number 300.

[0118] The electronic device (110) can check delivery allocation delay prediction information for a set time interval by using a prediction model learned by repeatedly performing the above-described operation. For example, the electronic device (110) can check delivery allocation delay prediction information for a set time interval output from the prediction model by inputting the confirmed status information based on the time interval corresponding to the time point of the set time interval into the prediction model. For example, the time interval corresponding to the time point of the set time interval may correspond to a future designated time interval (e.g., 30 minutes) based on the current time point.

[0119]

[0120] FIG. 4 is a configuration diagram illustrating a method for an electronic device to determine policy information according to one embodiment.

[0121] According to one embodiment, the electronic device (110) may include a trigger generation unit (410), a data storage unit (420), and a prediction model (430). The trigger generation unit (410), the data storage unit (420), and the prediction model (430) may be logically separated structures, and at least some of these may be implemented as a single device (e.g., a processor (820)).

[0122] The electronic device (110) can generate a trigger signal based on a specified period through the trigger generation unit (410). For example, the electronic device (110) can transmit the generated trigger signal to the data storage unit (420).

[0123] The electronic device (110) can input at least some of the data stored in the data storage unit (420) into the prediction model (430). For example, when a trigger signal generated based on a specified period is transmitted to the data storage unit (420), the electronic device (110) can input the delivery history information and / or status information stored in the data storage unit (420) into the prediction model (430).

[0124] The electronic device (110) can verify the prediction model (430) based on delivery history information. For example, the electronic device (110) can train the prediction model (430) based on delivery history information of a specified past time period during which delivery services were provided. For example, the electronic device (110) can repeatedly train the prediction model (430) based on delivery history information regardless of a specified period associated with a trigger signal.

[0125] The electronic device (110) can determine policy information (460) for a delivery service to adjust at least one of the delivery demand and delivery supply of a set time interval based on state information and a prediction model (430).

[0126] For example, the electronic device (110) can identify first prediction information (441), second prediction information (442), and third prediction information (443) corresponding to a first time interval, a second time interval after the first time interval, and a third time interval after the second time interval, respectively, based on state information and a prediction model (430). For example, the first time interval may be shorter than the second time interval, and the second time interval may be shorter than the third time interval.

[0127] For example, the electronic device (110) can check the first prediction information (441) corresponding to the first time interval among the set time intervals, and can check the delivery allocation delay prediction time for the first time interval based on the weighted average (451) calculated by applying a high weight to the delivery allocation delay prediction time at a time close to the present among the first prediction information (441). The electronic device (110) can determine policy information (460) for the first time interval based on the calculated delivery allocation delay prediction time.

[0128] For example, the electronic device (110) can check second prediction information (442) corresponding to the second time interval among the set time intervals, check the short-term prediction trend (452) of the delivery allocation delay prediction time of the second time interval based on the second prediction information (442), and determine policy information (460) for the second time interval based on the result of comparison between the short-term prediction trend (452) and the first reference value. For example, the electronic device (110) can check the first difference between the LIS length and LDS length of the delivery allocation delay prediction time of the second time interval based on the short-term prediction trend (452), and determine policy information (460) for the second time interval based on the result of comparison between the first difference and the first reference value.

[0129] For example, the electronic device (110) can check third prediction information (443) corresponding to the third time interval among the set time intervals, check the mid-to-long-term prediction trend (453) of the delivery allocation delay prediction time of the third time interval based on the third prediction information (443), and determine policy information (460) for the third time interval based on the result of comparison between the mid-to-long-term prediction trend (453) and the second reference value. For example, the electronic device (110) can check the second difference between the LIS length and LDS length of the delivery allocation delay prediction time of the third time interval based on the mid-to-long-term prediction trend (453), and determine policy information (460) for the third time interval based on the result of comparison between the second difference and the second reference value. For example, the second reference value may be greater than the first reference value.

[0130] The electronic device (110) can perform an action according to the first policy information (461) if the delivery allocation delay prediction information (440) satisfies the first condition regarding the shortage of delivery supply, and can perform an action according to the second policy information (462) if the second condition regarding the shortage of delivery demand is satisfied.

[0131] The first policy information (461) may include a policy that performs at least one of processing an increase in shipping fees and hiding at least one store exposed for shipping services. For example, the first policy information (461) may further include sending a shipping fee increase notification to the delivery terminal (120) and a request to perform shipping tasks.

[0132] The second policy information (462) may include a policy that performs at least one of the shipping cost reduction processing and the exposure processing for at least one store that is hidden.

[0133] For example, if the weighted average (451) exceeds a specified value, the electronic device (110) determines that the first prediction information (441) satisfies the first condition regarding the shortage of delivery supply and can determine the first policy information (461) for regulating the delivery supply of the first time interval.

[0134] For example, if the weighted average (451) is less than or equal to a specified value, the electronic device (110) determines that the first prediction information (441) satisfies the second condition regarding the lack of delivery demand and can determine the second policy information (462) for adjusting the delivery demand of the first time zone.

[0135] For example, if the first difference between the LIS length and LDS length of the delivery allocation delay prediction time of the second time interval confirmed based on the short-term prediction trend (452) exceeds the first reference value, the electronic device (110) determines that the second prediction information (442) satisfies the first condition regarding the shortage of delivery supply and can determine the first policy information (461) for adjusting the delivery supply of the second time interval.

[0136] For example, if the first difference between the LIS length and LDS length of the delivery allocation delay prediction time of the second time interval confirmed based on the short-term prediction trend (452) is less than or equal to the first reference value, the electronic device (110) determines that the second prediction information (442) satisfies the second condition regarding the lack of delivery demand and can determine the second policy information (462) for adjusting the delivery demand of the second time interval.

[0137] For example, if the second difference between the LIS length and LDS length of the delivery allocation delay prediction time of the third time interval confirmed based on the medium-to-long-term prediction trend (453) exceeds the second reference value, the electronic device (110) determines that the third prediction information (443) satisfies the first condition regarding the shortage of delivery supply and can determine the first policy information (461) for adjusting the delivery supply of the third time interval.

[0138] For example, if the second difference between the LIS length and LDS length of the delivery allocation delay prediction time of the third time interval confirmed based on the medium-to-long-term prediction trend (453) is less than or equal to the second reference value, the electronic device (110) determines that the third prediction information (443) satisfies the second condition regarding the lack of delivery demand and can determine the second policy information (462) for adjusting the delivery demand of the third time interval.

[0139]

[0140] FIG. 5 is a flowchart illustrating a method of providing information by an electronic device according to one embodiment.

[0141] According to one embodiment, the electronic device (110) can perform the operations disclosed in FIG. 5. For example, at least some of the components included in the electronic device (110) (e.g., the processor (810), memory (820), and communication device (830) of FIG. 8) may be configured to perform the operations of FIG. 5.

[0142] In the following embodiments, the operations of S510 to S530 may be performed sequentially, but are not necessarily performed sequentially. For example, the order of each operation may be changed, and at least two operations may be performed in parallel. Additionally, content corresponding to or overlapping with the above description in relation to FIG. 5 may be briefly explained or omitted.

[0143] According to one embodiment, the electronic device (110) can check delivery allocation delay prediction information for each of the plurality of time intervals included in the set time interval (S510).

[0144] The electronic device (110) can check the first delivery allocation delay prediction information and the second delivery allocation delay prediction information corresponding to each of the first time interval and the second time interval among the set time intervals by using state information and a prediction model. For example, the electronic device (110) can further check the third delivery allocation delay prediction information corresponding to the third time interval.

[0145] According to one embodiment, the electronic device (110) can determine the delivery allocation delay prediction time of the first time interval based on the weighted average of the first delivery allocation delay prediction information (S520).

[0146] The electronic device (110) can determine the delivery allocation delay prediction time of the first time interval based on a weighted average calculated by applying a high weight to the delivery allocation delay prediction time of the time interval near the present among the first delivery allocation delay prediction information. That is, the electronic device (110) can calculate the weighted average of the delivery allocation delay prediction time for the first time interval by applying a relatively high weight to the delivery allocation delay prediction time of the time interval near the present among the multiple delivery allocation delay prediction times of the first time interval included in the first delivery allocation delay prediction information.

[0147] The electronic device (110) can determine policy information for adjusting at least one of the delivery supply and delivery demand of the first time zone based on a weighted average. For example, if the weighted average exceeds a specified value, the electronic device (110) can determine first policy information for increasing the delivery supply of the first time zone. For example, if the weighted average is less than or equal to a specified value, the electronic device (110) can determine second policy information for increasing the delivery demand of the first time zone.

[0148] According to one embodiment, the electronic device (110) can check the trend of the delivery allocation delay prediction time of the second time interval through the second delivery allocation delay prediction information (S530).

[0149] The electronic device (110) can determine the first trend of the delivery allocation delay prediction time of the second time interval based on the second delivery allocation delay prediction information, and determine policy information based on the result of comparison between the first trend and the first reference value.

[0150] The electronic device (110) can determine the difference between the LIS length and LDS length of the delivery allocation delay prediction time of the second time interval based on the first trend. For example, if the difference exceeds a first reference value, the electronic device (110) can determine first policy information to increase the delivery supply of the second time interval. For example, if the difference exceeds a first reference value, the electronic device (110) can determine second policy information to increase the delivery demand of the second time interval.

[0151]

[0152] FIG. 6 is a flowchart illustrating a method of providing information by an electronic device according to one embodiment.

[0153] According to one embodiment, the electronic device (110) can perform the operations disclosed in FIG. 6. For example, at least some of the components included in the electronic device (110) (e.g., the processor (810), memory (820), and communication device (830) of FIG. 8) may be configured to perform the operations of FIG. 6.

[0154] In the following embodiments, the operations of S610 to S640 may be performed sequentially, but are not necessarily performed sequentially. For example, the order of each operation may be changed, and at least two operations may be performed in parallel. Additionally, content corresponding to or overlapping with the above description in relation to FIG. 6 may be briefly explained or omitted.

[0155] According to one embodiment, the electronic device (110) can identify a first trend of the delivery delay prediction time of the second time interval based on the second delivery allocation delay prediction information (S610).

[0156] The electronic device (110) can identify the trends of delivery supply and delivery demand predicted for the second time period based on the first trend.

[0157] According to one embodiment, the electronic device (110) can determine the difference between the LIS length and the LDS length based on the first trend (S620).

[0158] The electronic device (110) can determine the longest increasing subsequence (LIS) of the predicted delivery allocation delay time for the second time interval based on the first trend, and determine the length of the longest increasing subsequence.

[0159] The electronic device (110) can determine the longest declining subsequence (LDS) of the predicted delivery allocation delay time for the second time interval based on the first trend, and determine the length of the longest declining subsequence.

[0160] The electronic device (110) can check the difference between the LIS length and the LDS length.

[0161] According to one embodiment, the electronic device (110) can determine the difference between the LIS length and the LDS length based on the first trend (S630).

[0162] The electronic device (110) can check whether the difference exceeds a first reference value (S630).

[0163] For example, the electronic device (110) can identify a second trend of the delivery delay prediction time of the third time interval based on third delivery allocation delay prediction information for the third time interval, and determine policy information for the third time interval based on the result of comparing the difference between the LIS length and LDS length of the second trend with a second reference value. At this time, the second reference value (e.g., 3) may be greater than the first reference value.

[0164] For example, the first reference value may correspond to 2 and the second reference value may correspond to 3, but such numerical limitations are merely examples for illustrative purposes and the embodiments of the present disclosure are not limited to the numerical limitations described above.

[0165] For example, if the difference exceeds the first reference value (e.g., Step S630 - Yes), the electronic device (110) can perform Step S640.

[0166] For example, if the difference is less than or equal to the first reference value (e.g., step S630 - No), the electronic device (110) can perform step S635.

[0167] According to one embodiment, the electronic device (110) can determine first policy information for increasing the delivery supply (S640).

[0168] The electronic device (110) can determine first policy information for increasing the delivery supply of the second time interval. For example, the first policy information may include a policy to perform at least one of increasing the delivery fee and hiding at least one store exposed for delivery services when the delivery allocation delay prediction information satisfies a first condition regarding the shortage of delivery supply.

[0169] According to one embodiment, the electronic device (110) can determine second policy information to increase delivery demand (S635).

[0170] The electronic device (110) can determine second policy information to increase delivery demand in the second time zone. For example, the second policy information may include a policy to perform at least one of delivery cost reduction processing and exposure processing for at least one hidden store if delivery allocation delay prediction information satisfies a second condition regarding a lack of delivery demand.

[0171]

[0172] FIG. 7 is a flowchart illustrating a method of providing information by an electronic device according to one embodiment.

[0173] According to one embodiment, the electronic device (110) can perform the operations disclosed in FIG. 7. For example, at least some of the components included in the electronic device (110) (e.g., the processor (810), memory (820), and communication device (830) of FIG. 8) may be configured to perform the operations of FIG. 7.

[0174] In the following embodiments, the operations of S710 to S720 may be performed sequentially, but are not necessarily performed sequentially. For example, the order of each operation may be changed, and at least two operations may be performed in parallel. Additionally, content corresponding to or overlapping with the above description in relation to FIG. 7 may be briefly explained or omitted.

[0175] According to one embodiment, the electronic device (110) can identify a target store among at least one store based on delivery history information (S710).

[0176] The electronic device (110) can identify a target store among at least one store whose order volume in the past time period exceeds a specified order volume based on delivery history information.

[0177] The electronic device (110) can identify a target store among at least one store whose average delivery allocation delay time in the past time interval exceeds the specified delay time based on delivery history information.

[0178] According to one embodiment, the electronic device (110) can perform a hiding process for the target store first (S720).

[0179] The electronic device (110) can prioritize hiding the target store among at least one store if the delivery allocation delay prediction information satisfies the second condition regarding the shortage of delivery supply.

[0180]

[0181] FIG. 8 is an example diagram of the configuration of an electronic device according to one embodiment.

[0182] Referring to FIG. 8, the electronic device (110) includes a processor (810) and a memory (820), and may further include a communication device (830) depending on the embodiment. The electronic device (110) can be connected to an external device (e.g., the delivery terminal (120) of FIG. 1) through the communication device (830) and exchange data.

[0183] The processor (810) may include at least one device described through FIGS. 1 to 7 or perform at least one method described through FIGS. 1 to 7. The memory (820) may store information for performing at least one method described through FIGS. 1 to 7. The memory (820) may be a volatile memory or a non-volatile memory.

[0184] The processor (810) can control an electronic device (110) that executes a program and provides information for processing an item. The code of the program executed by the processor (810) can be stored in memory (820).

[0185] The communication device (830) can support the establishment of a direct (e.g., wired) communication channel or a wireless communication channel between various devices, including an electronic device (110) (e.g., a server) and an external device, and the performance of communication through the established communication channel. The communication device (830) may include one or more communication processors that operate independently of the processor (810) and support direct (e.g., wired) communication or wireless communication. According to one embodiment, the communication device (830) may include a wireless communication module (e.g., a cellular communication module, a short-range wireless communication module, or a GNSS (global navigation satellite system) communication module) or a wired communication module (e.g., a LAN (local area network) communication module, or a power line communication module). The corresponding communication module among these communication modules can communicate with an external electronic device through a first network (e.g., a short-range communication network such as Bluetooth, WiFi (wireless fidelity) direct, or IrDA (infrared data association)) or a second network (e.g., a legacy cellular network, a 5G network, a next-generation communication network, the Internet, or a long-range communication network such as a computer network (e.g., LAN or WAN). These various types of communication modules may be integrated into a single component (e.g., a single chip) or implemented as multiple separate components (e.g., multiple chips). The wireless communication module can identify or authenticate the electronic device (110) within a communication network, such as the first network or the second network, using subscriber information (e.g., International Mobile Subscriber Identifier (IMSI)) stored in the subscriber identification module.

[0186] In addition, the electronic device (110) of the embodiment may further include an interface capable of providing information to a user (e.g., a worker, a manager, or a customer).

[0187] Meanwhile, the present specification and drawings disclose preferred embodiments of the present invention. Although specific terms have been used, they are used merely in a general sense to facilitate the explanation of the technical content of the present invention and to aid in understanding the invention, and are not intended to limit the scope of the present invention. It is obvious to those skilled in the art that, in addition to the embodiments disclosed herein, other variations based on the technical concept of the present invention are possible.

[0188] A server or terminal according to the embodiments described above may include 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, and user interface devices such as a touch panel, a key, a button, etc. Methods implemented as software modules or algorithms may be stored on a computer-readable recording medium as computer-readable code or program instructions executable on the processor. Here, computer-readable recording media include magnetic storage media (e.g., ROM (read-only memory), RAM (random-access memory), floppy disks, hard disks, etc.) and optical reading media (e.g., CD-ROM, DVD (Digital Versatile Disc)). Computer-readable recording media may be distributed across networked computer systems, allowing computer-readable code to be stored and executed in a distributed manner. The medium may be readable by a computer, stored in memory, and executed by a processor.

[0189] The present embodiment may be represented by functional block configurations and various processing steps. These functional blocks may be implemented by various numbers of hardware and / or software configurations that execute specific functions. For example, the embodiment may employ integrated circuit configurations such as memory, processing, logic, look-up tables, etc., capable of executing various functions by the control of one or more microprocessors or other control devices. Similar to how components may be implemented as software programming or software elements, the present embodiment may be implemented in programming or scripting languages ​​such as C, C++, Java, assembler, Python, etc., including various algorithms implemented as combinations of data structures, processes, routines, or other programming configurations. Functional aspects may be implemented as algorithms executed on one or more processors. Additionally, the present embodiment may employ prior art for electronic configuration, 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 above terms may include the meaning of a series of software processes (routines) in conjunction with processors, etc.

[0190] The aforementioned embodiments are merely examples, and other embodiments may be implemented within the scope of the claims set forth below.

Claims

1. In a method of providing information performed by an electronic device related to a delivery service, A step of verifying delivery history information related to the above delivery service; Step of verifying the prediction model based on the above delivery history information; A step of checking status information related to the above delivery service; A step of confirming delivery allocation delay prediction information for a time interval set based on the above prediction model and the above status information; and The step of determining policy information for the delivery service to adjust at least one of delivery demand and delivery supply based on the delivery allocation delay prediction information of the set time interval; comprising Method of providing information.

2. In Paragraph 1, The above shipping history information is, at least one of the total number of delivery requests in a designated past time interval where the delivery service was provided, the number of delivery requests not assigned, the amount of change in delivery requests, the delivery assignment time, the number of delivery personnel capable of performing delivery tasks, the number of delivery personnel currently performing delivery tasks, whether an event occurred, and weather information. Method of providing information.

3. In Paragraph 1, The above status information is, at least one of the number of delivery requests confirmed based on the time interval corresponding to the time of the set time interval, the amount of change in delivery requests, the delivery allocation time, the number of delivery personnel capable of performing delivery tasks, the number of delivery personnel currently performing delivery tasks, whether an event has occurred, and weather information. Method of providing information.

4. In Paragraph 1, The above delivery allocation delay prediction information is, It includes first delivery allocation delay prediction information, second delivery allocation delay prediction information, and third delivery allocation delay prediction information corresponding to each of the first time interval among the set time intervals, the second time interval after the first time interval, and the third time interval after the second time interval, and The first time interval is shorter than the second time interval, and the second time interval is shorter than the third time interval. Method of providing information.

5. In Paragraph 1, The above delivery allocation delay prediction information is, Determined based on the delivery request time and delivery allocation time through the above delivery service, Method of providing information.

6. In Paragraph 4, The above method of providing information is, A step of verifying the delivery allocation delay prediction time of the first time interval based on a weighted average calculated by applying a high weight to the delivery allocation delay prediction time at a time close to the present among the first delivery allocation delay prediction information; Method of providing information.

7. In Paragraph 4, The above method of providing information is, A step of confirming a first trend of the delivery allocation delay prediction time of the second time interval based on the second delivery allocation delay prediction information; The step of determining the policy information based on the result of comparing the first trend and the first reference value; further comprising Method of providing information.

8. In Paragraph 7, The above method of providing information is, Based on the first trend above, a step of determining the difference between the LIS (longest increasing subsequence) length and the LDS (longest decreasing subsequence) length of the delivery allocation delay prediction time of the second time interval; and The method further comprises the step of determining first policy information to increase the delivery supply of the second time zone when the difference exceeds the first reference value, and determining second policy information to increase the delivery demand of the second time zone when the difference is less than or equal to the first reference value. Method of providing information.

9. In Paragraph 7, The above method of providing information is, A step of confirming a second trend of the delivery allocation delay prediction time of the third time interval based on the third delivery allocation delay prediction information; The step of determining the policy information based on the comparison result between the second trend and the second reference value; further comprising The above second reference value is greater than the above first reference value, Method of providing information.

10. In Paragraph 1, The above method of providing information is, Further comprising the step of determining first policy information for regulating the above delivery supply; The above first policy information is, A policy comprising, if the above delivery allocation delay prediction information satisfies the first condition regarding the shortage of the above delivery supply, to perform at least one of the processing of increasing the delivery fee and the processing of hiding at least one store exposed for the above delivery service, Method of providing information.

11. In Paragraph 10, The above method of providing information is, If the above delivery allocation delay prediction information satisfies the above first condition, the step of performing the above delivery fee increase processing preferentially; and If the delivery allocation delay prediction information continues to satisfy the first condition after a specified time has elapsed, the step of further performing a hiding process for the at least one store; further comprising Method of providing information.

12. In Paragraph 1, The above method of providing information is, Further comprising the step of determining second policy information for regulating the above delivery demand; The above second policy information is, A policy comprising, if the above delivery allocation delay prediction information satisfies the second condition regarding the lack of delivery demand, to perform at least one of delivery cost reduction processing and exposure processing for at least one hidden store, Method of providing information.

13. In Paragraph 12, The above method of providing information is, If the above delivery allocation delay prediction information satisfies the above second condition, the step of performing the above delivery cost reduction processing preferentially; and If the delivery allocation delay prediction information continues to satisfy the second condition after a specified time has elapsed, the step of further performing exposure processing for the at least one store; further comprising Method of providing information.

14. In Paragraph 10, The above method of providing information is, A step of identifying a target store among at least one store whose order volume exceeds a specified order volume based on the above delivery history information; and The step of preferentially performing the hiding process on the target store among the at least one store; further comprising Method of providing information.

15. In Paragraph 10, The above method of providing information is, A step of identifying a target store among at least one store whose average delivery allocation delay time exceeds a specified delay time based on the above delivery history information; and The step of preferentially performing the hiding process on the target store among the at least one store; further comprising Method of providing information.

16. A computer-readable, non-transient recording medium having a program for executing any one of the methods of paragraphs 1 through 15 on a computer.

17. In an electronic device that provides information, Memory for storing at least one instruction; and A processor operatively connected to the above memory; comprising, When the above at least one instruction is executed by the processor, the electronic device: Check delivery history information related to the delivery service, Check the prediction model based on the above delivery history information, and Check the status information related to the above delivery service, and Check the delivery allocation delay prediction information for the time interval set based on the above prediction model and the above status information, and Configured to determine policy information for the delivery service to adjust at least one of delivery demand and delivery supply based on delivery allocation delay prediction information of the above-set time interval, Electronic device.

18. In Paragraph 16, The above delivery allocation delay prediction information is, It includes first delivery allocation delay prediction information, second delivery allocation delay prediction information, and third delivery allocation delay prediction information corresponding to each of the first time interval among the set time intervals, the second time interval after the first time interval, and the third time interval after the second time interval, and The first time interval is shorter than the second time interval, and the second time interval is shorter than the third time interval. Method of providing information.

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