KR102449350B1 - System for providing stock managing service and method for operation thereof - Google Patents

Abstract

Various embodiments of the present invention relate to a system that provides an inventory management service using an artificial intelligence model and an operating method therefor. The system that provides the inventory management service comprises: a plurality of user devices; a product providing server; and a management server.

Description

SYSTEM FOR PROVIDING STOCK MANAGING SERVICE AND METHOD FOR OPERATION THEREOF

The present invention relates to an inventory management service.

In addition, various embodiments of the present invention relate to a system for providing an inventory management service using an artificial intelligence model and an operating method thereof.

In recent years, as the Internet spreads widely regardless of age or region, various businesses for generating profits using the Internet network are emerging and expanding. Among them, e-commerce systems, particularly shopping malls using the Internet, are emerging in rapid succession, including various portal sites.

In particular, in addition to a simple Internet shopping mall in which several products are simply posted on an Internet site so that buyers can view and purchase the products, shopping malls of various business methods are emerging based on various sales or marketing capabilities and capital.

For example, a model in which a seller enters a specific Internet site, sells goods and pays a sales commission, a business model in which a shopping mall is distributed to a business operator who wants a shopping mall in the Internet site and pays a allowance through member sales, an independent Soho Mall on the Internet (SOHO mall, Small Office Home Office mall) is built and operated individually, and a model that allows consumers who enter a well-known portal site to search for and purchase products by simply linking their own shopping mall site to a specific portal site. A shopping mall operation method is being proposed.

Also, in recent years, artificial intelligence systems that implement human-level intelligence have been used in various fields. Unlike the existing rule-based smart system, an artificial intelligence system is a system in which a machine learns, judges, and becomes smarter by itself. The more the artificial intelligence system is used, the better the recognition rate and the more accurate understanding of user preferences, and the existing rule-based smart systems are gradually being replaced by deep learning-based artificial intelligence systems.

Artificial intelligence technology consists of machine learning (eg, deep learning) and elemental technologies using machine learning.

Machine learning is an algorithm technology that categorizes/learns the characteristics of input data by itself, and element technology uses machine learning algorithms such as deep learning to simulate functions such as cognition and judgment of the human brain. It consists of technical fields such as understanding, reasoning/prediction, knowledge expression, and motion control.

Various fields where artificial intelligence technology is applied are as follows. Linguistic understanding is a technology for recognizing and applying/processing human language/text, and includes natural language processing, machine translation, dialogue system, question and answer, and speech recognition/synthesis. Visual understanding is a technology for recognizing and processing objects like human vision, and includes object recognition, object tracking, image search, human recognition, scene understanding, spatial understanding, image improvement, and the like. Inferential prediction is a technology for logically reasoning and predicting by judging information, and includes knowledge/probability-based reasoning, optimization prediction, preference-based planning, and recommendation. Knowledge expression is a technology that automatically processes human experience information into knowledge data, and includes knowledge construction (data generation/classification) and knowledge management (data utilization). Motion control is a technology for controlling autonomous driving of a vehicle and movement of a robot, and includes motion control (navigation, collision, driving), manipulation control (action control), and the like.

Domestic Patent Publication No. 10-2002-0079302 (2002.10.19)

The present invention intends to propose a part that can be improved in providing an inventory management service.

A system for providing an inventory management service using an artificial intelligence model according to various embodiments of the present invention and an operation method therefor, apply various selection information about a product and a prediction period to be confirmed to the artificial intelligence model during the prediction period It is possible to provide an inventory management service that calculates the expected sales volume of the product.

The technical problems to be achieved in the present invention are not limited to the technical problems mentioned above, and other technical problems not mentioned will be clearly understood by those of ordinary skill in the art to which the present invention belongs from the description below. will be able

According to various embodiments, a system for providing an inventory management service includes a plurality of user devices, a product providing server, and a management server, wherein the management server includes a specific information obtained from the plurality of user devices during a specific period. Identifies selection information for a product - The selection information for the specific product includes the number of selections of detailed information of the specific product, the number of additions to the shopping cart, the number of registrations of the product of interest, the number of reviews, the number of inquiries, and the number of payment completion- , by applying the selection information for the specific product and the prediction period related to the specific product to an artificial intelligence model for identifying a forecast period related to the specific product and estimating the expected sales volume, during the forecast period calculating the first expected sales volume to be sold, calculating an order quantity of the specific product based on the current inventory amount and the first expected sales volume of the specific product, and calculating the order amount of the specific product based on the order amount for the specific product It may be set to transmit a message requesting delivery to the product providing server.

According to various embodiments, the number of times of selecting the detailed information of the specific product is that the specific product is selected by the plurality of user devices from the product list including the information on the plurality of products and the details of the specific product represents the number of times of displaying information, the number of times of adding the specific product to the shopping cart represents the number of times the specific product is added to the shopping cart by the plurality of user devices, and the number of times of registering the product of interest of the specific product is, Indicates the number of times the specific product is registered as a product of interest by a plurality of user devices, the number of reviews for the specific product indicates the number of times that a review for the specific product is written, and the number of inquiries about the specific product may indicate the number of times an inquiry is made for the specific product, and the number of payment completions for the specific product may indicate the number of times payment for the specific product has been successfully completed.

According to various embodiments, the management server obtains information about a weight for each expected sales volume for the specific product during the prediction period as output data of the artificial intelligence model, and a weight is It may be set to determine the highest expected sales volume as the first predicted sales volume.

According to various embodiments, the management server may be configured to determine the order amount of the specific product by applying a predetermined ratio to a quantity obtained by subtracting the current inventory amount from the first expected sales volume.

According to various embodiments, the management server may be configured to obtain selection information for each product and sales volume information for each product from the memory of the management server.

According to various embodiments, the management server sets selection information for each product for each period before a specific time as input data, and sets the sales volume of each product for each period after the specific time as output data, It can be set to perform learning of an artificial intelligence model.

An enhanced inventory management service may be provided through the present invention.

According to various embodiments of the present invention, malicious inventory is prevented by estimating the expected sales volume of a product with high accuracy using an artificial intelligence model learned based on various selection information of the product, and inventory management is performed through an automated inventory management method. It is possible to reduce unnecessary resource cost and provide the effect of efficiently controlling the inventory of goods.

The effects obtainable in the present invention are not limited to the above-mentioned effects, and other effects not mentioned may be clearly understood by those of ordinary skill in the art from the following description. will be.

Other aspects, features and benefits as described above of certain preferred embodiments of the present invention will become more apparent from the following description taken in conjunction with the accompanying drawings.
1 is a block diagram of an electronic device and a network according to various embodiments of the present disclosure;
2 is a block diagram of an electronic device according to various embodiments of the present disclosure;
3 is a block diagram of a program module according to various embodiments of the present disclosure;
4 illustrates devices constituting a system for providing an inventory management service according to various embodiments of the present disclosure.
5 is a flowchart illustrating a method of operating a management server according to various embodiments of the present disclosure;
6 is a view for explaining selection information for a specific product, according to various embodiments of the present disclosure;
7 illustrates an example in which an artificial intelligence model operates to estimate an expected sales volume for a specific product, according to various embodiments.
8 is a diagram for explaining an operation of training an artificial intelligence model to estimate an expected sales volume for a specific product, according to various embodiments of the present disclosure;
8 is a diagram for explaining an operation of training an artificial intelligence model to estimate an expected sales volume for a specific product, according to various embodiments of the present disclosure;
9 is a diagram for explaining an embodiment of learning an artificial intelligence model, according to various embodiments.

Hereinafter, various embodiments of the present document will be described with reference to the accompanying drawings. The examples and terms used therein are not intended to limit the technology described in this document to specific embodiments, and should be understood to cover various modifications, equivalents, and/or substitutions of the embodiments. In connection with the description of the drawings, like reference numerals may be used for like components. The singular expression may include the plural expression unless the context clearly dictates otherwise. In this document, expressions such as “A or B” or “at least one of A and/or B” may include all possible combinations of items listed together. Expressions such as "first," "second," "first," or "second," can modify the corresponding elements, regardless of order or importance, and to distinguish one element from another element. It is used only and does not limit the corresponding components. When an (eg, first) component is referred to as being “connected (functionally or communicatively)” or “connected” to another (eg, second) component, that component is It may be directly connected to the component or may be connected through another component (eg, a third component).

In this document, "configured (or configured to)" means "suitable for," "having the ability to," "modified to, ," "made to," "capable of," or "designed to," may be used interchangeably. In some contexts, the expression “a device configured to” may mean that the device is “capable of” with other devices or components. For example, the phrase “a processor configured (or configured to perform) A, B, and C” refers to a dedicated processor (eg, an embedded processor) for performing the operations, or by executing one or more software programs stored in a memory device. , may refer to a general-purpose processor (eg, a CPU or an application processor) capable of performing corresponding operations.

The electronic device according to various embodiments of the present disclosure may include, for example, a smartphone, a tablet PC, a mobile phone, a video phone, an e-book reader, a desktop PC, a laptop PC, a netbook computer, a workstation, a server, a PDA, and a PMP. It may include at least one of a portable multimedia player, an MP3 player, a medical device, a camera, and a wearable device. A wearable device may be an accessory (e.g., watch, ring, bracelet, anklet, necklace, eyewear, contact lens, or head-mounted-device (HMD)), a textile or clothing integral (e.g. electronic garment); It may include at least one of a body-worn (eg, skin pad or tattoo) or bioimplantable circuit In some embodiments, the electronic device may include, for example, a television, a digital video disk (DVD) player, Audio, refrigerator, air conditioner, vacuum cleaner, oven, microwave oven, washing machine, air purifier, set-top box, home automation control panel, security control panel, media box (e.g. Samsung HomeSync ^TM , Apple TV ^TM , or Google TV ^TM ) , a game console (eg, Xbox ^TM , PlayStation ^TM ), an electronic dictionary, an electronic key, a camcorder, or an electronic picture frame.

In another embodiment, the electronic device may include various medical devices (eg, various portable medical measuring devices (eg, a blood glucose meter, a heart rate monitor, a blood pressure monitor, or a body temperature monitor), magnetic resonance angiography (MRA), magnetic resonance imaging (MRI), Computed tomography (CT), imagers, or ultrasound machines, etc.), navigation devices, global navigation satellite systems (GNSS), event data recorders (EDRs), flight data recorders (FDRs), automotive infotainment devices, marine electronic equipment (e.g. navigation devices for ships, gyro compasses, etc.), avionics, security devices, head units for vehicles, industrial or household robots, drones, ATMs in financial institutions, point of sale (POS) in stores of sales) or IoT devices (eg, light bulbs, various sensors, sprinkler devices, fire alarms, thermostats, street lights, toasters, exercise equipment, hot water tanks, heaters, boilers, etc.). According to some embodiments, the electronic device is a piece of furniture, a building/structure, or a vehicle, an electronic board, an electronic signature receiving device, a projector, or various measuring devices (eg, water, electricity, gas, or a radio wave measuring device). In various embodiments, the electronic device may be flexible or a combination of two or more of the various devices described above. The electronic device according to the embodiment of the present document is not limited to the above-described devices. In this document, the term user may refer to a person who uses an electronic device or a device (eg, an artificial intelligence electronic device) using the electronic device.

1 , an electronic device 101 in a network environment 100 is described, in various embodiments. The electronic device 101 may include a bus 110 , a processor 120 , a memory 130 , an input/output interface 150 , a display 160 , and a communication interface 170 .

Hereinafter, specific components of the electronic device 101 will be described with reference to FIGS. 1 to 3 .

4 illustrates devices constituting a system 400 for providing an inventory management service, according to various embodiments.

According to various embodiments, the system 400 for providing an inventory management service may include a plurality of user devices 401a , 401b , 401c , a product providing server 402 , and a management server 403 . . According to an embodiment, the plurality of user devices 401a, 401b, and 401c, the product providing server 402, and the management server 403 constitute at least one of the respective components of the electronic device 101 of FIG. 1 . It can be implemented to include elements. Hereinafter, it is assumed that the management server 403 corresponds to the electronic device 101 of FIG. 1 .

According to one embodiment, each of the plurality of user devices 401a, 401b, 401c is, for example, a smartphone, a tablet PC, a mobile phone, a video phone, an e-book reader, a desktop PC, a laptop PC, a netbook computer, a work It may include at least one of a station, a server, a PDA, a portable multimedia player (PMP), a camera, and a wearable device. According to an embodiment, each of the plurality of user devices 401a, 401b, and 401c accesses a website or application provided by the management server 403 and transmits information processable by the management server 403, or Information processed by the management server 403 may be received. The plurality of user devices 401a, 401b, and 401c receive the source code for displaying each page of the shopping mall related web site provided by the management server 403, and each page of the web site through a web browser can be displayed. The number (eg, three) of the plurality of user devices 401a, 401b, and 401c described in the present specification is only one example and is not limited thereto, and it is understood by those skilled in the art that various numbers of user devices may be used. will be easily understood by

According to an embodiment, the product providing server 402 is a server operating in conjunction with the management server 403 , and may provide a service for delivering products according to the order amount of the products requested by the management server 403 . The product providing server 402 may be a server operated by a business handling wholesale products.

According to an embodiment, the management server 403 may be a server that provides a shopping mall related web site composed of a plurality of web pages to a plurality of user devices 401a, 401b, and 401c. . According to an embodiment, the management server 403 transmits a source code that enables the plurality of user devices 401a, 401b, and 401c to display each page of the website to the plurality of user devices 401a, 401b, and 401c. ) can be sent. The management server 403 may be a server operated by a business handling retail products.

5 is a flowchart for explaining how the management server 403 operates, FIG. 6 is a diagram for explaining selection information for a specific product, and FIG. 7 is an artificial intelligence for estimating the expected sales volume for a specific product. An example in which the model operates is shown.

In operation 501 , according to various embodiments, the management server 403 (eg, the processor 120 of FIG. 1 ) configures a plurality of user devices (eg, the plurality of user devices 401a, 401b, 401c of FIG. 4 ). )), selection information for a specific product acquired during a specific period can be identified.

The selection information for a specific product includes the number of times of selecting detailed information of a specific product, the number of additions to the shopping cart of a specific product, the number of registrations of products of interest for a specific product, the number of reviews for a specific product, the number of inquiries about a specific product, and the number of inquiries about a specific product. It may include at least one of the number of payment completion times.

For example, referring to <601> and <602> of FIG. 6 , “the number of times of selecting detailed information” of a specific product 610 is a product list (eg, screen <601>) including information about a plurality of products. A specific product 610 is selected by the plurality of user devices 401a, 401b, and 401c among the product list displayed in Indicates the number of times displayed, and when screen <601> is changed to screen <602> by user selection, the management server 403 may count "the number of times of selecting detailed information" once.

For example, referring to <601> and <602> of FIG. 6 , the “number of shopping cart additions” of the specific product 610 indicates that the specific product 610 is selected by the plurality of user devices 401a, 401b, and 401c. Indicates the number of times added to the shopping cart, and the shopping cart addition item 611 for the specific product 610 is selected on the <601> screen by the plurality of user devices 401a, 401b, and 401c, or the specific product 611 is selected on the <602> screen When the shopping cart addition item 613 for 610 is selected, the management server 403 may count "the number of times added to the shopping cart" once.

For example, referring to <601> and <602> of FIG. 6 , the “number of registrations of products of interest” of a specific product 610 is a specific product 610 by a plurality of user devices 401a, 401b, and 401c. Indicates the number of times this product of interest has been registered, and the item of interest 612 for a specific product 610 is selected on screen <601> by a plurality of user devices 401a, 401b, 401c, or screen <602> When the product of interest registration item 614 for a specific product 610 is selected, the management server 403 may count "the number of times of registration of the product of interest" once.

For example, referring to <603> of FIG. 6 , the “number of reviews” for a specific product 610 indicates the number of times that a review is written for the specific product 610, and includes a plurality of user devices 401a, 401b, 401c), when one review for a specific product is written in the review item 615, the management server 403 may count the “number of reviews” once.

For example, referring to <603> of FIG. 6 , the “number of inquiries” for a specific product 610 indicates the number of times an inquiry is made for a specific product 610, and a plurality of user devices 401a, 401b, 401c), when one inquiry for a specific product is created in the Q&A item 616, the management server 403 may count the "number of inquiries" once.

For example, referring to <602> of FIG. 6 , “the number of payment completions” for a specific product 610 indicates the number of times payment has been successfully completed for a specific product 610, and a plurality of user devices ( When the payment item 617 is selected by 401a, 401b, 401c) and the payment for the specific product 610 is successfully completed by one of the prescribed methods (eg, card payment, direct deposit, simple pay, etc.), management The server 403 may count the "number of payments" once.

According to an embodiment, the management server 403 sets the management server 403 for a specific period (eg, within 7 days from the current time) indicating a period for analyzing the specific product 610 from the manager of the management server 403 . ) through an input interface (or input means), and selection information acquired during the specific period from among all selection information for a specific product 610 acquired from a plurality of user devices 401a, 401b, and 401c can be selected and/or checked. In this case, the selection information may be information based on a selection by an administrator of the management server 403 and/or information indicating a target selected by the administrator.

In operation 503 , according to various embodiments, the management server 403 (eg, the processor 120 of FIG. 1 ) may be referred to as a prediction period (or "monitoring period" or "observation period") related to a specific product. can be identified. According to an embodiment, the management server 403 may receive a prediction period related to a specific product from the manager of the management server 403 . The prediction period related to the specific product is a period in which the manager intends to predict the expected sales volume for the specific product 610 , and a predetermined period (eg, 7 days after the current time) may be input by the manager.

As another example, the management server 403 (eg, the processor 120 of FIG. 1 ) calculates a prediction period (or may be referred to as a “monitoring period” or “observation period”) related to a specific product (= time) in the following mathematics It can be calculated and/or calculated through Equation 1.

[Equation 1]

In this case, t _d represents the average of the time it takes users (customers) to access the shopping mall (and/or online platform) of the present invention and make a purchase (ie, final payment), and n _d is the shopping mall (and/or online platform) of the present invention. / or online platform) the number of products belonging to the same category as a specific product among all products being sold, n _t is the total number of products sold in the shopping mall (and/or online platform) of the present invention, n _c is the number of products being accessed The number of users (customers), ta _a , represents an average time until the users (customers) put a specific product into a shopping cart and purchase (ie, final payment) in the shopping mall (and/or online platform) of the present invention. Meanwhile, the units of time, t _d , and ta _a may be identically set to any one of seconds, minutes, and hours. In addition, N and M correspond to an arbitrary value (eg, '1' or '2', etc.) or a constant value set by the management server 403 (eg, the processor 120 of FIG. 1 ) according to a predetermined criterion. and the values of N and M may be adjusted by '+1', '+2' or '-1' and '-2' according to the input of the administrator.

In operation 505, according to various embodiments, the management server 403 (eg, the processor 120 of FIG. 1 ) selects information and a specific product for the specific product 610 in the artificial intelligence model for estimating the expected sales volume By applying the prediction period related to 610 , it is possible to calculate a first expected sales volume for which the specific product 610 will be sold during the prediction period.

For example, referring to FIG. 7 , the management server 403 controls the specific product ( 610) and the prediction period related to the specific product 610 may be applied to the AI model 700 as input data 701, and the prediction period as output data 702 of the AI model Information on weights for each expected sales volume (eg, A, B, C, D, etc.) for a specific product 610 during the period may be obtained. In this case, the management server 403 selects the expected sales volume 710 (eg, B) having the highest weight from among the weight information for each predicted sales volume for a specific product 610 during the forecast period, and selects the selected The expected sales volume 710 may be determined as the first predicted sales volume ( 703 ). The operation of generating and learning the artificial intelligence model 700 will be described later with reference to FIG. 8 .

In operation 507 , according to various embodiments, the management server 403 (eg, the processor 120 of FIG. 1 ) determines the specific product 610 based on the current inventory amount and the first expected sales volume of the specific product 610 . Order quantity can be calculated.

According to an embodiment, the management server 403 determines the order amount of the specific product 610 by applying a predetermined ratio to the quantity obtained by subtracting the current inventory amount of the specific product 610 from the first expected sales volume of the specific product 610 . can be calculated. For example, the management server 403 sets a ratio (eg, N) to the quantity obtained by subtracting the current inventory amount (eg, N) of the specific product 610 from the first expected sales volume (eg, B) of the specific product 610 . : K%) as the quantity (eg (B-N)*K*0.01) may be determined as the order quantity of the specific product 610 . The predetermined ratio may be selected by an administrator of the management server 403 .

In operation 509 , according to various embodiments, the management server 403 (eg, the processor 120 of FIG. 1 ) is a message requesting delivery of a specific product 610 based on the order amount for the specific product 610 . may be transmitted to the product providing server (eg, the product providing server 402 of FIG. 4 ). For example, the management server 403 automatically provides a message including an order requesting delivery of a specific product 610 equal to the order amount to a specified address (eg, the business address of the management server 403). can be sent to the server 402 .

FIG. 8 is a diagram for explaining an operation of learning an artificial intelligence model in order to estimate the expected sales volume for a specific product, and FIG. 9 is a diagram for explaining an embodiment of learning the artificial intelligence model.

According to various embodiments, the management server 403 (eg, the processor 120 of FIG. 1 ) is artificial intelligence for estimating the expected sales volume during the forecast period for each product, as shown in 801 of FIG. 8 . In order to generate a model (eg, the artificial intelligence model 700 of FIG. 7 ), selection information for each product and sales volume information of each product may be obtained from a memory (eg, the memory 130 of FIG. 1 ). The selection information for each product may include the number of times of selecting detailed information of each product, the number of additions to the shopping cart, the number of registrations of interested products, the number of reviews, the number of inquiries, and the number of payment completion times. The sales volume information for each product may mean the number determined that the purchase of each product is confirmed and the sale is completed for each product.

The AI model may utilize various models such as Recurrent Neural Network (RNN), Deep Neural Network (DNN), and Dynamic Recurrent Neural Network (DRNN). Here, RNN is a deep learning technique that simultaneously considers current data and past data. A recurrent neural network (RNN) represents a neural network in which connections between units constituting an artificial neural network constitute a directed cycle. Furthermore, various methods may be used for a structure capable of constructing a recurrent neural network (RNN), for example, a fully recurrent network, a hopfield network, an Elman network, an ESN (Echo). State network), long short term memory network (LSTM), bi-directional RNN, continuous-time RNN (CTRNN), hierarchical RNN, and secondary RNN are representative examples. In addition, as a method for learning a recurrent neural network (RNN), methods such as gradient descent, Hessian Free Optimization, and Global Optimization Method may be used.

According to various embodiments, the management server 403 (eg, the processor 120 of FIG. 1 ) as shown in 802 of FIG. 8 , artificial intelligence for selection information for each product and sales volume information for each product In the model 700 , it can be processed into a learnable form (eg, text information is assigned to a specific value capable of matrix operation and pre-processed). According to an embodiment, the management server 403 processes selection information for each product for each period before a specific time and sales volume information for each product for each period after a specific time into a form that can be learned from the artificial intelligence model 700 . can do.

According to various embodiments, the management server 403 (eg, the processor 120 of FIG. 1 ), as shown in 803 of FIG. 8 , includes selection information and specific The artificial intelligence model 700 may be generated by using the sales volume information for each product for each period after the time point as training data.

According to an embodiment, the management server 403 sets selection information for each product for each period before a specific time point as input data, and sales volume (eg, A) of each product for each period after the specific time point. Dogs, B dogs, C dogs) are set as output data, and learning (eg, weight learning 810) of the AI model 700 based on various types of AI learning algorithms is performed. can be done For example, referring to FIG. 9 , the management server 403 sets selection information for each product during the first previous period 901 before the specific time point 900 as input data, and the specific time point 900 . ) after a first sales volume of each product during a first subsequent period 904 , a second sales volume of each product during a second subsequent period 905 , and a third sales volume of each product during a third subsequent period 906 . can be set as output data to train the artificial intelligence model 700 .

For another example, referring to FIG. 9 , the management server 403 sets selection information for each product during the second previous period 902 before the specific time point 900 as input data, and the specific time point 900 . A first sales volume of each product during a first subsequent period 904 after 900 , a second sales volume of each product during a second subsequent time period 905 , and a third sales volume of each product during a third subsequent period 906 . 3 It is possible to train the artificial intelligence model 700 by setting the sales volume as output data.

For another example, referring to FIG. 9 , the management server 403 sets the selection information for each product during the third previous period 903 before the specific time 900 as input data, and the specific time point 900 . A first sales volume of each product during a first subsequent period 904 after 900 , a second sales volume of each product during a second subsequent time period 905 , and a third sales volume of each product during a third subsequent period 906 . 3 It is possible to train the artificial intelligence model 700 by setting the sales volume as output data. According to an embodiment, the artificial intelligence model 700 may perform weight learning by classifying each product. Since the aforementioned AI learning algorithm may include various types of well-known machine learning and deep learning algorithms, a detailed description thereof will be omitted. At this time, according to the learning, the generated artificial intelligence model 700 responds to input of selection information for a specific product acquired during a specific period and a prediction period related to the specific product, the specific product will be sold during the prediction period. It may be implemented to finally output a weight for the expected sales volume. For example, the artificial intelligence model 700 includes layers including weight values for calculating this in response to input of selection information for a specific product acquired during a specific period and a prediction period related to the specific product, and , may be implemented to output a weight for the expected sales volume as output data by performing an operation in each of the layers.

According to various embodiments, a system for providing an inventory management service includes a plurality of user devices, a product providing server, and a management server, wherein the management server includes a specific information obtained from the plurality of user devices during a specific period. Identifies selection information for a product - The selection information for the specific product includes the number of selections of detailed information of the specific product, the number of additions to the shopping cart, the number of registrations of the product of interest, the number of reviews, the number of inquiries, and the number of payment completion- , by applying the selection information for the specific product and the prediction period related to the specific product to an artificial intelligence model for identifying a forecast period related to the specific product and estimating the expected sales volume, during the forecast period calculating the first expected sales volume to be sold, calculating an order quantity of the specific product based on the current inventory amount and the first expected sales volume of the specific product, and calculating the order amount of the specific product based on the order amount for the specific product It may be set to transmit a message requesting delivery to the product providing server.

According to various embodiments, the number of times of selecting the detailed information of the specific product is that the specific product is selected by the plurality of user devices from the product list including the information on the plurality of products and the details of the specific product represents the number of times of displaying information, the number of times of adding the specific product to the shopping cart represents the number of times the specific product is added to the shopping cart by the plurality of user devices, and the number of times of registering the product of interest of the specific product is, Indicates the number of times the specific product is registered as a product of interest by a plurality of user devices, the number of reviews for the specific product indicates the number of times that a review for the specific product is written, and the number of inquiries about the specific product may indicate the number of times an inquiry is made for the specific product, and the number of payment completions for the specific product may indicate the number of times payment for the specific product has been successfully completed.

According to various embodiments, the management server obtains information about a weight for each expected sales volume for the specific product during the prediction period as output data of the artificial intelligence model, and a weight is It may be set to determine the highest expected sales volume as the first predicted sales volume.

According to various embodiments, the management server may be configured to determine the order amount of the specific product by applying a predetermined ratio to a quantity obtained by subtracting the current inventory amount from the first expected sales volume.

According to various embodiments, the management server may be configured to obtain selection information for each product and sales volume information for each product from the memory of the management server.

According to various embodiments, the management server sets selection information for each product for each period before a specific time as input data, and sets the sales volume of each product for each period after the specific time as output data, It can be set to perform learning of an artificial intelligence model.

Meanwhile, the electronic device 101 will be described again with reference to FIGS. 1 to 3 .

In some embodiments, the electronic device 101 may omit at least one of the components or may additionally include other components. The bus 110 may include a circuit that connects the components 110 - 170 to each other and transmits communication (eg, a control message or data) between the components. The processor 120 may include one or more of a central processing unit, an application processor, and a communication processor (CP). The processor 120 may, for example, execute an operation or data processing related to control and/or communication of at least one other component of the electronic device 101 .

The memory 130 may include volatile and/or non-volatile memory. The memory 130 may store, for example, commands or data related to at least one other component of the electronic device 101 . According to one embodiment, the memory 130 may store software and/or a program 140 . Program 140 may include, for example, kernel 141 , middleware 143 , application programming interface (API) 145 , and/or application program (or “application”) 147 , etc. . At least a portion of the kernel 141 , the middleware 143 , or the API 145 may be referred to as an operating system. The kernel 141 is, for example, system resources (eg, middleware 143, API 145, or application program 147) used to execute an operation or function implemented in other programs (eg, middleware 143, API 145, or the application program 147). : The bus 110, the processor 120, the memory 130, etc.) can be controlled or managed. In addition, the kernel 141 may provide an interface capable of controlling or managing system resources by accessing individual components of the electronic device 101 from the middleware 143 , the API 145 , or the application program 147 . can

The middleware 143 may, for example, play an intermediary role so that the API 145 or the application program 147 communicates with the kernel 141 to send and receive data. Also, the middleware 143 may process one or more work requests received from the application program 147 according to priority. For example, the middleware 143 may use a system resource (eg, the bus 110 , the processor 120 , or the memory 130 ) of the electronic device 101 for at least one of the application programs 147 . It can give priority and process the one or more work requests. The API 145 is an interface for the application 147 to control a function provided by the kernel 141 or the middleware 143, for example, at least for file control, window control, image processing, or character control. It can contain one interface or function (eg command). The input/output interface 150 transmits, for example, a command or data input from a user or other external device to other component(s) of the electronic device 101 , or another component ( ) can output a command or data received from the user or other external device.

Display 160 may include, for example, a liquid crystal display (LCD), a light emitting diode (LED) display, an organic light emitting diode (OLED) display, or a microelectromechanical system (MEMS) display, or an electronic paper display. may include The display 160 may, for example, display various contents (eg, text, images, videos, icons, and/or symbols, etc.) to the user. The display 160 may include a touch screen, and may receive, for example, a touch, gesture, proximity, or hovering input using an electronic pen or a part of the user's body. The communication interface 170, for example, sets up communication between the electronic device 101 and an external device (eg, the first external electronic device 102, the second external electronic device 104, or the server 106). can For example, the communication interface 170 may be connected to the network 162 through wireless communication or wired communication to communicate with an external device (eg, the second external electronic device 104 or the server 106 ).

Wireless communication, for example, LTE, LTE Advance (LTE-A), CDMA (code division multiple access), WCDMA (wideband CDMA), UMTS (universal mobile telecommunications system), WiBro (Wireless Broadband), or GSM (Global System for Mobile Communications) may include cellular communication using at least one of. According to one embodiment, the wireless communication is, for example, WiFi (wireless fidelity), Bluetooth, Bluetooth low energy (BLE), Zigbee (Zigbee), NFC (near field communication), magnetic secure transmission (Magnetic Secure Transmission), radio It may include at least one of a frequency (RF) or a body area network (BAN). According to one embodiment, the wireless communication may include GNSS. The GNSS may be, for example, a Global Positioning System (GPS), a Global Navigation Satellite System (Glonass), a Beidou Navigation Satellite System (hereinafter, “Beidou”) or Galileo, the European global satellite-based navigation system. Hereinafter, in this document, "GPS" may be used interchangeably with "GNSS". Wired communication may include, for example, at least one of universal serial bus (USB), high definition multimedia interface (HDMI), recommended standard232 (RS-232), power line communication, or plain old telephone service (POTS). have. The network 162 may include at least one of a telecommunications network, for example, a computer network (eg, a LAN or WAN), the Internet, or a telephone network.

Each of the first and second external electronic devices 102 and 104 may be the same as or different from the electronic device 101 . According to various embodiments, all or part of the operations executed by the electronic device 101 may be executed by one or a plurality of other electronic devices (eg, the electronic devices 102 and 104 , or the server 106 ). Accordingly, when the electronic device 101 is to perform a function or service automatically or upon request, the electronic device 101 performs at least some functions related thereto instead of or in addition to executing the function or service itself. may request from another device (eg, electronic device 102, 104, or server 106) The other electronic device (eg, electronic device 102, 104, or server 106) may request the requested function or The additional function may be executed and the result may be transmitted to the electronic device 101. The electronic device 101 may provide the requested function or service by processing the received result as it is or additionally. For example, cloud computing, distributed computing, or client-server computing technology may be used.

2 is a block diagram of an electronic device 201 according to various embodiments. The electronic device 201 may include, for example, all or a part of the electronic device 101 illustrated in FIG. 1 . The electronic device 201 includes one or more processors (eg, AP) 210 , a communication module 220 , a (subscriber identification module 224 , a memory 230 , a sensor module 240 , an input device 250 , and a display). 260 , an interface 270 , an audio module 280 , a camera module 291 , a power management module 295 , a battery 296 , an indicator 297 , and a motor 298 . The 210 may control a plurality of hardware or software components connected to the processor 210 by, for example, driving an operating system or an application program, and may perform various data processing and operations. ) may be implemented by, for example, a system on chip (SoC) According to an embodiment, the processor 210 may further include a graphic processing unit (GPU) and/or an image signal processor. The 210 may include at least some (eg, the cellular module 221) of the components shown in Fig. 2. The processor 210 may include at least one of the other components (eg, a non-volatile memory). The received command or data may be loaded into volatile memory for processing, and the resulting data may be stored in non-volatile memory.

The communication module 220 (eg, the communication interface 170) may have the same or similar configuration. The communication module 220 may include, for example, a cellular module 221 , a WiFi module 223 , a Bluetooth module 225 , a GNSS module 227 , an NFC module 228 , and an RF module 229 . have. The cellular module 221 may provide, for example, a voice call, a video call, a text service, or an Internet service through a communication network. According to an embodiment, the cellular module 221 may use a subscriber identification module (eg, a SIM card) 224 to identify and authenticate the electronic device 201 within a communication network. According to an embodiment, the cellular module 221 may perform at least some of the functions that the processor 210 may provide. According to one embodiment, the cellular module 221 may include a communication processor (CP). According to some embodiments, at least some (eg, two or more) of the cellular module 221 , the WiFi module 223 , the Bluetooth module 225 , the GNSS module 227 , or the NFC module 228 is one integrated chip. (IC) or contained within an IC package. The RF module 229 may transmit/receive a communication signal (eg, an RF signal), for example. The RF module 229 may include, for example, a transceiver, a power amp module (PAM), a frequency filter, a low noise amplifier (LNA), or an antenna. According to another embodiment, at least one of the cellular module 221 , the WiFi module 223 , the Bluetooth module 225 , the GNSS module 227 or the NFC module 228 transmits and receives an RF signal through a separate RF module. can The subscriber identification module 224 may include, for example, a card including a subscriber identification module or an embedded SIM, and may include unique identification information (eg, integrated circuit card identifier (ICCID)) or subscriber information (eg, IMSI). (international mobile subscriber identity)).

The memory 230 (eg, the memory 130 ) may include, for example, an internal memory 232 or an external memory 234 . The internal memory 232 may include, for example, a volatile memory (eg, DRAM, SRAM, or SDRAM, etc.), a non-volatile memory (eg, one time programmable ROM (OTPROM), PROM, EPROM, EEPROM, mask ROM, flash ROM). , a flash memory, a hard drive, or a solid state drive (SSD), etc. The external memory 234 may include a flash drive, for example, a compact flash (CF) or secure digital (SD). ), Micro-SD, Mini-SD, xD (extreme digital), MMC (multi-media card), memory stick, etc. The external memory 234 is functional with the electronic device 201 through various interfaces. may be physically or physically connected.

The sensor module 240 may, for example, measure a physical quantity or sense an operating state of the electronic device 201 , and convert the measured or sensed information into an electrical signal. The sensor module 240 is, for example, a gesture sensor 240A, a gyro sensor 240B, a barometric pressure sensor 240C, a magnetic sensor 240D, an acceleration sensor 240E, a grip sensor 240F, a proximity sensor ( 240G), color sensor (240H) (e.g. RGB (red, green, blue) sensor), biometric sensor (240I), temperature/humidity sensor (240J), illuminance sensor (240K), or UV (ultra violet) sensor ) may include at least one of the sensors 240M. Additionally or alternatively, the sensor module 240 may include, for example, an olfactory (e-nose) sensor, an electromyography (EMG) sensor, an electroencephalogram (EEG) sensor, an electrocardiogram (ECG) sensor, It may include an infrared (IR) sensor, an iris sensor, and/or a fingerprint sensor. The sensor module 240 may further include a control circuit for controlling at least one or more sensors included therein. In some embodiments, the electronic device 201 further comprises a processor configured to control the sensor module 240 , either as part of the processor 210 or separately, while the processor 210 is in a sleep state; The sensor module 240 may be controlled.

The input device 250 may include, for example, a touch panel 252 , a (digital) pen sensor 254 , a key 256 , or an ultrasonic input device 258 . The touch panel 252 may use, for example, at least one of a capacitive type, a pressure sensitive type, an infrared type, and an ultrasonic type. Also, the touch panel 252 may further include a control circuit. The touch panel 252 may further include a tactile layer to provide a tactile response to the user. The (digital) pen sensor 254 may be, for example, a part of a touch panel or may include a separate recognition sheet. Key 256 may include, for example, a hardware button, an optical key, or a keypad. The ultrasonic input device 258 may detect an ultrasonic wave generated by an input tool through a microphone (eg, the microphone 288 ), and check data corresponding to the sensed ultrasonic wave.

Display 260 (eg, display 160 ) may include panel 262 , hologram device 264 , projector 266 , and/or control circuitry for controlling them. Panel 262 may be implemented, for example, to be flexible, transparent, or wearable. The panel 262 may include the touch panel 252 and one or more modules. According to an embodiment, the panel 262 may include a pressure sensor (or a force sensor) capable of measuring the intensity of the user's touch. The pressure sensor may be implemented integrally with the touch panel 252 or as one or more sensors separate from the touch panel 252 . The hologram device 264 may display a stereoscopic image in the air by using light interference. The projector 266 may display an image by projecting light onto the screen. The screen may be located inside or outside the electronic device 201 , for example. Interface 270 may include, for example, HDMI 272 , USB 274 , optical interface 276 , or D-subminiature (D-sub) 278 . The interface 270 may be included in, for example, the communication interface 170 shown in FIG. 1 . Additionally or alternatively, the interface 270 may include, for example, a mobile high-definition link (MHL) interface, an SD card/multi-media card (MMC) interface, or an infrared data association (IrDA) standard interface. have.

The audio module 280 may interactively convert a sound and an electrical signal, for example. At least some components of the audio module 280 may be included in, for example, the input/output interface 145 illustrated in FIG. 1 . The audio module 280 may process sound information input or output through, for example, the speaker 282 , the receiver 284 , the earphone 286 , or the microphone 288 . The camera module 291 is, for example, a device capable of photographing still images and moving images, and according to an embodiment, one or more image sensors (eg, a front sensor or a rear sensor), a lens, and an image signal processor (ISP). , or a flash (eg, an LED or xenon lamp, etc.). The power management module 295 may manage power of the electronic device 201 , for example. According to an embodiment, the power management module 295 may include a power management integrated circuit (PMIC), a charger IC, or a battery or fuel gauge. The PMIC may have a wired and/or wireless charging method. The wireless charging method includes, for example, a magnetic resonance method, a magnetic induction method, or an electromagnetic wave method, and may further include an additional circuit for wireless charging, for example, a coil loop, a resonance circuit, or a rectifier. have. The battery gauge may measure, for example, the remaining amount of the battery 296 , voltage, current, or temperature during charging. Battery 296 may include, for example, rechargeable cells and/or solar cells.

The indicator 297 may display a specific state of the electronic device 201 or a part thereof (eg, the processor 210 ), for example, a booting state, a message state, or a charging state. The motor 298 may convert an electrical signal into mechanical vibration, and may generate vibration, a haptic effect, or the like. The electronic device 201 is, for example, a mobile TV support device capable of processing media data according to standards such as digital multimedia broadcasting (DMB), digital video broadcasting (DVB), or mediaFlo ^TM (eg, digital multimedia broadcasting). : GPU). Each of the components described in this document may be composed of one or more components, and the name of the component may vary depending on the type of the electronic device. In various embodiments, the electronic device (eg, the electronic device 201 ) is configured as a single entity by omitting some components, further including additional components, or combining some of the components. The functions of the previous corresponding components may be performed identically.

In various embodiments of the present disclosure, the electronic device 201 (or the electronic device 101 ) may include a housing including a front surface, a rear surface, and side surfaces surrounding a space between the front surface and the rear surface. A touch screen display (eg, the display 260 ) may be disposed in the housing and exposed through the front surface. A microphone 288 is disposed within the housing and may be exposed through a portion of the housing. At least one speaker 282 is disposed in the housing, and may be exposed through another portion of the housing. A hardware button (eg, key 256 ) may be disposed on another portion of the housing or configured to be displayed on the touchscreen display. A wireless communication circuit (eg, the communication module 220) may be located in the housing. The processor 210 (or processor 120 ) may be located in the housing and may be electrically connected to the touch screen display, the microphone 288 , the speaker 282 , and the wireless communication circuitry. The memory 230 (or the memory 130 ) may be located in the housing and may be electrically connected to the processor 210 .

In various embodiments of the present disclosure, the memory 230 is configured to store a first application program including a first user interface for receiving a text input, and the memory 230, when executed, Stores instructions causing the processor 210 to perform a first operation and a second operation, wherein the first operation is performed through the button while the first user interface is not displayed on the touch screen display. Receive a first type of user input, and after receiving the first type of user input, receive a first user utterance through the microphone 288, automatic speech recognition (ASR) and intelligence providing first data on the first user utterance to an external server including an intelligence system, and after providing the first data, the intelligent system in response to the first user utterance from the external server receiving at least one command to perform a task generated by , after receiving the first type of user input, receive a second user utterance through the microphone 288, provide second data for the second user utterance to the external server, and After providing data, receiving, from the server, data for the text generated by the automatic speech recognition from the second user utterance, but not receiving a command generated by the intelligent system, the first user The text can be entered into the interface.

In various embodiments of the present invention, the button may include a physical key located on the side of the housing.

In various embodiments of the present disclosure, the first type of user input may be performed after pressing the button once, pressing the button twice, pressing the button 3 times, and pressing the button once. It may be one of a press and hold, or a double press and hold press of the button.

In various embodiments of the present disclosure, the instructions may further cause the processor to display the first user interface with a virtual keyboard. The button may not be part of the virtual keyboard.

In various embodiments of the present disclosure, the instructions further cause the processor 210 to receive, from the external server, data for text generated by ASR from the first user utterance within the first operation. can cause

In various embodiments of the present disclosure, the first application program may include at least one of a note application program, an email application program, a web browser application program, and a calendar application program.

In various embodiments of the present disclosure, the first application program includes a message application, and the instructions include, when the processor 210 exceeds a selected time period after inputting the text, the wireless communication circuit It may further cause to transmit the text entered automatically through .

In various embodiments of the present disclosure, the instructions further cause the processor 210 to perform a third operation, wherein the third operation is performed while displaying the first user interface on the touch screen display. , receives a second type of user input through the button, and after receiving the second type of user input, receives a third user utterance through the microphone, and receives the third user utterance through the external server. may receive from the external server at least one command for performing a task generated by the intelligent system in response to the third user utterance after providing the third data for have.

In various embodiments of the present disclosure, the instructions further cause the processor 210 to perform a fourth operation, wherein the fourth operation is performed when the first user interface is not displayed on the touch screen display. On the way, the second type of user input is received through the button, and after receiving the second type of user input, a fourth user utterance is received through the microphone 288, and the fourth user utterance is received. provide fourth data for , to the external server, and after providing the fourth data, in response to the fourth user utterance, at least one command for performing the task generated by the intelligent system, the After receiving from an external server, receiving a fifth user utterance through the microphone, providing fifth data for the fifth user utterance to the external server, and providing the fifth data, the second 5 at least one command for performing the task generated by the intelligent system in response to the user's utterance may be received from the external server.

In various embodiments of the present invention, the first type of user input and the second type of user input are different from each other, and one press on the button, two presses on the button, three presses on the button , one of pressing and holding the button after pressing it once, or pressing and holding the press twice on the button.

In various embodiments of the present disclosure, the memory 230 is further configured to store a second application program including a second user interface for receiving a text input, and the instructions, when executed, include the processor ( 210) further causes a third operation to be performed, wherein the third operation receives the first type of user input through the button while displaying the second user interface, and the first type of user After the input is received, the third user utterance is received through the microphone, the third data for the third user utterance is provided to the external server, and after the third data is provided, the external receiving, from a server, data for text generated by ASR from the third user utterance, without receiving a command generated by the intelligent system, and inputting the text into the second user interface, and the text , and when the selected time period is exceeded, the inputted text may be automatically transmitted through the wireless communication circuit.

In various embodiments of the present disclosure, the memory 230 is configured to store a first application program including a first user interface for receiving a text input, and the memory 230, when executed, Stores instructions causing the processor 210 to perform a first operation and a second operation, wherein the first operation receives a first type of user input through the button, and the first type of user input After receiving , the first user utterance is received through the microphone 288, and to an external server including an automatic speech recognition (ASR) and an intelligence system, the first user utterance is received. and, after providing the first data, receive from the external server at least one command for performing a task generated by the intelligent system in response to the first user utterance and, the second operation includes receiving a second type of user input through the button, receiving a second user utterance through the microphone 288 after receiving the second type of user input, After providing the second data for the second user utterance to the external server, and after providing the second data, receiving data about the text generated by ASR from the second user utterance from the server , a command generated by the intelligent system may not be received, and the text may be entered into the first user interface.

In various embodiments of the present disclosure, the instructions may further cause the processor 210 to display the first user interface together with a virtual keyboard, wherein the button may not be part of the virtual keyboard.

In various embodiments of the present invention, the instructions further cause the processor 210 to receive data for the text generated by the ASR from the first user utterance within the first operation from the external server. can do.

In various embodiments of the present disclosure, the first application program may include at least one of a note application program, an email application program, a web browser application program, and a calendar application program.

In various embodiments of the present disclosure, the first application program includes a message application, and the instructions include, when the processor 210 exceeds a selected time period after inputting the text, the wireless communication circuit It may further cause to transmit the text entered automatically through .

In various embodiments of the present disclosure, the instructions may further cause the processor 210 to perform the first operation independently of displaying on the display of the first user interface.

In various embodiments of the present disclosure, the instructions perform the second operation when the processor 210 is at least one of a locked state of the electronic device or a turned off of the touch screen display. may cause more

In various embodiments of the present disclosure, the instructions may further cause the processor 210 to perform the second operation while displaying the first user interface on the touch screen display.

In various embodiments of the present invention, the memory 230, when executed, causes the processor 210 to receive a user utterance through the microphone 288, perform automatic speech recognition (ASR) or It is an external server that performs at least one of natural language understanding (NLU), and performs the ASR on the data for the user's utterance together with the data on the user's utterance, and performs the ASR on the data obtained for the natural language understanding. send information associated with whether to perform the natural language understanding , it is possible to store an instruction for causing to receive a command obtained as a result of performing the natural language understanding on the text from the external server.

3 is a block diagram of a program module according to various embodiments of the present disclosure; According to one embodiment, the program module 310 (eg, the program 140) is an operating system that controls resources related to the electronic device (eg, the electronic device 101) and/or various applications ( For example, the application program 147) may be included. The operating system may include, for example, Android ^TM , iOS ^TM , Windows ^TM , Symbian ^TM , Tizen ^TM , or Bada ^TM . Referring to FIG. 3 , the program module 310 includes a kernel 320 (eg, kernel 141), middleware 330 (eg, middleware 143), (API 360) (eg, API 145). ), and/or an application 370 (eg, an application program 147). At least a portion of the program module 310 is preloaded on the electronic device, or an external electronic device (eg, the electronic device ( 102, 104), server 106, etc.).

The kernel 320 may include, for example, a system resource manager 321 and/or a device driver 323 . The system resource manager 321 may control, allocate, or recover system resources. According to an embodiment, the system resource manager 321 may include a process manager, a memory manager, or a file system manager. The device driver 323 may include, for example, a display driver, a camera driver, a Bluetooth driver, a shared memory driver, a USB driver, a keypad driver, a WiFi driver, an audio driver, or an inter-process communication (IPC) driver. . The middleware 330 provides, for example, functions commonly required by the applications 370 or provides various functions through the API 360 so that the applications 370 can use limited system resources inside the electronic device. It may be provided as an application 370 . According to one embodiment, the middleware 330 includes a runtime library 335 , an application manager 341 , a window manager 342 , a multimedia manager 343 , a resource manager 344 , a power manager 345 , and a database manager ( 346 ), a package manager 347 , a connectivity manager 348 , a notification manager 349 , a location manager 350 , a graphic manager 351 , or a security manager 352 .

The runtime library 335 may include, for example, a library module used by the compiler to add a new function through a programming language while the application 370 is being executed. The runtime library 335 may perform input/output management, memory management, or arithmetic function processing. The application manager 341 may, for example, manage the life cycle of the application 370 . The window manager 342 may manage GUI resources used in the screen. The multimedia manager 343 may identify a format required to reproduce the media files, and may encode or decode the media files using a codec suitable for the format. The resource manager 344 may manage the space of the source code or memory of the application 370 . The power manager 345 may, for example, manage a capacity or power of a battery and provide power information required for an operation of an electronic device. According to an embodiment, the power manager 345 may interwork with a basic input/output system (BIOS). The database manager 346 may create, search, or change a database to be used in the application 370 , for example. The package manager 347 may manage installation or update of an application distributed in the form of a package file.

The connectivity manager 348 may manage wireless connections, for example. The notification manager 349 may provide the user with events such as, for example, arrival messages, appointments, and proximity notifications. The location manager 350 may manage location information of the electronic device, for example. The graphic manager 351 may manage a graphic effect to be provided to a user or a user interface related thereto, for example. Security manager 352 may provide, for example, system security or user authentication. According to an embodiment, the middleware 330 may include a telephony manager for managing the voice or video call function of the electronic device or a middleware module capable of forming a combination of functions of the aforementioned components. . According to an embodiment, the middleware 330 may provide a specialized module for each type of operating system. The middleware 330 may dynamically delete some existing components or add new components. The API 360 is, for example, a set of API programming functions, and may be provided in different configurations depending on the operating system. For example, in the case of Android or iOS, one API set may be provided for each platform, and in the case of Tizen, two or more API sets may be provided for each platform.

The application 370 is, for example, home 371 , dialer 372 , SMS/MMS 373 , instant message (IM) 374 , browser 375 , camera 376 , alarm 377 . , contact (378), voice dial (379), email (380), calendar (381), media player (382), album (383), watch (384), health care (e.g., measuring exercise or blood sugar) , or an application for providing environmental information (eg, barometric pressure, humidity, or temperature information). According to an embodiment, the application 370 may include an information exchange application capable of supporting information exchange between the electronic device and an external electronic device. The information exchange application may include, for example, a notification relay application for transmitting specific information to an external electronic device, or a device management application for managing the external electronic device. For example, the notification delivery application may transmit notification information generated by another application of the electronic device to the external electronic device or may receive notification information from the external electronic device and provide the notification information to the user. The device management application is, for example, a function of the external electronic device communicating with the electronic device (eg, turn-on/turn-off of the external electronic device itself (or some component) or the brightness (or resolution) of the display. adjustment), or an application running in an external electronic device may be installed, deleted, or updated. According to an embodiment, the application 370 may include an application (eg, a health management application of a mobile medical device) designated according to a property of the external electronic device. According to an embodiment, the application 370 may include an application received from an external electronic device. At least a portion of the program module 310 may be implemented (eg, executed) in software, firmware, hardware (eg, processor 210), or a combination of at least two or more thereof, a module for performing one or more functions; It may include a program, routine, instruction set, or process.

As used herein, the term “module” includes a unit composed of hardware, software, or firmware, and may be used interchangeably with terms such as, for example, logic, logic block, component, or circuit. A “module” may be an integrally formed component or a minimum unit or a part of performing one or more functions. A “module” may be implemented mechanically or electronically, for example, known or to be developed, application-specific integrated circuit (ASIC) chips, field-programmable gate arrays (FPGAs), or It may include a programmable logic device. At least a portion of an apparatus (eg, modules or functions thereof) or a method (eg, operations) according to various embodiments includes instructions stored in a computer-readable storage medium (eg, memory 130 ) in the form of a program module can be implemented as When the instruction is executed by a processor (eg, the processor 120), the processor may perform a function corresponding to the instruction. Computer-readable recording media include hard disks, floppy disks, magnetic media (eg, magnetic tape), optical recording media (eg, CD-ROM, DVD, magneto-optical media (eg, floppy disks), built-in memory, etc.) An instruction may include a code generated by a compiler or a code that can be executed by an interpreter A module or program module according to various embodiments may include at least one or more of the above-described components or , some may be omitted, or may further include other components According to various embodiments, operations performed by a module, a program module, or other components are sequentially, parallelly, repetitively or heuristically executed, or at least Some operations may be executed in a different order, omitted, or other operations may be added.

In addition, the embodiments disclosed in this document are provided for description and understanding of the disclosed, technical content, and do not limit the scope of the present disclosure. Accordingly, the scope of the present disclosure should be construed to include all modifications or various other embodiments based on the technical spirit of the present disclosure.

Claims (5)

In the system for providing an inventory management service,
a plurality of user devices for connecting the inventory management service to an online platform;
product providing server; and
a management server for providing the online platform; including,
The management server is:
An artificial intelligence model for estimating the expected sales volume is trained, and the selection information for each product during the first previous period before a specific time is inputted to the artificial intelligence model as learning data set as input data to create the artificial intelligence model. and output data of the first sales volume of each product in the first and subsequent periods after the specific point in time, the second sales volume of each product in the second and subsequent periods, and the third sales volume of each product in the third and subsequent periods The artificial intelligence model is learned by inputting it into the artificial intelligence model as learning data set as including the number of times, the number of registrations of products of interest, the number of reviews, the number of inquiries, and the number of payment completions;
Receive selection information for a specific product acquired during a specific period from the plurality of user devices,
Calculate the monitoring period (time) related to the specific product through Equation 1 below,
By applying the selection information for the specific product and the monitoring period related to the specific product to the artificial intelligence model, calculating a first expected sales volume in which the specific product will be sold during the monitoring period,
calculating an order amount of the specific product based on the current inventory amount of the specific product and the first expected sales volume;
set to transmit a message requesting delivery of the specific product to the product providing server based on the order amount for the specific product;
[Equation 1]

t _d represents the average of the time it takes users to access and purchase the online platform, n _d is the number of products belonging to the same category as the specific product among all products sold on the online platform, n _t is the total number of products sold on the online platform, n _c is the number of users accessing the online platform, t _a is the average time it takes for users to put a specific product in their shopping cart and purchase it on the online platform,
N and M are constant values arbitrarily set by the management server, and are adjusted according to the input of the administrator,
The management server is:
Obtaining information on weights for each expected sales volume for the specific product during the monitoring period as output data of the artificial intelligence model,
determining the expected sales volume having the highest weight among the information on the weight as the first expected sales volume;
A system for providing an inventory management service, configured to determine the order amount of the specific product by applying a predetermined ratio to a quantity obtained by subtracting the current inventory amount from the first expected sales volume.
The method of claim 1,
The number of times of selecting detailed information of the specific product indicates the number of times the specific product is selected by the plurality of user devices from the product list including information on all products and the detailed information of the specific product is displayed,
The number of times of adding the specific product to the shopping cart indicates the number of times the specific product is added to the shopping cart by the plurality of user devices,
The number of registration of the product of interest of the specific product indicates the number of times the specific product is registered as a product of interest by the plurality of user devices,
The number of reviews for the specific product indicates the number of times a review is written for the specific product,
The number of inquiries about the specific product indicates the number of times an inquiry has been made for the specific product,
The number of payment completions for the specific product indicates the number of times the payment for the specific product has been successfully completed, a system for providing an inventory management service. delete delete delete

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