KR20210065551A - Server for matching product with buyer and matching system having the same - Google Patents

Abstract

Various embodiments of the present invention relate to an electronic device, which comprises: a communication processor for communicating with at least one user terminal; an input unit for inputting training data in order to learn an artificial neural network model; a learning processor for training the artificial neural network model by using the training data; a memory for storing the artificial neural network model; and at least one processor operably coupled to the communication processor and the memory, wherein the at least one processor stores product design information provided by a first supplier terminal linked to communicate in the memory, stores constructor information provided by a second supplier terminal linked to communicate in the memory, uses an artificial neural network model to determine whether the product design information corresponds to purchase information in response to identification of a first signal related to purchase order and a request for selecting a product provided by the user terminal, processes the product design information corresponding to the purchase information in response to determination of correspondence to transmit the same to the user terminal, transmits a third signal related to payment for the product to the first supplier terminal in response to identification of a second signal related to selection of and payment for the product provided, and transmits a third signal related to the payment for the product to the first supplier terminal, and transmits information corresponding to the purchase information of the constructor information to the user terminal. Accordingly, optimal matching between a product and a user can be performed, based on various pieces of given information.

Description

Electronic device for product and user matching, and matching system including the same {SERVER FOR MATCHING PRODUCT WITH BUYER AND MATCHING SYSTEM HAVING THE SAME}

Various embodiments of the present invention relate to an electronic device for matching a product and a user, and a matching system including the same. More specifically, it relates to an electronic device for matching between a user and a product that helps a user who wants to select a wallpaper and a wallpapering company appropriately select, and a matching system including the same.

With the development of communication technologies and electronic devices, users of electronic devices may purchase items at a shopping mall regardless of place or time. From the seller's point of view, the online shopping mall does not need a space to display products, so space efficiency can be improved. The number of online shopping malls is gradually increasing because users can be freed from the constraints of time and space and space efficiency can be increased for sellers.

In the online shopping mall, advertisements or promotions of products can be made through the evaluation of users on SNS. In particular, young people are accessing shopping malls through applications using smartphones in addition to the existing computers based on information obtained from SNS, etc. With the advent of smartphones, various types of online sales are in progress.

When moving to a new house or performing interior construction, the homeowner (user) can select wallpaper.

According to various embodiments, an electronic device for matching a product and a user and a matching system including the same connect a wallpaper, a plasterer, and a user, so that a user in need of a wallpaper can select and install the wallpaper they want anytime, anywhere can prepare

In the case of an online shopping mall, since the information provided is too broad, a problem may occur in a user's selection of a product, and it may also be difficult to find a contractor suitable for the construction of the product.

Therefore, it is necessary to find a solution that provides an optimal combination based on a variety of given information.

An electronic device according to various embodiments includes a communication processor (CP) for communicating with one or more user terminals, an input unit for inputting training data for learning an artificial neural network model, A learning processor for training the artificial neural network model using the training data, a memory in which the artificial neural network model is stored, and at least one processor operably coupled to the communication processor and the memory, , the memory stores a plurality of instructions, and when the plurality of instructions are executed by the at least one processor, the at least one processor stores the product design information transmitted from the first supplier terminal in the memory. store, store the contractor information transmitted from the second supplier terminal in the memory, and identify the first signal related to the purchase information transmitted from the user terminal and the request to select the product, the identification of the first signal In response, determining whether to correspond to the product design information and the purchase information using the artificial neural network model, and processing the product design information corresponding to the purchase information in response to the determination of whether to correspond, a third signal related to product payment to the first supplier terminal, in response to the identification of the second signal transmitted to the user terminal, and a second signal related to the determination and payment of the delivered product from the user terminal; and transmit information corresponding to the purchase information among the contractor information to the user terminal.

In a method of operating an electronic device according to various embodiments of the present disclosure, product design information transmitted from a first supplier terminal communicatively connected to the electronic device is stored in a memory, and contractor information transferred from a second supplier terminal communicatively connected to the electronic device in response to identifying a first signal related to the operation of storing in the memory, the purchase information transmitted from the user terminal communicatively connected with the electronic device, and the request for selecting a product, the product design information using an artificial neural network model and determining whether to correspond to the purchase information. In response to the determination of whether or not to correspond, processing the product design information corresponding to the purchase information and transmitting the product design information to the user terminal, transmitted from the user terminal In response to identifying a second signal related to product determination and payment, transmitting a third signal related to product payment to the first supplier terminal, and information corresponding to the purchase information among the contractor information to the user terminal It may include the operation of transmitting to .

A matching system and an electronic device for matching according to various embodiments introduce a product (eg, wallpaper) of a desired design to the user based on the user's search history, the user's region and other conventional users Based on their evaluation, it is possible to recommend a contractor (eg, a plasterer) who can install the product.

A matching system and an electronic device for matching according to various embodiments may provide only necessary information to a user from various pieces of information about products and various pieces of information about builders. The user can increase convenience in selecting the recommended product and save time in selecting the product. Even if the user additionally selects a contractor, a contractor who has good access to the construction site while satisfying certain conditions can be recommended, so all work from purchasing a favorite product to actual installation can be solved with a single purchase operation. have.

1 is a block diagram of an electronic device operating in a network environment, according to various embodiments of the present disclosure;
2 is a conceptual diagram of an artificial neural network model constituting an electronic device according to various embodiments of the present disclosure.
3 illustrates a signal flow between an electronic device and a plurality of terminals connected to the electronic device according to various embodiments of the present disclosure.
4A, 4B, and 4C illustrate displaying information related to data sent by an electronic device to a user terminal connected to the electronic device according to various embodiments of the present disclosure;
5A, 5B, and 5C illustrate that an electronic device transmits mapped information to a user terminal according to various embodiments of the present disclosure;

1 is a block diagram of an electronic device operating in a network environment, according to various embodiments of the present disclosure;

The artificial neural network may refer to hardware, software, or a combination thereof for providing a generalized output with respect to an input.

For example, the artificial neural network includes an application for simulating a convolutional neural network (CNN), a Markov chain, or a binarized neural network (BNN), and a processor for executing the application. can work based on

Referring to FIG. 1 , an electronic device 100 (eg, a neural network learning device) is a device capable of performing machine learning through training, and may include a device for learning using a model composed of an artificial neural network. . For example, the neural network device 100 may be configured to input, output, build a database, and store information used for data mining, data analysis, and machine learning algorithms (eg, deep learning algorithms). can

The neural network device 100 may transmit/receive data to and from an external electronic device (not shown) through a communication unit (not shown), and may derive a result value by analyzing or learning data received from the external electronic device. The neural network device 100 may distribute and process the calculation of the external electronic device.

The neural network device 100 may be implemented as a server. In addition, the neural network apparatus 100 may be configured in plurality to form a neural network apparatus set. Each of the neural network devices 100 may process the computation by distributing it, and may derive a result value through data analysis and learning based on the distributed-processed data. The neural network device 100 may transmit a result obtained by using a machine learning algorithm or the like to an external electronic device or another neural network device.

According to various embodiments, the neural network apparatus 100 may include an input unit 110 , a processor 120 , a memory 130 , a learning processor 140 , and a communication processor 150 ( CP).

According to various embodiments, the input unit 110 may obtain input data for deriving an output value through artificial neural network model learning. The input unit 110 may obtain raw input data. The processor 120 or the learning processor 140 may preprocess the raw input data to generate training data that can be input to the artificial neural network model learning. The preprocessing may be to extract a feature point from the input data. As described above, the input unit 110 may receive data through the communication processor 150 to obtain input data or pre-process the data.

According to various embodiments, the processor 120 may collect usage history information from the electronic device 100 and store it in the memory 130 . The processor 120 may determine the best combination for executing a specific function through the stored usage history information and predictive modeling. The processor 120 may receive image information, audio information, data, or user input information from the input unit 110 .

According to various embodiments, the processor 120 may collect information in real time, process or classify the information, and store the processed information in the memory 130 , a database of the memory 130 , or the learning processor 140 . .

According to various embodiments, when the operation of the electronic device 100 is determined based on data analysis and machine learning algorithms, the processor 120 may control components of the electronic device 100 to execute the determined operation. . In addition, the processor 120 may control the electronic device 100 according to the control command to perform the determined operation.

When a specific operation is performed, the processor 120 analyzes historical information indicating the execution of the specific operation through data analysis and machine learning algorithms and techniques, and updates previously learned information based on the analyzed information. can The processor 120 may improve the accuracy of data analysis and machine learning algorithms and performance based on the updated information together with the learning processor 140 .

The memory 130 may store the product design information 131 , the contractor information 132 , the purchase information 133 , and the artificial neural network model 134 .

According to various embodiments, the memory 130 may store the shape, shape, color, location information, or time information of the product obtained from the communication processor 150 or the input unit 110 in the allocated area. According to various embodiments, the memory 130 may store input data obtained from the input unit 110 , learned data, or a learning history. The memory 130 may store a plurality of instructions to be executed by the processor.

According to various embodiments, the artificial neural network model 134 may be stored in a space allocated to the memory 130 . The space allocated to the memory 130 stores the artificial neural network model 134 that is being trained or learned through the learning processor 140, and when the artificial neural network model 134 is updated through learning, the updated artificial neural network model (134) can be stored. The space allocated to the memory 130 may store the learned model by dividing it into a plurality of versions according to a learning time point or learning progress.

According to various embodiments, the memory 130 may include a database capable of storing and classifying input data acquired from the input unit 110 and learned data.

According to various embodiments, the learning processor 140 learns the artificial neural network model 134 by directly acquiring data obtained by preprocessing the input data obtained by the processor 120 through the input unit 110 , or The artificial neural network model 134 may be learned by acquiring preprocessed input data stored in the database. For example, the learning processor 140 may acquire optimized parameters of the neural network model 134 by repeatedly learning the artificial neural network model 134 using various learning techniques.

According to various embodiments, the trained model may update the artificial neural network model 134 in the database. The learning processor 140 may be integrated into the electronic device 100 or implemented in the memory 130 . Specifically, the learning processor 140 may be implemented using the memory 130 .

According to various embodiments, the learning processor 140 generally identifies, indexes, categorizes, manipulates, stores, retrieves, and outputs data for use in supervised or unsupervised learning, data mining, predictive analytics, or other devices. may be configured to store data in one or more databases for Here, the database may be implemented using memory 130 , memory maintained in a cloud computing environment, or other remote memory location accessible by the terminal through a communication method such as a network. may be utilized by the processor 120 using any of a variety of different types of data analysis algorithms and machine learning algorithms. For example, examples of such algorithms include k-recent adjacency systems, fuzzy logic (eg likelihood theory), neural networks, Boltzmann machines, vector quantization, pulse neural networks, support vector machines, maximum margin classifiers, hill climbing, derivation Logical Systems Bayesian Networks, Peritnets (e.g. Finite State Machines, Milli Machines, Moore Finite State Machines), Classifier Trees (e.g. Perceptron Trees, Support Vector Trees, Markov Trees, Decision Tree Forests, Arbitrary Forests), Read Models and systems, artificial fusion, sensor fusion, image fusion, reinforcement learning, augmented reality, pattern recognition, automated planning, and more.

The communication processor 150 may refer to a configuration including a wireless communication unit (not shown) and an interface unit (not shown). That is, the communication processor 150 may be a processor capable of transmitting and receiving data with another device through wired/wireless communication or an interface.

When the learning model is updated, the updated learning model may be transmitted and loaded to another device such as a terminal or an external device through the communication processor 150 .

The communication processor 150 may communicate with various external terminals. For example, it is possible to perform wired/wireless communication with the first provider terminal 101 , the second provider terminal 102 , and the user terminal 103 . The communication may be LAN-connected wired communication or wireless communication such as long term evolution (LTE), mmWave, and the like.

The first provider terminal 101 , the second provider terminal 102 , and the user terminal 103 may be an electronic device capable of communication, for example, a smart phone, a tablet PC, a network-connected computer, or a laptop.

According to various embodiments, the first provider terminal 101 may establish a communication channel with the communication processor 150 of the electronic device 100 . The first supplier terminal 101 may transmit the product design information 131 to the electronic device 100 through the established communication channel. The first provider terminal 101 may be a terminal used by a designer. The first supplier terminal 101 may store the design of the product produced by the designer in a storage device (eg, memory) in the first supplier terminal 101 . Through a communication channel established with the electronic device through the communication unit or communication interface included in the first provider terminal 101, the first provider terminal 101 can deliver the product design information stored in the storage device to the electronic device 100 have. The product design information 131 transmitted to the communication processor 150 may be stored in an allocated area of the memory 130 . The product design information 131 may include the shape, shape, or color of the product. The product design information 131 may include product evaluation and product review expressed in numerical values, as well as information related to a product created by a designer.

According to various embodiments, the product design information 131 may not be input through the first supplier terminal 101 , but may be directly input through the input unit 110 .

According to various embodiments, the second provider terminal 102 may establish a communication channel with the communication processor 150 of the electronic device 100 . The second provider terminal 102 may transmit the contractor information 132 to the electronic device 100 through the established communication channel. The second provider terminal 102 may be a terminal used by a contractor. The second supplier terminal 102 may store the construction information input by the constructor in a storage device (eg, memory) in the second supplier terminal 102 . Through a communication channel established with the electronic device through the communication unit or communication interface included in the second provider terminal 102, the second provider terminal 102 may deliver the contractor information stored in the storage device to the electronic device 100 . The contractor information 132 transmitted to the communication processor 150 may be stored in an allocated area of the memory 130 . The contractor information 132 may be information including a possible construction location, a construction sample, or a portfolio input by the constructor. The constructor information 132 may include not only information input by the constructor, but also construction evaluation and construction review expressed in numerical values input by the user.

According to various embodiments, the contractor information 132 may not be input through the second provider terminal 102 , but may be directly input through the input unit 110 .

According to various embodiments, the user terminal 103 may establish a communication channel with the communication processor 150 of the electronic device 100 . The user terminal 103 may transmit the purchase information 133 to the electronic device 100 through the established communication channel. The user terminal 103 may be a terminal used by a user or a purchaser. The user terminal 103 may store the purchase information input by the user in a storage device (eg, memory) in the user terminal 103 . Through a communication channel established with the electronic device through a communication unit or communication interface included in the user terminal 103 , the user terminal 103 may transmit purchaser information stored in the storage device to the electronic device 100 . The purchase information 133 transmitted to the communication processor 150 may be stored in an allocated area of the memory 130 .

According to various embodiments, the purchase information 133 may not be input through the user terminal 103 but may be directly input through the input unit 110 . The purchaser information 133 may include a design such as a shape, shape, and color of a product desired by the user, a work location, and a work time. The purchase information 133 may include a history of a product search by a user through a web page, a previous purchase history, and the like.

An external electronic device or an electronic device according to various embodiments disclosed in this document may be a device of various types. The electronic device 100 , the first provider terminal 101 , the second provider terminal 102 , and the user terminal 103 are, for example, a portable communication device (eg, a smart phone), a computer device, a server device, and a portable device. It may include a medical device, a camera, a wearable device, or a home appliance device. The electronic device according to the embodiment of the present document is not limited to the above-described devices.

It should be understood that the various embodiments of this document and the terms used therein are not intended to limit the technical features described in this document to specific embodiments, and include various modifications, equivalents, or substitutions of the embodiments. In connection with the description of the drawings, like reference numerals may be used for similar or related components. The singular form of the noun corresponding to the item may include one or more of the item, unless the relevant context clearly dictates otherwise. As used herein, "A or B", "at least one of A and B", "at least one of A or B," "A, B or C," "at least one of A, B and C," and "A , B, or C" each may include all possible combinations of items listed together in the corresponding one of the phrases. Terms such as “first”, “second”, or “first” or “second” may be used simply to distinguish the component from other such components, and refer to those components in other aspects (eg, importance or order) is not limited. It is said that one (eg, first) component is "coupled" or "connected" to another (eg, second) component, with or without the terms "functionally" or "communicatively". When referenced, it means that one component can be connected to the other component directly (eg by wire), wirelessly, or through a third component.

As used herein, the term “module” may include a unit implemented in 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 part or a minimum unit or a part of the part that performs one or more functions. For example, according to an embodiment, the module may be implemented in the form of an application-specific integrated circuit (ASIC).

Various embodiments of the present document include software (eg, a storage medium (eg, internal memory) or external memory) readable by a machine (eg, the electronic device 101) including one or more instructions stored in the software ( For example, it can be implemented as a program). For example, the processor (eg, the processor 120 ) of the device (eg, the electronic device 100 ) may call at least one command among one or more commands stored from a storage medium and execute it. This makes it possible for the device to be operated to perform at least one function according to the at least one command called. The one or more instructions may include code generated by a compiler or code executable by an interpreter. The device-readable storage medium may be provided in the form of a non-transitory storage medium. Here, 'non-transitory' only means that the storage medium is a tangible device and does not contain a signal (eg, electromagnetic wave), and this term refers to the case where data is semi-permanently stored in the storage medium and It does not distinguish between temporary storage.

According to one embodiment, the method according to various embodiments disclosed in this document may be provided in a computer program product (computer program product). Computer program products may be traded between sellers and buyers as commodities. The computer program product is distributed in the form of a machine-readable storage medium (eg compact disc read only memory (CD-ROM)), or through an application store (eg Play Store ^TM ) or on two user devices ( It can be distributed (eg downloaded or uploaded) directly, online between smartphones (eg: smartphones). In the case of online distribution, at least a part of the computer program product may be temporarily stored or temporarily generated in a machine-readable storage medium such as a memory of a server of a manufacturer, a server of an application store, or a relay server.

According to various embodiments, each component (eg, a module or a program) of the above-described components may include a singular or a plurality of entities. According to various embodiments, one or more components or operations among the above-described corresponding components may be omitted, or one or more other components or operations may be added. Alternatively or additionally, a plurality of components (eg, a module or a program) may be integrated into one component. In this case, the integrated component may perform one or more functions of each component of the plurality of components identically or similarly to those performed by the corresponding component among the plurality of components prior to the integration. . According to various embodiments, operations performed by a module, program, or other component are executed sequentially, in parallel, repeatedly, or heuristically, or one or more of the operations are executed in a different order, or omitted. or one or more other operations may be added.

2 is a conceptual diagram of an artificial neural network model constituting an electronic device according to various embodiments of the present disclosure.

Referring to FIG. 2 , a typical convolutional neural network includes feature extraction 11 of input data 210 using a convolutional layer 201 and a pooling layer 202 and input using a fully connected layer 290 . It can be used for classification 12 of data 210 .

According to various embodiments, the convolutional layer 201 may be a layer that extracts meaningful features of the input data 210 through a convolution operation. For example, the convolutional layer 201 may generate new data to be transmitted to the next layer by applying a filter or a kernel (weight) matrix 230 of a specific size to the input data 210 . Such input/output data of the convolutional layer 201 may be referred to as feature maps.

When the data input to the convolutional neural network model is an input image including a plurality of components such as RGB components, the input data may consist of a plurality of channels. For example, the input/output data of the convolutional layer 201 may include channels in addition to the space of the two-dimensional image, and the feature map of the input/output data may be formed in a three-dimensional form.

According to various embodiments, the pooling layer 202 may reduce input data through sub-sampling. For example, the pooling layer 202 may reduce the size of data by sampling the data through a pooling technique such as max pooling and average pooling.

According to various embodiments, the fully connected layer 290 is a layer for performing data classification based on the features transmitted through the convolutional layer 201 and the pooling layer 202 , and a three-dimensional feature map is flattened. One-dimensional data can be input. As described above, the one-dimensional data that has passed through the fully connected layer 290 may be converted into an output signal through an activation function. Convolutional neural networks can use convolutional layers and pooling layers to maintain the three-dimensional shape of feature maps for input data (e.g. input images), thus avoiding loss of information about the relationships between pixels or channels in the input image. This can increase the image recognition rate.

3 illustrates a signal flow between an electronic device and a plurality of terminals connected to the electronic device according to various embodiments of the present disclosure.

Referring to FIG. 3 , the electronic device 100 may establish a communication channel with the first provider terminal 101 , the second provider terminal 102 , or the user terminal 103 to transmit/receive data or signals.

According to various embodiments, the electronic device 100 may receive the delivered product design information 131 from the first provider terminal 101 ( S201 ). The received product design information 131 may be stored in an allocated area of the memory 130 . The product design information 131 may include the shape, shape, or color of the product. For example, when the product is a wallpaper, the shape of the product design information 131 may include a square, a rectangle, or a size. The shape of the product design information 131 may include a pattern, a pattern, a photograph, or a picture expressed in the shape of the product. The color of the product design information 131 may include a color expressed in a shape. Additionally, the product design information 131 may include the price of the product and the material of the product (eg, a printable material and thickness in the case of wallpaper, or a material of paper constituting the wallpaper). The product design information 131 may extract feature points through the artificial neural network model 134 . The information on the design of the product included in the purchase information 133 may extract feature points through the artificial neural network model 134 . The processor 120 may recommend a design similar to the design desired by the user by comparing the feature points extracted from the product design information 131 and the feature points extracted from the design information included in the purchase information 133 .

According to various embodiments, the electronic device 100 may receive the contractor information 132 transmitted from the second provider terminal 102 ( S202 ). The electronic device 100 may store the received contractor information 132 in an allocated area of the memory 133 . The contractor information 132 may include a possible construction location of the constructor, a construction portfolio, or a construction photograph of a product. The possible construction location of the builder may be used to match the location of the buyer or user who wants to purchase the product. For example, if the user's construction site is Seocho-dong, Seocho-gu, if the construction location included in the construction company information 132 is adjacent areas such as Gangnam-gu and Seocho-gu, the construction company may be matched.

According to various embodiments, the electronic device 100 may identify, from the user terminal 103 , the transmitted purchase information 133 and a first signal related to a request for selecting a product ( S203 ). The received product purchase information 133 may be stored in an allocated area of the memory 130 . The purchase information 133 may include the shape, shape, or color of the product desired by the user. In addition, the purchase information 133 may include a history of a previous purchase by the user, a history searched by the user, and product evaluation of a previous user.

According to various embodiments, in response to the identification of the first signal, the electronic device 100 may determine whether to correspond to the product design information 131 and the purchase information 133 using the artificial neural network model 134 . . In response to the correspondence determination, the electronic device 100 may process the product design information 134 corresponding to the purchase information 133 and transmit the recommended product design to the user terminal 103 ( S204 ). The electronic device 100 may extract the feature points from the product design information 131 through the artificial neural network model 134 . The electronic device 100 may extract a feature point from the product design information included in the purchase information 133 through the artificial neural network model 134 . The electronic device 100 may determine a design corresponding to a design desired by the user by comparing the feature points extracted from the product design information 131 and the feature points extracted from the design information included in the purchase information 133 . The electronic device 100 may recommend a design similar to the design included in the user's purchase information 133 , and transmit the recommended design to the user terminal 103 .

According to various embodiments, in the electronic device 100 , any one of the shape, shape, or color of the product included in the purchase information 133 is the shape, shape, or color of the supplied product included in the product design information 131 . If it is determined that there is a discrepancy with the product design information, any one of the purchase information may be processed and transmitted to the user terminal in response to the determination of whether to match.

According to various embodiments, in the electronic device 100 , at least two of the shape, shape, or color of the product included in the purchase information 133 are the shape, shape, or color of the supplied product included in the product design information 131 . If it is determined that there is a discrepancy with the , the absence of a product corresponding to the purchase information may be notified to the user terminal in response to the determination of whether to match. In this case, returning to step S203 , the electronic device 100 may request the user terminal 103 to re-enter purchase information.

According to another embodiment, in the electronic device 100 , at least two of the shape, shape, or color of the product included in the purchase information 133 are the shape, shape, or color of the supplied product included in the product design information 131 . When it is determined that there is a discrepancy with the above, in response to the determination of whether to match, a product containing the most feature points extracted from the artificial neural network model 134 among products with low similarity may be recommended.

According to various embodiments, the electronic device 100 may identify a signal related to product determination from the user terminal 103 ( S205 ). The user may select a primary product design from the delivered recommended product design. When there are a plurality of delivered recommended products, one or more products may be selected. The user terminal 103 may transmit a signal related to product selection to the electronic device 100 . If the signal related to product determination is a content that there is no preferred product, the electronic device 100 may re-transmit the recommended product design ( S204 ). In this case, the electronic device 100 may recommend a product including the most feature points extracted from the artificial neural network model 134 among products with low similarity.

According to various embodiments, in response to identifying a signal related to product determination from the user terminal 103 , the electronic device 100 may transmit a product-mapped design to the user terminal 103 ( S206 ). The electronic device 100 may map a plurality of selected designs received from the user terminal 103 to an actual wall. The wall may be an object to be actually constructed by the user. The user may take a photo of an area to be actually constructed, select an area in which a product is to be installed, and transmit installation location information stored in the user terminal 103 to the electronic device 100 . The electronic device 100 may store the transferred installation location information in the purchase information 133 area allocated to the memory 130 . The electronic device 100 may map the design to the wall included in the installation location information stored in the purchase information 133 area. The electronic device 100 may transmit a design to which a product is mapped.

According to various embodiments, the electronic device 100 may identify a second signal related to the determination and payment of the delivered product from the user terminal 103 ( S207 ). The user terminal 103 may store product design information that the user finally selects related to purchase from among the plurality of mapped designs transmitted from the electronic device 100 . The user terminal 103 may transmit the selected design information and a request for payment to the electronic device 100 .

According to various embodiments, in response to the identification of the second signal, the electronic device may transmit a prototype or product production request to the first supplier terminal 101 to the first supplier terminal 101 ( S208 ). When the designer who is the user of the first provider terminal 101 does not manufacture the product and the owner of the electronic device 100 manufactures the product based on the designer's design, operation S208 may be omitted.

According to various embodiments, the electronic device 100 may transmit contractor information corresponding to the purchase information 133 among the contractor information 132 to the user terminal 103 ( S209 ). The electronic device 100 may compare the location information included in the contractor information 132 with the construction location information included in the purchase mediation 133 . The electronic device 100 may recommend a contractor whose location information included in the constructor information 132 is the same as or adjacent to the construction location information included in the purchase mediation 133 . In addition, the electronic device 100 may determine and provide companies that the user may prefer based on the contractor evaluation, recommendation, and price from among the constructor information 132 .

According to various embodiments, the electronic device 100 may identify the fourth signal related to the selection of the contractor transmitted from the user terminal 103 ( S210 ). The user terminal 103 may receive an input of a contractor selected by the user from among the recommended construction companies transmitted from the electronic device. The user terminal 103 may transmit a signal related to the contractor selected by the user to the electronic device 100 . The electronic device 100 may transmit the construction site information transmitted from the user terminal 103 to the second provider terminal 102 in response to the fourth signal related to the constructor (S211).

4A, 4B, and 4C illustrate displaying information related to data sent by an electronic device to a user terminal connected to the electronic device according to various embodiments of the present disclosure;

4A, 4B, and 4C explain recommendations by determining the similarity of shape, shape, and color in relation to S204. In FIG. 3, in relation to the transmission of the recommended product design (S204), it has been described that a design including a lot of feature points is recommended using the artificial neural network 134, but in detail, it is recommended by separating the shape, shape and color of the design. can be provided as

Referring to FIG. 4A , based on the user's search history included in the user's purchase information 133, when the user searches for a rectangular product design a lot, the electronic device 100 has a design shape of a long rectangle ( 301a), a trapezoid 301b, and a short rectangle 301c may be recommended. When the user selects the long rectangle 301a from among the information displayed on the display 300 of the user terminal 103 , the user terminal 103 may transmit the corresponding information to the electronic device 100 .

Referring to FIG. 4B , the electronic device 100 recommends a plurality of product shapes by comparing the feature points obtained from the artificial neural network 134 among designs searched for by the user among products corresponding to the long rectangular shape 301a. can In this case, the color may or may not be included in the shape of the product. The user terminal 103 may display the shapes of the plurality of product designs 302a, 302b, and 302c recommended by the electronic device on the display 300 . When the user selects a product 301b having a height displayed in a figure from among the information displayed on the display 300 of the user terminal 103 , the user terminal 103 may transmit the corresponding information to the electronic device 100 .

According to various embodiments, the electronic device 100 compares the feature points obtained from the artificial neural network 134 among the designs searched by the user among the products corresponding to the shape of the product 301b on which the figure is displayed, so that the color of the product is painted. The design 303 may be finally recommended. The recommended product design may be plural.

Although the above description has been described as displaying the form, shape, and color on the user terminal by subdividing it, this is only an example, and the design of the product can be displayed on the user terminal by subdividing it into more steps or by simplifying it into one step. have.

5A, 5B, and 5C illustrate that an electronic device transmits mapped information to a user terminal according to various embodiments of the present disclosure;

Referring to FIG. 5A , the user terminal 103 may take a picture including the wall 410 on which the product is to be installed or constructed. The user terminal 103 may input a photographing signal through the photographing button 401 included in the application in order to acquire an image including the wall surface 410 and the surrounding object 415 .

According to various embodiments, the user terminal 103 may identify the photographing signal and store the obtained image in the memory of the user terminal 103 . The user terminal 103 may display the image stored in the memory on the display.

According to various embodiments, the image stored in the memory may include distance information to distinguish the wall 410 from the surrounding object 415 . The user terminal 103 may include a time-of-flight (TOF) camera or a depth camera to obtain distance information.

Referring to FIG. 5B , the user terminal 103 may display an image stored in a memory on a display and provide a mode for selecting an area in which a product may be installed. The user terminal 103 may determine the product installation area 420 through a user's drag input, multi-touch, or the like. When the user terminal 103 determines the product installation area 420 , the user terminal 103 may transmit an image including information related to the product installation area 420 and information related to the non-installation wall surface 411 to the electronic device 100 .

Referring to FIG. 5C , the electronic device 100 may transmit an image in which a product design 412 is mapped to an image including information related to the product installation area 420 to the user terminal. In the electronic device 100 , the product design 412 may map the product installation area 420 and the distance information obtained during image capturing. A portion of the product installation area 420 that is obscured by the surrounding object 415 may be excluded, the mapping may be performed, and a corresponding design may be provided to the user terminal.

According to various embodiments, when a user selects a product design and photographs a wall to be installed, the user terminal 103 may perform mapping to deliver the mapped image to the user through the display of the user terminal 103 . have.

According to various embodiments described above, an electronic device includes a communication processor (CP) for communicating with one or more user terminals, and an input unit for inputting training data for training an artificial neural network model. a learning processor for training the artificial neural network model using the training data, a memory in which the artificial neural network model is stored, and at least one processor operably coupled to the communication processor and the memory. and the memory stores a plurality of instructions, and when the plurality of instructions are executed by the at least one processor, the at least one processor stores the product design information transmitted from the first supplier terminal into the memory. store in the memory, and store the contractor information transmitted from the second supplier terminal in the memory, identify the first signal related to the purchase information transmitted from the user terminal and the request to select a product, and In response to identification, determining whether to correspond to the product design information and the purchase information using the artificial neural network model, and processing the product design information corresponding to the purchase information in response to the determination of whether to match, Transmitting to the user terminal, and identifying a second signal related to the determination and payment of the delivered product from the user terminal, and in response to the identification of the second signal, a third related to product payment to the first provider terminal A signal may be transmitted, and information corresponding to the purchase information among the contractor information may be controlled to be transmitted to the user terminal.

According to various embodiments, the processor, when executing the instructions by the at least one processor, identifies a fourth signal related to the selection of the contractor transmitted from the user terminal, and in response to the fourth signal , may be set to deliver the construction site information delivered from the user terminal to the second provider terminal.

According to various embodiments, the product design information includes a shape, shape, and color forming the product, and the purchase information includes a shape, shape, and color forming a product accessed by the user. can do.

According to various embodiments, when the plurality of instructions are executed by the at least one processor, the user accesses the at least one processor while determining whether the product design information corresponds to the purchase information. Identify a supply product having a shape of the product design information corresponding to the shape of a product, identify a supply product having a shape of the product design information corresponding to the shape of the product accessed by the user, and the user accesses It may be set to identify a supply product having a color of the product design information corresponding to the color of one product.

According to various embodiments, when the plurality of instructions are executed by the at least one processor, the at least one processor determines whether any one of a shape, a shape, or a color of the product included in the purchase information is supplied. When it is determined that the product does not match the shape, shape, or color of the product, in response to the determination of whether or not the product is compatible, any one of the purchase information may be set to process the same and similar product design information and transmit it to the user terminal have.

According to various embodiments, when the plurality of instructions are executed by the at least one processor, at least two of the shape, shape, or color of the product included in the purchase information are provided by the at least one processor. When it is determined that the product does not match the shape, shape, or color, the user terminal may be configured to notify the absence of a product corresponding to the purchase information in response to the determination of whether the product is compatible.

According to various embodiments, the product design information further includes product evaluation information transmitted from other user terminals other than the user terminal, and the product design information corresponding to the purchase information is obtained based on the product evaluation information, The processed product design information may include a priority according to the evaluation information.

According to various embodiments, the product design information further includes location information to install the product, and the contractor information further includes location information input by the contractor and contractor evaluation information transmitted from other user terminals other than the user terminal. can do.

According to various embodiments, when the plurality of instructions are executed by the at least one processor, the at least one processor transmits the location information input by the installer corresponding to the location information to install the product to the user terminal can be controlled to do so.

According to various embodiments of the present disclosure, a method of operating an electronic device includes storing product design information transmitted from a first supplier terminal communicatively connected with the electronic device in a memory, and receiving the product design information transferred from a second supplier terminal communicatively connected with the electronic device. Storing contractor information in the memory, in response to identifying a first signal related to a request to select a product and purchase information transmitted from a user terminal in communication with the electronic device, using an artificial neural network model to determine the product Determining whether the design information corresponds to the purchase information, in response to the determination of whether the product corresponds to the purchase information, processing the product design information corresponding to the purchase information and transmitting it to the user terminal, from the user terminal, An operation of transmitting a third signal related to the selected product to the first supplier terminal in response to identifying a second signal related to determination and payment of the delivered product, and information corresponding to the purchase information among the builder information to the user It may include an operation of transmitting to the terminal.

Methods according to the embodiments described in the claims or specifications of the present disclosure may be implemented in the form of hardware, software, or a combination of hardware and software.

When implemented in software, a computer-readable storage medium storing one or more programs (software modules) may be provided. One or more programs stored in the computer-readable storage medium are configured to be executable by one or more processors in an electronic device (device). One or more programs include instructions for causing an electronic device to execute methods according to embodiments described in a claim or specification of the present disclosure.

Such programs (software modules, software) include random access memory, non-volatile memory including flash memory, read only memory (ROM), electrically erasable programmable ROM (EEPROM: Electrically Erasable Programmable Read Only Memory), magnetic disc storage device, Compact Disc-ROM (CD-ROM), Digital Versatile Discs (DVDs), or any other form of It may be stored in an optical storage device or a magnetic cassette. Alternatively, it may be stored in a memory composed of a combination of some or all thereof. In addition, each configuration memory may be included in plurality.

In addition, the program is transmitted through a communication network consisting of a communication network such as the Internet, Intranet, Local Area Network (LAN), Wide LAN (WLAN), or Storage Area Network (SAN), or a combination thereof. It may be stored on an attachable storage device that can be accessed. Such a storage device may be connected to a device implementing an embodiment of the present disclosure through an external port. In addition, a separate storage device on the communication network may be connected to the device implementing the embodiment of the present disclosure.

In the specific embodiments of the present disclosure described above, components included in the disclosure are expressed in the singular or plural according to the specific embodiments presented. However, the singular or plural expression is appropriately selected for the situation presented for convenience of description, and the present disclosure is not limited to the singular or plural component, and even if the component is expressed in plural, it is composed of the singular or singular. Even an expressed component may be composed of a plurality of components.

Meanwhile, although specific embodiments have been described in the detailed description of the present disclosure, various modifications are possible without departing from the scope of the present disclosure. Therefore, the scope of the present disclosure should not be limited to the described embodiments and should be defined by the claims described below as well as the claims and equivalents.

100: electronic device
101: first provider terminal
102: second provider terminal
103: user terminal
110: input unit
120: processor
130: memory
140: learning processor
150: communication processor

Claims (10)

In an electronic device,
a communication processor (CP, communication processor) for communicating with one or more user terminals;
an input unit for inputting training data for training an artificial neural network model;
a learning processor for training the artificial neural network model using the training data;
a memory in which the artificial neural network model is stored; and
at least one processor operably coupled to the communication processor and the memory;
The memory stores a plurality of instructions,
The plurality of instructions, when executed by the at least one processor, causes the at least one processor to:
Store the product design information transmitted from the first supplier terminal in the memory,
Storing the contractor information transmitted from the second provider terminal in the memory,
identifying, from the user terminal, the transmitted purchase information and a first signal related to the request to select a product,
In response to the identification of the first signal, determining whether to correspond to the product design information and the purchase information using the artificial neural network model,
In response to the determination of the correspondence, the product design information corresponding to the purchase information is processed and transmitted to the user terminal,
Identifies, from the user terminal, a second signal related to the determination and payment of the delivered product,
In response to the identification of the second signal, transmitting a third signal related to product payment to the first provider terminal,
An electronic device for controlling to transmit information corresponding to the purchase information among the contractor information to the user terminal.
According to claim 1,
The processor, when executing the instructions by the at least one processor,
Identifies a fourth signal related to the selection of the contractor transmitted from the user terminal,
In response to the fourth signal, an electronic device configured to transmit the construction site information transmitted from the user terminal to the second provider terminal.
According to claim 1,
The product design information includes a shape, shape, and color forming the product,
The purchase information is an electronic device including a shape, shape, and color forming a product accessed by the user.
4. The method of claim 3,
The plurality of instructions, when executed by the at least one processor, causes the at least one processor to:
While determining whether to correspond to the product design information and the purchase information, identify a supplied product having a shape of the product design information corresponding to the shape of the product accessed by the user,
Identify a supply product having a shape of the product design information corresponding to the shape of the product accessed by the user,
An electronic device configured to identify a supplied product having a color of the product design information corresponding to the color of the product accessed by the user.
5. The method of claim 4,
The plurality of instructions, when executed by the at least one processor, causes the at least one processor to:
When it is determined that any one of the shape, shape, or color of the product included in the purchase information does not match the shape, shape, or color of the supplied product,
The electronic device configured to process the product design information that is identical to any one of the purchase information in response to the determination of whether or not to respond, and transmit the same to the user terminal.
5. The method of claim 4,
The plurality of instructions, when executed by the at least one processor, causes the at least one processor to:
When it is determined that at least two of the shape, shape, or color of the product included in the purchase information do not match the shape, shape, or color of the supplied product,
The electronic device configured to notify the user terminal of the absence of a product corresponding to the purchase information in response to the determination of whether to match.
4. The method of claim 3,
The product design information further includes product evaluation information transmitted from other user terminals other than the user terminal,
The product design information corresponding to the purchase information is obtained based on the product evaluation information,
The processed product design information is an electronic device including a priority according to the evaluation information.
According to claim 1,
The product design information further includes location information to install the product,
The builder information may further include location information input by the builder and builder evaluation information transmitted from other user terminals other than the user terminal.
9. The method of claim 8,
The plurality of instructions, when executed by the at least one processor, causes the at least one processor to:
An electronic device for controlling to transmit the location information input by the builder corresponding to the location information on which the product is to be installed to a user terminal.
A method for an electronic device, comprising:
storing product design information transferred from a first supplier terminal communicatively connected to the electronic device in a memory, and storing contractor information transferred from a second supplier terminal communicatively connected to the electronic device in the memory;
In response to identifying the first signal related to the request for selecting the product and the purchase information transmitted from the user terminal communicatively connected to the electronic device, whether the product design information and the purchase information correspond to each other using an artificial neural network model action to determine;
processing the product design information corresponding to the purchase information in response to the determination of whether the product corresponds to the purchase information, and transmitting the processing information to the user terminal;
transmitting, from the user terminal, a third signal related to the selected product to the first supplier terminal in response to identifying a second signal related to the determination and payment of the delivered product; and
and transmitting information corresponding to the purchase information among the contractor information to the user terminal.

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