Method and apparatus for matching each product with distributor

Abstract

A computer-implemented method for performing a product-specific distributor matching service by a matching server connected to a product supplier terminal and a distributor terminal managing distribution in a predetermined area comprises the steps of: (a) receiving product information from the product supplier terminal; (b) generating product disclosure information by using the product information; (c) providing the product disclosure information to a plurality of distributor terminals; (d) receiving distribution information generated on the basis of the product disclosure information from at least one of the plurality of distributor terminals to which the product disclosure information is transferred, the distribution information including distribution intention information regarding the product in the predetermined area with regard to each terminal; (e) generating distribution analysis information by using the distribution information; and (f) providing the distribution analysis information to the product supplier terminal. The distribution analysis information includes distribution intention information regarding each distributor terminal to which the distribution information has been transferred.

Description

Method and device for matching distributors by product

[0001] The present invention relates to a method for matching distributors by product and a device for performing the same.

[0002] In the traditional distribution industry, the matching process between product suppliers and distributors is often inefficient and complex. For example, product suppliers must spend significant time and resources to find suitable distributors for their products, and distributors also struggle to find suitable products to distribute.

[0003] These challenges are particularly acute when it comes to finding and connecting with geographically dispersed distributors and suppliers. Traditional matchmaking methods often rely on existing networks, such as personal connections or exhibitions, or require individual approaches through different platforms, which can be inconvenient.

[0004] Additionally, the asymmetry of product and distribution information creates an information gap between suppliers and distributors, which lowers transaction rates and increases inefficiencies in the distribution process.

[0005] To address these issues, a system is needed to improve the flow of information between suppliers and distributors and efficiently match them with mutually suitable partners. For example, to meet this need, product suppliers may need the knowledge to implement a matching service tailored to the needs of both parties, based on the information they share with distributors.

[0006] The problem to be solved in one embodiment includes having distributors participating in distribution provide distribution analysis information based on product information provided by product suppliers, and having this information generated and provided in various formats as reports.

[0007] Additionally, the aforementioned task may also include providing a matching service that matches partners that meet each other's needs in the flow of information between product suppliers and distributors.

[0008] However, the problem to be solved according to one embodiment is not limited to this.

[0009] According to one embodiment, a computer-implemented method for performing a product-specific distributor matching service by a matching server connected to a product supplier terminal and a distributor terminal managing distribution in a predetermined region includes the steps of: (a) receiving product information from the product supplier terminal; (b) generating product disclosure information using the product information; (c) providing the product disclosure information to a plurality of distributor terminals; (d) receiving distribution information generated based on the product disclosure information from at least one of the plurality of distributor terminals to which the product disclosure information has been transmitted; wherein the distribution information includes distribution intent information for the product in the predetermined region for each of the terminals; (e) generating distribution analysis information using the distribution information; and (f) providing the distribution analysis information to the product supplier terminal, wherein the distribution analysis information includes distribution intent information for each distributor terminal that has transmitted the distribution information.

[0010] In addition, the computer-implemented method further includes a step of receiving supply intent information for the product from a product supplier terminal that provided the distribution analysis information; wherein the supply intent information may include i) product supply intent information for the product and / or ii) a product supply plan for the predetermined region.

[0011] In addition, the computer-implemented method may further include a step of reviewing the provided supply intent information; and a step of providing the reviewed supply intent information to at least one of the distributor terminals that received the distribution information.

[0012] In addition, the product supply plan may include at least one selected from the group consisting of (i) the expected supply quantity of the product, (ii) the raw material procurement plan of the product, (iii) the supply unit price of the product, (iv) the minimum order quantity of the product, (v) the lead time of the product supply, (vi) VOC (Voice Of Customer) response information of the product, and (vii) the transportation conditions of the product.

[0013] In addition, the computer-implemented method further includes a step of receiving distribution confirmation information for the product from a terminal that has received the supply intent information, wherein the distribution confirmation information may include i) supply price and / or ii) distribution price for the product in the predetermined region for each terminal.

[0014] In addition, the computer-implemented method may further include a step of providing, to the product supplier terminal or the distributor terminal, matching information including at least one of (i) identification information of the product supplier and distributor terminal pre-stored in the server and (ii) product identification information for the product.

[0015] In addition, the computer-implemented method may further include a step of providing, to the product supplier terminal or the distributor terminal, a draft contract including at least one of (i) identification information of the product supplier and distributor terminal pre-stored in the server and (ii) product identification information for the product.

[0016] Additionally, the product information may include compositional specifications of the product and / or effective specifications of the product.

[0017] In addition, the above structural specifications may include at least one selected from the group consisting of the classification of the product, the use of the product, the licensing information of the product, the expiration date information of the product, the storage method information of the product, the components of the product, the size of the product, the weight of the product, the design of the product, and the brand of the product.

[0018] Additionally, the effective specifications may include at least one selected from the group consisting of the selling point of the product, the effect of the product, and the performance of the product.

[0019] Additionally, if the product is an incomplete product, the product information may include development information describing the development stage of the product.

[0020] Additionally, if the development stage of the product described in the above development information is below a predetermined stage, the transmission of the product information may be restricted.

[0021] Additionally, the step of generating the product disclosure information or the step of generating the market analysis information may include a step of filtering out incorrect and / or false information contained in the information used for generation.

[0022] Additionally, the step of filtering out the above-mentioned incorrect information and / or false information may be performed according to predetermined statistical numerical criteria.

[0023] Additionally, the above predetermined statistical figures may be determined based on the past performance of the server users.

[0024] Additionally, the step of filtering out the above-mentioned incorrect and / or false information may be performed by a language comparison model.

[0025] Additionally, the above language comparison model can be learned using past market analysis information transmitted from the distributor terminal.

[0026] Additionally, the above distribution information may include information on the expected distribution volume in a predetermined area for each terminal.

[0027] Additionally, the above distribution analysis information may include distribution status information for the above product.

[0028] Additionally, the above distribution status information may include at least one selected from the group consisting of (i) distribution market size, (ii) distribution market sector, (iii) distribution market growth rate, (iv) country-specific competitor information, and (v) licensing information for the product.

[0029] Additionally, the above distribution analysis information may include distribution strategies for the above product.

[0030] Additionally, the above distribution strategy may include improvement requests for the above product.

[0031] In addition, the step of generating the distribution analysis information may include a step of generating a distribution analysis report using the distribution analysis information, and the step of transmitting the distribution analysis information to the product supplier terminal may include a step of transmitting the distribution analysis report to the product supplier terminal.

[0032] In addition, in the step of generating the distribution analysis information, if there are multiple distributor terminals that provided the distribution information, one terminal among the multiple distributor terminals that provided the distribution information can be selected, and distribution analysis information including distribution information provided from the selected distributor terminal can be generated.

[0033] Additionally, the server may further include a step of being connected to a real-time terminal and instructing the real-time terminal to conduct an on-site investigation of the distributor or product supplier that provided information to the server.

[0034] According to one embodiment, a computer device that performs a product-specific distributor matching service by being connected to a product supplier terminal and a distributor terminal that manages distribution in a predetermined region includes a memory that stores at least one command; and a processor, wherein the at least one command is executed by the processor to (a) receive product information from the product supplier terminal, (b) generate product disclosure information using the product information, (c) provide the product disclosure information to a plurality of distributor terminals, (d) receive distribution information generated based on the product disclosure information from at least one terminal among the plurality of distributor terminals to which the product disclosure information has been transmitted, wherein the distribution information includes distribution intent information for the product in the predetermined region for each terminal, (e) generate distribution analysis information using the distribution information, and (f) provide the distribution analysis information to the product supplier terminal, wherein the distribution analysis information includes distribution intent information for each distributor terminal that has transmitted the distribution information.

[0035] In addition, by executing the at least one command by the processor, supply intention information for the product is received from the product supplier terminal that provided the distribution analysis information, and the supply intention information may include i) product supply intention information for the product and / or ii) a product supply plan for the predetermined region.

[0036] In addition, by executing at least one command by the processor, the provided supply intention information can be reviewed, and the reviewed supply intention information can be provided to at least one terminal among the distributor terminals that have received the distribution information.

[0037] In addition, the product supply plan may include at least one selected from the group consisting of (i) the expected supply quantity of the product, (ii) the raw material procurement plan of the product, (iii) the supply unit price of the product, (iv) the minimum order quantity of the product, (v) the lead time of the product supply, (vi) VOC (Voice Of Customer) response information of the product, and (vii) the transportation conditions of the product.

[0038] In addition, by executing at least one command by the processor, distribution confirmation information for the product is provided from the terminal that has received the supply intent information, and the distribution confirmation information may include i) supply price and / or ii) distribution price for the product in the predetermined region for each terminal.

[0039] In addition, by executing the at least one command by the processor, matching information including at least one of (i) identification information of the product supplier and distributor terminal pre-stored in the server and (ii) product identification information for the product can be provided to the product supplier terminal or the distributor terminal.

[0040] In addition, the method may further include providing a draft contract including at least one of (i) identification information of the product supplier and distributor terminal pre-stored in the server and (ii) product identification information for the product to the product supplier terminal or distributor terminal.

[0041] Additionally, the product information may include compositional specifications of the product and / or effective specifications of the product.

[0042] In addition, the above structural specifications may include at least one selected from the group consisting of the classification of the product, the use of the product, the licensing information of the product, the expiration date information of the product, the storage method information of the product, the components of the product, the size of the product, the weight of the product, the design of the product, and the brand of the product.

[0043] Additionally, the effective specifications may include at least one selected from the group consisting of the selling point of the product, the effect of the product, and the performance of the product.

[0044] Additionally, if the product is an incomplete product, the product information may include development information describing the development stage of the product.

[0045] Additionally, if the development stage of the product described in the above development information is below a predetermined stage, the transmission of the product information may be restricted.

[0046] Additionally, incorrect and / or false information contained in the information used to generate the above product disclosure information or the above market analysis information may be filtered out.

[0047] Additionally, filtering of the above incorrect and / or false information may be performed based on predetermined statistical criteria.

[0048] Additionally, the above predetermined statistical figures may be determined based on the past performance of the server users.

[0049] Additionally, filtering of the above misinformation and / or false information can be performed by a language comparison model.

[0050] Additionally, the above language comparison model can be learned using past market analysis information transmitted from the distributor terminal.

[0051] Additionally, the above distribution information may include information on the expected distribution volume in a predetermined area for each terminal.

[0052] Additionally, the above distribution analysis information may include distribution status information for the above product.

[0053] Additionally, the above distribution status information may include at least one selected from the group consisting of (i) distribution market size, (ii) distribution market sector, (iii) distribution market growth rate, (iv) country-specific competitor information, and (v) licensing information for the product.

[0054] Additionally, the above distribution analysis information may include distribution strategies for the above product.

[0055] Additionally, the above distribution strategy may include improvement requests for the above product.

[0056] In addition, by executing at least one command by the processor, a distribution analysis report can be generated using the distribution analysis information, and the distribution analysis report can be transmitted to the product supplier terminal.

[0057] In addition, when the at least one command is executed by the processor, if there are multiple distributor terminals that have provided the distribution information, one terminal among the multiple distributor terminals that have provided the distribution information can be selected, and distribution analysis information including the distribution information provided from the selected distributor terminal can be generated.

[0058] Additionally, by executing at least one command by the processor, the server can be connected to a real-time terminal and instruct the real-time terminal to conduct an on-site investigation of the distributor or product supplier that provided information to the server.

[0059] In one embodiment, distributors can always discover products they wish to distribute, and product suppliers can search for suitable distributors, so that distributors and product suppliers can be effectively matched without time or space constraints and without being limited to product fields.

[0060] From a product supplier's perspective, extensive global product marketing allows them to share information and offer distribution suggestions to a diverse range of distributors. Furthermore, distributors' information allows them to assess the competitiveness of their products and review their proposals to determine supply volume and pricing.

[0061] Meanwhile, from the distributor's perspective, it has the effect of allowing them to quickly discover a variety of products by reviewing the products provided by product suppliers, taking into account their own distribution status and capabilities.

[0062] FIG. 1 illustrates an example of a product-specific distributor matching server and various entities connected to a network according to one embodiment.

[0063] FIG. 2 illustrates an exemplary configuration diagram for a server according to one embodiment.

[0064] Figure 3 conceptually illustrates the architecture for deep learning.

[0065] Figure 4 conceptually illustrates the architecture for a convolutional neural network.

[0066] FIG. 5 illustrates an example of a process in which a product-specific distributor matching server transmits information between a product supplier and a distributor according to one embodiment.

[0067] FIG. 6 illustrates an example of a product-specific distributor matching service process performed by a product-specific distributor matching server according to one embodiment.

[0068] FIGS. 7A to 7D illustrate examples of U / I displayed in various entities according to one embodiment.

[0069] FIG. 8 illustrates an exemplary flowchart of a product-specific distributor matching method according to one embodiment.

[0070] The advantages and features of the present invention, and the methods for achieving them, will become clearer with reference to the embodiments described in detail below together with the accompanying drawings. However, the present invention is not limited to the embodiments disclosed below and may be implemented in various different forms. These embodiments are provided solely to ensure that the disclosure of the present invention is complete and to fully inform those skilled in the art of the scope of the invention, and the present invention is defined solely by the scope of the claims.

[0071] When describing embodiments of the present invention, detailed descriptions of known functions or configurations will be omitted if they are deemed to unnecessarily obscure the gist of the invention. Furthermore, the terms described below are defined in light of their functions in the embodiments of the present invention and may vary depending on the intent or custom of the user or operator. Therefore, their definitions should be based on the overall content of this specification.

[0072] FIG. 1 illustrates an example of a product-specific distributor matching server and various entities connected to a network according to one embodiment.

[0073] FIG. 1 illustrates, by way of example, a product-specific distributor matching server (100) and various entities (200 to 300) connected to a network (400) according to one embodiment. Referring to FIG. 1, the product-specific distributor matching server (100), a product supplier terminal (200), and a distributor terminal (300) can communicate with each other via the network (400). The drawing illustrated in FIG. 1 is merely exemplary, and the scope of the present invention is not limited to what is illustrated in FIG. 1.

[0074] Here, the network (400) refers to a wireless or wired network. Among these, in the case of a wireless network, for example, at least one of LTE (long-term evolution), LTE-A (LTE Advance), CDMA (code division multiple access), WCDMA (wideband CDMA), UMTS (universal mobile telecommunications system), WiBro (Wireless Broadband), WiFi (wireless fidelity), Bluetooth, NFC (near field communication), and GNSS (global navigation satellite system) may be included. In addition, in the case of a wired network, for example, at least one of USB (universal serial bus), HDMI (high definition multimedia interface), RS-232 (recommended standard 232), LAN (local area network), WAN (wide area network), the Internet, and a telephone network may be included.

[0075] The product supplier terminal (200) and distributor terminal (300) are devices designed to provide, use, and provide feedback on necessary information for sharing information using the product-specific distributor matching service performed by the product-specific distributor matching server. Here, the product supplier can supply products typically handled in a distribution business. The products supplied by the product supplier may be directly manufactured by the product supplier or may be supplied from another source. Furthermore, the method of product production and supply may vary, and in this specification, the product supplier is defined as a person who supplies products procured through any method.

[0076] Information entered by the product supplier terminal may include product information and information regarding the country in which it is intended for distribution. Product information may include product name, product category, product efficacy, product price, product shipping conditions, and VOC (Voice of Customer) response information. Furthermore, product information may be used to identify the product. This information is then relayed to the distributor, who can then use it to conduct more accurate market analysis of the product.

[0077] Additionally, information entered into the product supplier terminal may include information regarding the countries in which the product will be distributed. This allows product suppliers to provide input regarding the countries in which the product will be distributed. Product suppliers can input information regarding the countries in which the product will be distributed, taking into account various product supply circumstances. The product-specific distributor matching server can coordinate product-specific distributor matching services based on the received information.

[0078] The information entered by the distributor terminal can primarily be used to check information about available products and request desired products. For example, requests may include product specifications, the country of origin, or the country in which the product is scheduled to be distributed.

[0079] Additionally, information entered into a distributor's terminal may indicate the distributor's intent to distribute a specific product. This intent information indicates whether the distributor wishes to distribute the product. For example, a distributor may receive product information from a server, analyze the information, and, if the distributor wishes to distribute the product, provide the server with information indicating their intent to distribute. At this time, the distributor may transmit various information along with the intent to distribute information. For example, the product's expected distribution volume, expected price, expected sales volume, and expected customer base may be transmitted to the server along with the intent to distribute.

[0080] Meanwhile, information entered into product supplier and distributor terminals can be anything necessary for product supply, including product information and distribution destinations, regardless of format or content. This information may include business information generated by product suppliers and distributors. For example, this business information may include product information, customer base, customer response information, licensing information, sales information, and operating profit information.

[0081] As described above, according to one embodiment, users of the product-specific distributor matching server can access various information through the server. For example, they can access various business information generated by product suppliers and distributors. Distribution businesses may have other roles beyond product suppliers and distributors. For example, there may be a product inspector. Here, due diligence refers to the inspector conducting an investigation of a product supplier or distributor. The scope of the investigation may be necessary to predict whether the product supplier can smoothly supply the product. Furthermore, the scope of the investigation may be to determine the reliability of the information provided by the distributor. For example, the scope of due diligence can be narrowly defined as product production, product procurement, or product distribution related to product supply / product distribution, or broadly encompass almost all areas related to the company's operations, including the company's capital structure, stocks, shareholders, licenses, assets (real estate, personal property, intellectual property rights, etc.), contracts (sales contracts, financial contracts, etc.), litigation, disputes, human resources, labor, environment, insurance, taxation, financial statements, and financial condition.

[0082] Below, we will look at these servers (100) in more detail.

[0083] FIG. 2 illustrates an exemplary configuration diagram for a server according to one embodiment.

[0084] Referring to FIG. 2, the server (100) includes a communication unit (110), a memory (120), and a processor (130). However, the configuration diagram illustrated in FIG. 2 is merely exemplary, and the spirit of the present invention is not limited to the configuration diagram illustrated in FIG. 2. For example, the server (100) may include at least one configuration not illustrated in FIG. 2, or may not include at least one of the configurations illustrated in FIG. 2.

[0085] The communication unit (110) can be implemented by a wired or wireless communication module. The server (100) can communicate with an external terminal or server, such as the identification number 200, 300, or 400 illustrated in FIG. 1, through the communication unit (110).

[0086] The memory (120) can be implemented by a medium that stores information. Such a medium may be at least one type of storage medium among a flash memory type, a hard disk type, a multimedia card micro type, a card type memory (e.g., SD or XD memory, etc.), a random access memory (RAM), a static random access memory (SRAM), a read-only memory (ROM), an electrically erasable programmable read-only memory (EEPROM), a programmable read-only memory (PROM), a magnetic memory, a magnetic disk, and an optical disk, but is not limited thereto.

[0087] Various types of information can be stored in this memory (120). For example, information obtained by the server (100) from an external entity (200, 300, 400) through the communication unit (110) can be stored in the memory (120).

[0088] Specifically, the memory (120) may store the status of the product-specific distributor matching service performed by the product-specific distributor matching server (100). Furthermore, information not handled by the product-specific distributor matching server may also be crawled from public information. Furthermore, the memory (120) may store this matching status in its original form, or, in some cases, may be preprocessed and stored. Preprocessing may include summarizing various types of matching information into key information, such as product information providers, product information, and product information recipients. Of course, the types of preprocessing are not limited thereto, and various types of processing that can be performed to store and retrieve documents may be included in this preprocessing.

[0089] Additionally, the memory (120) may store various types of information obtained from the product supplier terminal (200). Specifically, the memory (120) may store information, as described above, that the product supplier (210) inputs to transmit and share information using a service performed by a product-specific distributor matching server.

[0090] Additionally, the memory (120) may store various types of information obtained from the distributor terminal (300). Specifically, the memory (120) may store information, as described above, that the distributor (410) inputs to transmit and share information using a service performed by the product-specific distributor matching server.

[0091] Meanwhile, various types of modules or models may be implemented in the memory (120). When these modules or models are executed by the processor (130) described below, the intended function is performed. For example, these modules or models may include an information update generation module and an advice module that recommends information to service users based on information input from entities connected to the server. For example, using this recommendation information, product suppliers can receive recommendations on the format, type, and examples of product information to be input, and distributors can receive recommendations on a list of products to be reviewed. In addition, new information can be generated using information input to the server, such as information input from product suppliers or distributors, and the information can be judged based on certain criteria.

[0092] At least one of the aforementioned modules or modules may be implemented based on rules or an AI network. Below, we will examine AI networks and the like.

[0093] A model or module in this specification may refer to any form of computer program that operates based on a network function, an artificial neural network, and / or a neural network. Throughout this specification, the terms model, neural network, network function, and neural network may be used interchangeably. A neural network is a network in which one or more nodes are interconnected through one or more links to form input node and output node relationships within the network. The characteristics of a neural network can be determined based on the number of nodes and links within the neural network, the correlation between the nodes and links, and the weight value assigned to each link. A neural network may be composed of a set of one or more nodes. A subset of the nodes constituting the neural network may constitute a layer.

[0094] A deep neural network (DNN) may refer to a neural network that includes multiple hidden layers in addition to an input layer and an output layer. As shown in FIG. 3 as an example of this concept, a deep neural network is composed of one or more, preferably two or more, hidden layers in the middle.

[0095] These deep neural networks can include convolutional neural networks (CNNs), vision transformers, recurrent neural networks (RNNs), long short-term memory (LSTM) networks, generative pre-trained transformers (GPTs), autoencoders, generative adversarial networks (GANs), restricted boltzmann machines (RBMs), deep belief networks (DBNs), Q networks, U networks, Siamese networks, generative adversarial networks (GANs), transformers, etc.

[0096] Alternatively, depending on the embodiment, the deep neural network may be a model trained using transfer learning. Here, transfer learning refers to a learning method in which a large amount of unlabeled training data is pre-trained using a semi-supervised or self-learning method to obtain a pre-trained model (or base) having a first task, and then the pre-trained model is trained using labeled training data using a supervised learning method to fine-tune it to be suitable for a second task, thereby implementing a target model. One of the models trained using this transfer learning method includes, but is not limited to, BERT (Bidirectional Encoder Representations from Transformers).

[0097] In particular, in one embodiment, an artificial intelligence model, specifically a language model, may be used for search, which will be described later.

[0098] The description of the deep neural network described above is only an example, and the present disclosure is not limited thereto. In the case of the convolutional neural network illustrated in FIG. 4, it is composed of a feature extraction unit (feature learning) that extracts features from an image, and a classification unit (classification) that performs classification using the extracted features. The feature extraction unit may include, but is not limited to, a convolution layer that extracts features from an image using a kernel, a ReLU layer as one of the activation functions, and a pooling layer for reducing the dimensionality of the data. In addition, the classification unit may include, but is not limited to, a flatten layer that lines up the features extracted from the feature extraction unit, and a fully connected layer and a softmax function that actually perform classification.

[0099] Neural networks can learn through at least one of the following methods: supervised learning, unsupervised learning, semi-supervised learning, self-supervised learning, or reinforcement learning. Neural network learning can be the process of applying knowledge to the neural network to perform a specific action.

[0100] Neural networks can be trained to minimize output errors. This process involves repeatedly inputting training data into the neural network, calculating the neural network output and target error for the training data, and backpropagating the neural network error from the output layer to the input layer to update the weights of each node in the neural network to reduce the error. In supervised learning, labeled data is used for each training data, while unsupervised learning uses unlabeled data. The amount of change in the connection weights of each updated node can be determined by the learning rate. The neural network's calculation of input data and backpropagation of errors can constitute a learning cycle (epoch). The learning rate can vary depending on the number of iterations in the neural network's training cycle. Additionally, to prevent overfitting, methods such as increasing the learning data, regularization, dropout that disables some nodes, and batch normalization layers can be applied.

[0101] Meanwhile, the model disclosed in one embodiment may borrow at least a portion of a transformer. The transformer may be composed of an encoder that encodes embedded data and a decoder that decodes the encoded data. The transformer may have a structure that receives a series of data, performs encoding and decoding steps, and outputs a series of data of different types. In one embodiment, the series of data may be processed into a form operable by the transformer. The process of processing the series of data into a form operable by the transformer may include an embedding process. Expressions such as data tokens, embedding vectors, and embedding tokens may refer to data embedded in a form operable by the transformer.

[0102] To encode and decode a series of data, a transformer can utilize an attention algorithm to process the encoders and decoders within the transformer. An attention algorithm can refer to an algorithm that, for a given query, calculates the similarity for one or more keys, reflects this similarity in the values ​​corresponding to each key, and then weights and sums the values ​​to which the similarity is reflected to calculate an attention value.

[0103] Depending on how the query, key, and value are configured, various types of attention algorithms can be categorized. For example, if attention is obtained by setting the query, key, and value all to the same value, this could be a self-attention algorithm. If attention is obtained by reducing the dimensionality of the embedding vector to process a series of input data in parallel and then generating individual attention heads for each segmented embedding vector, this could be a multi-head attention algorithm.

[0104] In one embodiment, the transformer may be composed of modules that perform multiple multi-head self-attention algorithms or multi-head encoder-decoder algorithms. In one embodiment, the transformer may also include additional components other than attention algorithms, such as embedding, normalization, and softmax. Methods for constructing a transformer using attention algorithms may include methods disclosed in Vaswani et al., Attention Is All You Need, 2017 NIPS, which is incorporated herein by reference.

[0105] A transformer can be applied to various data domains, such as embedded natural language, segmented image data, and audio waveforms, to transform a series of input data into a series of output data. To transform data with various data domains into a series of data that can be input to a transformer, the transformer can embed the data. The transformer can process additional data that expresses the relative positional relationship or phase relationship between the series of input data. Alternatively, vectors expressing the relative positional relationship or phase relationship between the input data can be additionally reflected in the series of input data to embed the series of input data. In one example, the relative positional relationship between the series of input data may include, but is not limited to, word order within a natural language sentence, the relative positional relationship between each segmented image, and the time order of segmented audio waveforms. The process of adding information expressing the relative positional relationship or phase relationship between the series of input data may be referred to as positional encoding.

[0106] Referring back to FIG. 2, let us examine the processor (130). First, the processor (130) according to one embodiment may perform technical features according to embodiments of the present disclosure, which will be described later, by executing at least one instruction stored in the memory (120). In one embodiment, the processor (130) may be configured with at least one core, and may include a processor for data analysis and / or processing, such as a central processing unit (CPU), a general purpose graphics processing unit (GPGPU), or a tensor processing unit (TPU) of the server (100).

[0107] This processor (130) can train a neural network or model designed using machine learning or deep learning methods. To this end, the processor (130) can perform calculations for neural network training, such as processing input data for training, extracting features from the input data, calculating errors, and updating the weights of the neural network using backpropagation.

[0108] Additionally, the processor (130) may perform inference for a predetermined purpose using a model implemented in an artificial neural network manner.

[0109] Hereinafter, let us look at various operations or functions that the server (100) can perform by executing at least one command stored in the memory (120) by the processor (130).

[0110] First, the processor (130) can control the communication unit (110). Through this, the server (100) can obtain information by communicating with various entities (200, 300, 400) illustrated in FIG. 1 through the communication unit (110).

[0111] Additionally, the processor (130) can read the aforementioned data or commands stored in the memory (120) and record new data or commands in the memory (120). Furthermore, the processor (130) can modify or delete data or commands already recorded. This will be discussed in more detail below.

[0112] According to one embodiment, a computer device that performs a product-specific distributor matching service by being connected to a product supplier terminal and a distributor terminal that manages distribution in a predetermined region includes a memory that stores at least one command; and a processor, wherein the at least one command is executed by the processor to (a) receive product information from the product supplier terminal, (b) generate product disclosure information using the product information, (c) provide the product disclosure information to a plurality of distributor terminals, (d) receive distribution information generated based on the product disclosure information from at least one terminal among the plurality of distributor terminals to which the product disclosure information has been transmitted, wherein the distribution information includes distribution intent information for the product in the predetermined region for each terminal, (e) generate distribution analysis information using the distribution information, and (f) provide the distribution analysis information to the product supplier terminal, wherein the distribution analysis information includes distribution intent information for each distributor terminal that has transmitted the distribution information.

[0113] Here, a product supplier is a person who wishes to be matched with a distributor using the server and can supply products typically handled in a distribution business. The products supplied by the product supplier may be manufactured directly by the product supplier or obtained from another source. Furthermore, the methods of product production and supply may vary. In this specification, a product supplier is defined as a person who supplies products procured through any method.

[0114] First, the product information entered by the product supplier may include the product's structural specifications and / or product's effective specifications. Here, the product's structural specifications may include at least one selected from the group consisting of the product's classification, product's purpose, product's licensing information, product's expiration date information, product's storage method information, product's components, product's size, product's weight, product's design, and product's brand. Meanwhile, the product's effective specifications may include at least one selected from the group consisting of the product's selling point, product's effect, and product's performance. Here, the selling point refers to a unique feature or advantage that enables a product or service to be competitive in the market and appeal to consumers. The selling point is an important element in marketing and sales strategies and can be a key factor in inducing consumers to purchase the product.

[0115] The server can use this product information to generate product disclosure information. This process may include filtering out misinformation and / or disinformation. Misinformation refers to errors in information that the information provider is unaware of, while disinformation refers to information provided by the information provider to induce a specific perspective on the information recipient. Such misinformation and / or disinformation, if provided to a product supplier, can negatively impact the supplier's business, and therefore requires filtering. Below, we will examine examples of filtering.

[0116] The filtering of the above-mentioned misinformation and / or disinformation can be performed based on predetermined statistical criteria. These predetermined statistical values ​​may include sales and operating profit recorded by the distributor in the past. In other words, information that differs by a certain amount from the distributor's recorded sales performance may be filtered out.

[0117] Additionally, the predetermined statistical values ​​may be determined based on the distributor's past distribution performance. Furthermore, the step of filtering out misinformation and / or disinformation may be performed by a language comparison model. Furthermore, the language comparison model may be trained using past market analysis information transmitted from the distributor's terminal. That is, a language model that has learned the distributor's past sales strategies may compare the sales strategies included in the market analysis information with the sales strategies previously implemented. If the sales strategies differ by more than a predetermined threshold, the sales strategy may be filtered out.

[0118] Next, the distributor can receive product disclosure information from the server, generate distribution information, and then transmit it back to the server. This distribution information may include expected distribution volume information for each terminal in a predetermined region. For example, this expected distribution volume information may include distribution status information, which may include at least one of the following: (i) distribution market size, (ii) distribution market sector, (iii) distribution market growth rate, (iv) country-specific competitor information, and (v) licensing information.

[0119] Additionally, the above distribution information may include a distribution strategy for the product, which may include product improvement requests. For example, a distributor may provide the server with information on product improvements based on their distribution expertise.

[0120] Meanwhile, this distribution information can be converted into distribution analysis information on the server. This process, like the product disclosure information generation process, may include a step for filtering out misinformation and / or disinformation. Furthermore, the step of generating the distribution analysis information may include a step of generating a distribution analysis report using the distribution analysis information, and the step of transmitting the distribution analysis information to the product supplier terminal may include a step of transmitting the distribution analysis report to the product supplier terminal.

[0121] In addition, in the step of generating the distribution analysis information, if there are multiple distributor terminals that provided the distribution information, one terminal among the multiple distributor terminals that provided the distribution information can be selected, and distribution analysis information including distribution information provided from the selected distributor terminal can be generated.

[0122] Hereinafter, various types of information transmitted using a server (100) according to one embodiment will be examined. However, the following are merely exemplary, and the spirit of the present invention is not limited thereto.

[0123] FIG. 5 illustrates an example of a process in which a product-specific distributor matching server transmits information between a product supplier and a distributor according to one embodiment.

[0124] Referring to FIG. 5, the server (100) may receive product information from a product supplier terminal (200) (S110). At this time, the product information may specify the product in question and is information necessary for performing a product-specific distributor matching service for the product in the future. Here, the product information may include the product's structural specifications and the product's effective specifications. In addition, the structural specifications may include at least one selected from the group consisting of the product's classification, the product's components, the product's size, the product's weight, the product's design, and the product's brand. In addition, the effective specifications may include at least one selected from the group consisting of the product's selling point, the product's purpose, the product's effect, the product's performance, and the product's licensing.

[0125] Next, the server (100) can generate product disclosure information using product information (S120).

[0126] As mentioned above, this process may include a step for filtering out misinformation and / or disinformation. Misinformation refers to errors in information that the information provider is unaware of, while disinformation refers to information provided by the information provider to induce a specific perspective on the information recipient. Such misinformation and / or disinformation, if provided to a product supplier, can negatively impact the supplier's business, and therefore requires filtering. This process ensures that the server provides high-quality information across the entire service.

[0127] Next, the server (100) can provide product disclosure information to multiple distributor terminals (S130). At this time, the distributors receiving the product disclosure information may be authorized distributors. Here, "authorized" refers to distributor terminals that have been registered with the server through a prescribed procedure and are certified. For example, the server may have a procedure for registering multiple distributors as information providers before performing the product-specific distributor matching service. This procedure may be for institutional registration, information provision, or reliability verification, but is not limited thereto.

[0128] In this case, the product disclosure information provided above may include product identification information that can identify the product for the product-specific distributor matching service, but may not include the product supplier's identification information. Product identification information is necessary for distributors who will receive the information in the future to generate distribution information through distribution market analysis. The exclusion of product supplier identification information may prevent distributors from utilizing information other than product information in their distribution market analysis. By leveraging the distributor's own distribution capabilities, along with pure product information, objective and transparent distribution information can be produced.

[0129] Next, the server (100) may receive distribution information generated based on the product disclosure information from at least one of the multiple distributor terminals to which the product disclosure information has been transmitted (S140). Here, the distribution information is generated based on the product disclosure information and may include distribution intentions and / or distribution expectations for the product. At this time, the distribution information may be received from some of the distributor terminals that have received the product disclosure information. In other words, distributors who have received the product disclosure information may choose not to transmit the distribution information at their own discretion.

[0130] Next, the server (100) can use the above distribution information to generate distribution analysis information (S150). For example, this distribution analysis information can be generated in the form of a distribution report provided to product suppliers. This allows product suppliers to review the distribution status in the region they are responsible for and decide whether to supply products to that region.

[0131] Next, the server (100) may provide distribution analysis information to the product supplier terminal (S160). The distribution analysis information includes distribution intent information for each distributor terminal that transmitted the distribution information. The provided distribution analysis information may include distribution intent information for the product and expected distribution volume information for the product of the distributor who generated the distribution information that formed the basis of the distribution analysis information. Here, the distribution intent information is information expressing whether the distributor wishes to distribute the product, as described above. Along with the distribution intent information, the distributor may transmit expected distribution volume information, including information such as expected distribution sales, expected distribution volume, and expected distribution customer group.

[0132] Hereinafter, the process of providing a product-specific distributor service using a server (100) according to one embodiment will be examined. However, the following is merely exemplary, and the spirit of the present invention is not limited thereto.

[0133] FIG. 6 illustrates an example of a product-specific distributor matching service process performed by a product-specific distributor matching server according to one embodiment.

[0134] Referring to FIG. 6, the server can receive product information from a product supplier terminal (S210). Using the received product information, the server can generate product disclosure information (S220). The generated product disclosure information can be provided to a distributor terminal responsible for distribution in a predetermined region by the server (S230). Distribution information can be generated based on the product disclosure information provided to the distributor terminal. This distribution information can be provided from the distributor terminal to the server (S240). The server can generate distribution analysis information using the received distribution information (S250). The generated distribution analysis information can be provided to the product supplier terminal that provided the product information (S260). The operations in steps (S210) to (S260) overlap with those described in FIG. 5, and therefore, a detailed description thereof will be omitted. Let us examine an example of the service provided by the server after the distribution analysis information is provided, through operations subsequent to step (S260).

[0135] Referring to step S271 of FIG. 6, supply information generated based on distribution analysis information provided to a product supplier terminal may be provided from the product supplier terminal to a server (S271). At this time, the supply information may include (i) product supply intent information for the product and / or (ii) a product supply plan for the predetermined region. In addition, the product supply plan may include at least one selected from the group consisting of (i) the expected supply amount of the product, (ii) a raw material procurement plan for the product, (iii) a supply unit price of the product, (iv) a minimum order quantity of the product, (v) a lead time for the product supply, (vi) VOC (Voice Of Customer) response information for the product, and (vii) transportation conditions of the product.

[0136] Next, in step (S272), the server may provide supply information to the distributor terminal. At this time, the supply information may undergo a review process, including a filtering step, by the server, similar to the product disclosure information generation step (S220) and the distribution analysis information generation step (S250). By receiving the supply information, the distributor terminal can confirm the product supplier's intention to supply the product. In step (S280), the server may receive distribution plan information from the distributor terminal. At this time, the distribution plan information may include (i) the supply price and / or (ii) the distribution price for the product in the predetermined region for each terminal. By confirming the product supplier's supply information and the distributor's distribution plan intention that matches the product supplier's supply information, the server can confirm that the product supplier and the product-specific distributor are matched. In step (290), the server may provide the product supplier and the distributor with the fact of the match and information related to the match.

[0137] FIG. 7 illustrates an example of a U / I (User Interface) displayed in various entities according to one embodiment.

[0138] Referring to Fig. 7a, a U / I displayed on a product supplier terminal according to an embodiment is exemplarily illustrated. However, the configuration diagram illustrated in Fig. 7a is merely exemplary, and the spirit of the present invention is not limited to the configuration diagram illustrated in Fig. 7a. For example, the product-specific distributor matching server may include at least one configuration not illustrated in Fig. 7a, or may not include at least one of the configurations illustrated in Fig. 7a, for efficient product-specific distributor matching services. Furthermore, such configurations may be displayed on entity terminals other than the product supplier terminal.

[0139] The U / I displayed on the product supplier terminal according to an embodiment of FIG. 7a provides an area where various information (product overview and specifications, photos, brochures, certification information, territory, suggested price, etc.) for multiple products (product A, product B) can be input. Through this U / I, the product supplier can provide product information for products it wishes to distribute to the server.

[0140] Referring to FIG. 7b, a U / I displayed on a distributor terminal according to one embodiment is exemplarily illustrated.

[0141] Referring to Fig. 7b, a U / I displayed on a distributor terminal according to an embodiment is exemplarily illustrated. However, the configuration diagram illustrated in Fig. 7b is merely exemplary, and the spirit of the present invention is not limited to the configuration diagram illustrated in Fig. 7b. For example, the product-specific distributor matching server may include at least one configuration not illustrated in Fig. 7b, or may not include at least one of the configurations illustrated in Fig. 7b, for efficient product-specific distributor matching services. Furthermore, such configurations may be displayed on entity terminals other than the distributor terminal.

[0142] The UI displayed on the distributor terminal according to the embodiment of Figure 7b provides an area where product information provided by product suppliers wishing to distribute is displayed. This area may display various product information generated by various product suppliers. Using this information, distributors can select products they can distribute.

[0143] Referring to FIG. 7c, a U / I displayed on a distributor terminal according to one embodiment is exemplarily illustrated.

[0144] Referring to Fig. 7c, a U / I displayed on a distributor terminal according to an embodiment is exemplarily illustrated. However, the configuration diagram illustrated in Fig. 7c is merely exemplary, and the spirit of the present invention is not limited to the configuration diagram illustrated in Fig. 7c. For example, the product-specific distributor matching server may include at least one configuration not illustrated in Fig. 7c, or may not include at least one of the configurations illustrated in Fig. 7c, for efficient product-specific distributor matching services. Furthermore, such configurations may be displayed on entity terminals other than the distributor terminal.

[0145] The UI displayed on the distributor terminal according to one embodiment of FIG. 7c provides an area where the distributor can provide distribution information to the server. Through the distribution information provision area according to one embodiment, the distributor can provide various distribution information (country market, competitiveness, suggested price, and quantity) for multiple products (Product A, Product D).

[0146] Referring to FIG. 7d, a U / I displayed on a product-specific distributor matching server according to one embodiment is exemplarily illustrated.

[0147] Referring to FIG. 7D, a U / I displayed on a product-specific distributor matching server according to an embodiment is exemplarily illustrated. However, the configuration diagram illustrated in FIG. 7D is merely exemplary, and the spirit of the present invention is not limited to the configuration diagram illustrated in FIG. 7D. For example, the product-specific distributor matching server may include at least one configuration not illustrated in FIG. 7D or may not include at least one of the configurations illustrated in FIG. 7D for efficient product-specific distributor matching services. Furthermore, such configurations may be displayed on entity terminals other than the product-specific distributor matching server.

[0148] The UI displayed on the product-specific distributor matching server according to an embodiment of FIG. 7d provides an area where the server can select a distributor for each product. FIG. 7d illustrates a configuration in which, after reviewing distribution information (offered price and quantity) provided by multiple distributors (Distributors 1 to 6) for Product A in each region (Korea, Italy), a distributor for each region is selected. At this time, there may be one or more distributors for each region.

[0149] We have examined the information and functions that can be provided through the server and entities connected to the server through the U / I configuration of FIGS. 7a to 7d.

[0150] Through these services, distributors can constantly discover products they wish to distribute, and product suppliers can be matched with distributors who can provide appropriate distribution services without any time or space constraints.

[0151] From a product supplier's perspective, extensive global product marketing allows them to share information and offer distribution suggestions to a diverse range of distributors. Furthermore, distributors' information allows them to assess the competitiveness of their products and review their proposals to determine supply volume and pricing.

[0152] Meanwhile, from the distributor's perspective, it has the effect of allowing them to quickly discover a variety of products by reviewing the products provided by product suppliers, taking into account their own distribution status and capabilities.

[0153] Figure 8 illustrates a flowchart for a product-specific distributor matching method according to one embodiment. This flowchart is merely exemplary, and the scope of the present invention is not limited thereto. For example, depending on the embodiment, each step may be performed in a different order than that illustrated in Figure 8, or at least one step not illustrated in Figure 8 may be additionally performed, or at least one of the steps illustrated in Figure 8 may not be performed.

[0154] Referring to FIG. 8, a computer-implemented method for performing a product-specific distributor matching service by a matching server connected to a product supplier terminal and a distributor terminal managing distribution in a predetermined region comprises the steps of: (a) receiving product information from the product supplier terminal; (b) generating product disclosure information using the product information; (c) providing the product disclosure information to a plurality of distributor terminals; (d) receiving distribution information generated based on the product disclosure information from at least one terminal among the plurality of distributor terminals to which the product disclosure information has been transmitted; the distribution information includes distribution intent information for the product in the predetermined region for each terminal; and (e) generating distribution analysis information using the distribution information.

[0155] (f) a step of providing the above distribution analysis information to the product supplier terminal; the above distribution analysis information includes distribution intent information for each distributor terminal that transmitted the above distribution information.

[0156] Meanwhile, the method according to the various embodiments described above can be implemented in the form of a computer program stored in a computer-readable recording medium programmed to perform each step of the method, and can also be implemented in the form of a computer-readable recording medium storing a computer program programmed to perform each step of the method.

[0157] The above description is merely an illustrative illustration of the technical idea of ​​the present invention, and those skilled in the art will appreciate that various modifications and variations can be made without departing from the essential quality of the present invention. Therefore, the embodiments disclosed in the present invention are intended to illustrate, rather than limit, the technical idea of ​​the present invention, and the scope of the technical idea of ​​the present invention is not limited by these embodiments. The scope of protection of the present invention should be interpreted by the following claims, and all technical ideas within a scope equivalent thereto should be interpreted as being included in the scope of the rights of the present invention.

Claims

1. A computer implementation method for performing a product-specific distributor matching service by a matching server connected to a product supplier terminal and a distributor terminal that manages distribution in a predetermined area, (a) a step of receiving product information from the product supplier terminal; (b) a step of generating product disclosure information using the above product information; (c) a step of providing the above product disclosure information to multiple distributor terminals; (d) a step of receiving distribution information generated based on the product disclosure information from at least one of a plurality of distributor terminals to which the product disclosure information has been transmitted; the distribution information includes distribution intent information for the product; (e) a step of generating distribution analysis information using the above distribution information; and (f) A computer-implemented method comprising a step of providing the above distribution analysis information to the product supplier terminal, wherein the distribution analysis information includes distribution intent information for each distributor terminal that transmitted the distribution information.

2. In paragraph 1, A step of receiving supply information on the product from a product supplier terminal that provided the distribution analysis information; further comprising; A computer-implemented method wherein the above supply information includes (i) product supply intent information for the product and / or (ii) a product supply plan for the predetermined region.

3. In paragraph 2, A step of reviewing the supply information provided above; and A step of providing the above-reviewed supply information to at least one terminal among the distributor terminals that received the above-mentioned distribution information. A computer implemented method further comprising:

4. In paragraph 2, A computer-implemented method wherein the product supply plan includes at least one selected from the group consisting of (i) the expected supply quantity of the product, (ii) a raw material procurement plan for the product, (iii) a supply unit price of the product, (iv) a minimum order quantity of the product, (v) a lead time for supplying the product, (vi) VOC (Voice Of Customer) response information for the product, and (vii) transportation conditions for the product.

5. In paragraph 3, Further comprising a step of receiving distribution plan information for the product from a terminal that has received the above supply information, A computer-implemented method wherein the above distribution plan information includes (i) the supply price and / or (ii) the distribution price for the above product in the above predetermined region for each terminal.

6. In paragraph 5, A computer-implemented method further comprising the step of providing, to the product supplier terminal and / or the distributor terminal, matching information including at least one of (i) identification information of the product supplier and distributor terminal pre-stored in the server and (ii) product identification information for the product.

7. In paragraph 5, A computer-implemented method further comprising the step of providing, to the product supplier terminal and / or the distributor terminal, a draft contract including at least one of (i) identification information of the product supplier and distributor terminal pre-stored in the server and (ii) product identification information for the product.

8. In paragraph 1, A computer-implemented method wherein the product information includes a structural specification of the product and / or an effective specification of the product.

9. In paragraph 8, A computer-implemented method in which the above-mentioned structural specifications include at least one selected from the group consisting of the classification of the product, the use of the product, the licensing information of the product, the expiration date information of the product, the storage method information of the product, the components of the product, the size of the product, the weight of the product, the design of the product, and the brand of the product.

10. In paragraph 8, A computer-implemented method wherein the effective specification includes at least one selected from the group consisting of a selling point of the product, an effect of the product, and a performance of the product.

11. In paragraph 1, A computer-implemented method wherein, if the product is an incomplete product, the product information includes development information describing the development stage of the product.

12. In paragraph 11, A computer-implemented method in which transmission of product information is restricted when the development stage of the product described in the development information is below a predetermined stage.

13. In paragraph 1, A computer-implemented method comprising a step of filtering out incorrect and / or false information from among the information included in the step of generating the product disclosure information or the step of generating the market analysis information.

14. In paragraph 13, A computer-implemented method wherein the step of filtering out the above-mentioned incorrect information and / or false information is performed according to predetermined statistical numerical criteria.

15. In paragraph 14, A computer implementation method in which the above predetermined statistical figures are determined based on the past performance of the above server users.

16. In paragraph 13, A computer-implemented method wherein the step of filtering out the above-mentioned incorrect and / or false information is performed by a language comparison model.

17. In paragraph 16, The above language comparison model is a computer-implemented method learned by past market analysis information transmitted from the distributor terminal.

18. In paragraph 1, A computer implementation method wherein the above distribution information includes information on the expected distribution amount in a predetermined area for each terminal.

19. In paragraph 1, A computer-implemented method wherein the above distribution analysis information includes distribution status information for the above product.

20. In paragraph 19, A computer-implemented method wherein the above distribution status information includes at least one selected from the group consisting of (i) the size of the distribution market, (ii) the sector of the distribution market, (iii) the growth rate of the distribution market, (iv) information on competitors by country, and (v) licensing information for the product.

21. In paragraph 1, A computer-implemented method wherein the above distribution analysis information includes a distribution strategy for the above product.

22. In paragraph 21, A computer-implemented method for providing a distribution strategy including improvement requests for the product.

23. In paragraph 1, The step of generating the above distribution analysis information includes the step of generating a distribution analysis report using the above distribution analysis information, A computer-implemented method wherein the step of transmitting the distribution analysis information to the product supplier terminal includes the step of transmitting the distribution analysis report to the product supplier terminal.

24. In paragraph 1, The step of generating the above distribution analysis information is: A computer-implemented method for selecting one of the multiple distributor terminals that provided the above distribution information, when there are multiple distributor terminals that provided the above distribution information, and generating distribution analysis information including the distribution information provided from the selected distributor terminal.

25. In paragraph 1, A computer-implemented method further comprising the step of: said server being connected to a real-time terminal; and instructing said real-time terminal to conduct a real-time investigation of said distributor or product supplier that provided information to said server.

26. A computer-readable recording medium storing a computer program that is performed to include each step included in any one of paragraphs 1 to 25.

27. A computer program stored on a computer-readable recording medium that is executed to include each step included in any one of paragraphs 1 to 25.

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