A method, device and medium for online business opportunity mining for suppliers

Abstract

The present application discloses a method, device and medium for mining online business opportunities for suppliers, and the method includes: obtaining supply information related to the supplier; the supply information includes commodity types and commodity inventory; searching for commodity types in the e-commerce platform, and determining candidate purchasers with commodity type procurement needs; if the commodity type is a first-category commodity, determining the enterprise scale of the supplier according to the commodity inventory; the storage time limit of the first-category commodity is not greater than the preset storage threshold; determining the priority of the candidate purchaser according to the priority corresponding to the enterprise scale and the procurement information of the candidate purchaser; matching the supply information with the procurement information according to the priority, generating a supply plan, and recommending the corresponding purchaser in the supply plan to the supplier. The embodiment of the present application matches the supply information with the procurement information of the candidate purchaser on the basis of the priority, thereby improving the accuracy of matching the supplier with accurate procurement information.

Description

Technical Field

[0001] The present application relates to the field of computer technology, and in particular to an online business opportunity mining method, device and medium for suppliers. Background Art

[0002] In recent years, e-commerce has become more and more prosperous, and online trading platforms for various commodities have also flourished. Electronic procurement platforms save a lot of time and space for buyers and suppliers, improve transaction efficiency, and are increasingly becoming an important choice for people's trading methods.

[0003] At present, the types of procurement information that suppliers can query on e-commerce platforms are increasing, and the amount of data is also increasing. However, the information services of existing e-commerce platforms are still very extensive, not refined, and only complete the preliminary collection and retrieval functions of information, resulting in a low accuracy rate in matching suppliers with accurate procurement information in the massive data of e-commerce platforms. Summary of the invention

[0004] The embodiments of the present application provide an online business opportunity mining method, device and medium for suppliers, which are used to solve the problem of low accuracy in matching suppliers with accurate procurement information in the massive data of an e-commerce platform.

[0005] The present application embodiment adopts the following technical solutions:

[0006] On the one hand, an embodiment of the present application provides an online business opportunity mining method for suppliers, the method comprising: obtaining supply information related to the supplier; the supply information comprises commodity types and commodity inventory; searching the commodity types in an e-commerce platform to determine candidate buyers who have procurement needs for the commodity types; if the commodity types are first-category commodities, determining the enterprise scale of the supplier according to the commodity inventory; the storage time limit of the first-category commodities is not greater than a preset storage threshold; determining a priority plan corresponding to the enterprise scale and the procurement information of the candidate buyers to determine the priority of the candidate buyers; matching the supply information with the procurement information according to the priority, generating a supply plan, and recommending the buyers corresponding to the supply plan to the supplier.

[0007] In one example, determining the enterprise scale of the supplier based on the inventory of the goods specifically includes: judging whether the inventory of the goods is greater than a preset quantity N; if so, the enterprise scale of the supplier is a first enterprise scale; determining the priority of the candidate buyer based on the priority determination scheme corresponding to the enterprise scale and the purchasing information of the candidate buyer specifically includes: determining the time difference between the purchasing time of the purchasing information and the current time; sorting the time differences from small to large to obtain a first sorting result queue; in the first sorting result queue, determining the priority of the candidate buyer; the smaller the value of the time difference, the higher the corresponding priority.

[0008] In one example, determining the enterprise scale of the supplier based on the commodity inventory specifically includes: determining whether the commodity inventory is greater than a preset quantity N; if not, the enterprise scale of the supplier is a second enterprise scale; determining the priority of the candidate buyer based on the priority determination scheme corresponding to the enterprise scale and the purchasing information of the candidate buyer specifically includes: determining the purchase unit price of the purchasing information; sorting the purchase unit prices from high to low to obtain a second sorting result queue; in the second sorting result queue, determining the priority of the candidate buyer; the higher the value of the purchase unit price, the higher the priority.

[0009] In one example, the supply information is matched with the procurement information according to the priority to determine the supply plan, which specifically includes: extracting multiple candidate buyers from high to low according to the priority, and determining the multiple candidate buyers as buyers to be matched; matching the supply information with the procurement information through a buyer screening model to determine the probability value of the supplier matching the buyer to be matched; if the probability value is greater than a preset matching threshold, outputting the buyer to be matched to the supply plan.

[0010] In one example, the purchaser screening model is used to match the supply information with the purchase information to determine the probability value of the supplier matching the purchaser to be matched, which specifically includes: determining the supply rule table of the supplier; the supply rule table includes matching fields, percentage scores and matching rules; scoring each matching field in the supply rule table to determine the percentage score of each matching field; calculating the total score of the percentage scores; in each matching field, according to the matching rule, matching the purchase information to determine the score corresponding to each matching field; calculating the total score of the scores corresponding to each matching field; determining the ratio of the total score to the total score, and using the ratio as the probability value of the supplier matching the purchaser to be matched.

[0011] In one example, if the probability value is greater than a preset matching threshold, after the to-be-matched purchaser is output to the supply plan, the method further includes: if a new purchaser who purchases the type of goods is added, the supply information is matched with the purchasing information of the new purchaser through the purchaser screening model to determine the probability value of the supplier matching the new purchaser; if the probability value is greater than the preset matching threshold, the new purchaser is recommended to the supplier.

[0012] In one example, after recommending the purchaser corresponding to the supply plan to the supplier, the method also includes: determining other purchasers that other suppliers in the same industry as the supplier are interested in; recommending the other purchasers to the supplier to determine whether the supplier is interested in the other purchasers; receiving a first feedback from the supplier to obtain a first feedback result; if the first feedback result is interest, establishing a communication channel between the supplier and the other purchasers.

[0013] In one example, after recommending the purchaser corresponding to the supply plan to the supplier, the method also includes: determining the supplier's historical purchasers within a preset time period; recommending the historical purchasers to the supplier to determine whether the supplier is interested in the historical purchasers; receiving second feedback from the supplier to obtain a second feedback result; if the second feedback result is interest, establishing a communication channel between the supplier and the historical purchaser.

[0014] On the other hand, an embodiment of the present application provides an online business opportunity mining device for suppliers, comprising: at least one processor; and a memory communicatively connected to the at least one processor; wherein the memory stores instructions executable by the at least one processor, and the instructions are executed by the at least one processor so that the at least one processor can: obtain supply information related to the supplier; the supply information includes commodity types and commodity inventory; retrieve the commodity types in an e-commerce platform, and determine candidate buyers with procurement needs for the commodity types; if the commodity types are first-category commodities, determine the enterprise scale of the supplier based on the commodity inventory; the storage time limit of the first-category commodities is not greater than a preset storage threshold; determine the priority of the candidate buyer based on the priority determination plan corresponding to the enterprise scale and the procurement information of the candidate buyer; according to the priority, match the supply information with the procurement information, generate a supply plan, and recommend the buyer corresponding to the supply plan to the supplier.

[0015] On the other hand, an embodiment of the present application provides a non-volatile computer storage medium for online business opportunity mining for suppliers, storing computer executable instructions, characterized in that the computer executable instructions are set to: obtain supply information related to the supplier; the supply information includes commodity types and commodity inventory; retrieve the commodity types in the e-commerce platform, and determine candidate buyers with procurement needs for the commodity types; if the commodity types are first-category commodities, determine the enterprise scale of the supplier based on the commodity inventory; the storage time limit of the first-category commodity is not greater than a preset storage threshold; determine the priority of the candidate buyer based on the priority determination plan corresponding to the enterprise scale and the procurement information of the candidate buyer; according to the priority, match the supply information with the procurement information, generate a supply plan, and recommend the buyer corresponding to the supply plan to the supplier.

[0016] At least one of the above technical solutions adopted in the embodiments of the present application can achieve the following beneficial effects:

[0017] The embodiment of the present application determines the enterprise scale of the supplier through the inventory of the first category of goods, and determines the priority of the candidate buyers according to the priority determination plan corresponding to the enterprise scale and the purchasing information of the candidate buyers. It is possible to measure the inventory of goods, combine the enterprise scale of the supplier and the purchasing information of the candidate buyers, and determine the priority of the candidate buyers. Figure 1 The method can determine the priority of candidate buyers based on the measurement of commodity inventory and the combination of the supplier's enterprise scale and the candidate buyers' procurement information. It can initially screen the candidate buyers from the perspective of the supplier's enterprise scale, and then match the supply information with the candidate buyers' procurement information based on the priority. It can ensure the maximization of profits for suppliers of different enterprise scales, and timely handle commodities with a short storage time, and improve the accuracy of matching suppliers with accurate procurement information in the massive data of the e-commerce platform. BRIEF DESCRIPTION OF THE DRAWINGS

[0018] In order to more clearly illustrate the technical solution of the present application, some embodiments of the present application will be described in detail below in conjunction with the accompanying drawings, in which:

[0019] Figure 1 A flowchart of an online business opportunity mining method for suppliers provided in an embodiment of the present application;

[0020] Figure 2 A schematic diagram of the structure of an online business opportunity mining device for suppliers provided in an embodiment of the present application. DETAILED DESCRIPTION

[0021] In order to make the purpose, technical solution and advantages of the present application clearer, the technical solution of the present application will be clearly and completely described below in conjunction with specific embodiments and corresponding drawings. Obviously, the described embodiments are only part of the embodiments of the present application, not all of the embodiments. Based on the embodiments in the present application, all other embodiments obtained by ordinary technicians in the field without creative work are within the scope of protection of the present application.

[0022] In some embodiments of the present application, the embodiment of the present application determines the enterprise scale of the supplier through the inventory of the first category of goods, and determines the priority of the candidate purchaser according to the priority determination scheme corresponding to the enterprise scale and the purchase information of the candidate purchaser. It can measure the inventory of goods, combine the enterprise scale of the supplier and the purchase information of the candidate purchaser, determine the priority of the candidate purchaser, and conduct an initial screening of the candidate purchaser from the perspective of the enterprise scale of the supplier. Then, on the basis of the priority, the supply information is matched with the purchase information of the candidate purchaser, so as to achieve the maximization of the profits of suppliers of different enterprise scales, and timely handle the goods with a short storage time limit, and improve the accuracy of matching the supplier with accurate purchase information in the massive data of the e-commerce platform, and solve the problem of low accuracy of matching the supplier with accurate purchase information in the massive data of the e-commerce platform. Based on this idea, the following is a specific explanation.

[0023] Figure 1 The present invention provides a flowchart of an online business opportunity mining method for suppliers provided in an embodiment of the present invention. The method can be implemented by a terminal device or a server, and there is no special limitation on this. For the convenience of understanding and description, the following embodiments are described in detail by taking the server as an example.

[0024] It should be noted that the server may be a single device or a system consisting of multiple devices, that is, a distributed server, and this application does not make any specific limitation on this.

[0025] Figure 1 The process in may include the following steps:

[0026] S101: Acquire supply information related to suppliers, where the supply information includes product types and product inventory.

[0027] In some embodiments of the present application, the supply information includes the type of goods, the inventory of the goods, the industry to which they belong, and the like.

[0028] S102: Searching for commodity categories in the e-commerce platform, and determining candidate buyers who have commodity category procurement needs.

[0029] In some embodiments of the present application, the server may search in the e-commerce platform in various ways, such as directory search, keyword search, natural language search, etc. The e-commerce platform may be a trading platform that meets the needs of suppliers and buyers, such as the iGoCloud platform.

[0030] S103: If the commodity type is a first category commodity, determine the enterprise scale of the supplier according to the inventory of the commodity; the storage time limit of the first category commodity is not greater than a preset storage threshold.

[0031] In addition, the first category of goods includes goods that are not suitable for long-term storage, such as fresh fruits, fresh vegetables, etc. Since the storage time limit of the first category of goods is not greater than the preset storage threshold, it is necessary to consider the inventory of the first category of goods held in the supplier's warehouse.

[0032] Furthermore, to a certain extent, there is a positive correlation between the inventory of goods and the size of the enterprise, that is, the larger the inventory of goods, the larger the enterprise scale, and the smaller the inventory of goods, the smaller the enterprise scale.

[0033] S104: Determine the priority of the candidate buyers according to the priority determination plan corresponding to the enterprise scale and the procurement information of the candidate buyers.

[0034] In some embodiments of the present application, the purchase information includes purchase time, product type, purchase quantity, estimated amount, company type, etc.

[0035] In addition, considering the priority determination scheme corresponding to the enterprise scale can better combine the characteristics of the enterprise scale. For example, when the inventory of goods is large, enterprises with larger scale can achieve small profits but quick turnover on the basis of ensuring the value of the first category of goods in order to avoid overstocking of the first category of goods. For enterprises with smaller scale, when the inventory of goods is small, they may need to focus on the cost issue to maximize profits.

[0036] S105: Match the supply information with the purchase information according to the priority, generate a supply plan, and recommend the purchaser corresponding to the supply plan to the supplier.

[0037] In some embodiments of the present application, the server first determines the priority of the candidate purchaser, and then matches the supply information with the purchase information of the candidate purchaser based on the priority. After matching, the purchaser that matches the supply information of the supplier can be screened out from multiple candidate purchasers, thereby generating a supply plan. That is, the supply plan may include one purchaser and the purchase information corresponding to the purchaser, or may include multiple purchasers and the purchase information corresponding to each purchaser.

[0038] It should be noted that although the embodiments of the present application are based on Figure 1 Steps S101 to S105 are described in sequence, but this does not mean that steps S101 to S105 must be performed in a strict order. Figure 1 The order shown in the figure is to introduce and explain step S101 to step S105 in sequence, in order to facilitate those skilled in the art to understand the technical solution of this embodiment. In other words, in the embodiment of the present application, the order between step S101 to step S105 can be appropriately adjusted according to actual needs.

[0039] pass Figure 1 The method can determine the priority of candidate buyers based on the measurement of commodity inventory and the combination of the supplier's enterprise scale and the candidate buyers' procurement information. It can initially screen the candidate buyers from the perspective of the supplier's enterprise scale, and then match the supply information with the candidate buyers' procurement information based on the priority. It can ensure the maximization of profits for suppliers of different enterprise scales, and timely handle commodities with a short storage time, and improve the accuracy of matching suppliers with accurate procurement information in the massive data of the e-commerce platform.

[0040] based on Figure 1 The present application also provides some specific implementation schemes and extension schemes of the method, which will be described below.

[0041] In some embodiments of the present application, since the specific quantity of commodity inventory will affect the urgency of the supplier in processing this batch of commodities, the server pre-sets a preset number N for measuring urgency, that is, if the commodity inventory exceeds the preset number N, the commodity needs to be processed as soon as possible and the urgency is higher; if the commodity inventory does not exceed the preset number N, the urgency of processing the commodity will be lower.

[0042] Therefore, the server determines whether the inventory of the goods is greater than the preset quantity N. If so, the enterprise scale of the supplier is the first enterprise scale, and the priority of the candidate purchaser is determined according to the priority determination scheme corresponding to the first enterprise scale and the purchase information of the candidate purchaser. If not, the enterprise scale of the supplier is the second enterprise scale, and the priority of the candidate purchaser is determined according to the priority determination scheme corresponding to the second enterprise scale and the purchase information of the candidate purchaser. Among them, the first enterprise scale is greater than the second enterprise scale.

[0043] Specifically, the server determines the priority of the candidate purchaser according to the priority determination scheme corresponding to the first enterprise scale and the purchase information of the candidate purchaser, specifically including: obtaining the purchase time in the purchase information of the candidate purchaser, and subtracting the purchase time from the current time to determine the time difference between the purchase time and the current time, and sorting the time difference from small to large, and outputting it to the first sorting result queue, and finally in the first sorting result queue, determining the candidate purchaser corresponding to the minimum value of the time difference as the highest priority, and from the minimum value of the time difference, the priority of the candidate purchaser is reduced in sequence until the candidate purchaser corresponding to the maximum value of the time difference is determined as the lowest priority. That is, the smaller the value of the time difference, the higher the priority.

[0044] Specifically, the server determines the priority of the candidate purchaser according to the priority determination scheme corresponding to the second enterprise scale and the purchase information of the candidate purchaser, specifically including: obtaining the purchase quantity and estimated amount in the purchase information of the candidate purchaser, calculating the ratio of the purchase quantity to the estimated amount, thereby determining the purchase unit price of the commodity, and sorting the purchase unit prices from high to low, and outputting them to the second sorting result queue, and finally in the second sorting result queue, determining the candidate purchaser corresponding to the highest purchase unit price as the highest priority, and starting from the highest purchase unit price, successively reducing the priority of the candidate purchaser until the candidate purchaser corresponding to the lowest purchase unit price is determined as the lowest priority. That is, the higher the value of the purchase unit price, the higher the priority.

[0045] The embodiment of the present application determines the inventory of the first category of goods. If the inventory is large, it corresponds to a larger enterprise scale, and the purchaser with the earliest purchase time is recommended first, so that the supplier can handle the first category of goods in time, achieve small profits but quick turnover, and avoid the long backlog of the first category of goods, thereby reducing the value of the first category of goods. If the inventory is small, it corresponds to a smaller enterprise scale, and the purchaser with a higher purchase price is recommended first, it is necessary to focus on the cost of the enterprise to maximize the benefits.

[0046] In some embodiments of the present application, if the commodity type is a second category commodity, the storage time limit of the second category commodity is greater than a preset storage threshold, that is, the second category commodity includes commodities that can be stored for a longer time, such as keyboards, mice, computers, etc.

[0047] Then, the server executes the above processing procedure when the inventory of the first category of goods is less than N, thereby determining the priority of the candidate buyers.

[0048] The embodiment of the present application gives priority to recommending purchasers with higher purchase unit prices for the second category of goods with a longer storage period, thereby helping to improve the interests of suppliers. For example, the purchaser has higher requirements for the quality of the goods, so the bid is also higher, and the quality requirements of the goods produced by the supplier are also high, which meets the needs of the purchaser. Therefore, recommending the purchaser to the supplier can achieve a mutually beneficial and win-win situation.

[0049] In some embodiments of the present application, in order to improve the matching degree between suppliers and candidate buyers, the server pre-sets a buyer screening model and then screens the candidate buyers.

[0050] Specifically, the server first extracts a plurality of candidate buyers from high to low according to the priorities of the candidate buyers, and determines the plurality of candidate buyers as buyers to be matched.

[0051] It should be noted that the specific number of multiple candidate buyers extracted from high to low can be set according to actual needs and is not limited here.

[0052] Then, the server matches the supply information with the purchasing information through the buyer screening model to determine the probability value of the supplier matching the buyer to be matched. If the probability value is greater than the preset matching threshold, the buyer to be matched is output to the supply plan. If the probability value is not greater than the preset matching threshold, the buyer to be matched is discarded.

[0053] Among them, the buyer screening model specifically includes: the server first obtains the supplier's supply rule table, wherein the supply rule table includes classification, matching fields, proportion scores and matching rules, etc.

[0054] Then, the server scores each matching field in the supply rule table, determines the percentage score of each matching field, and calculates the total score of the percentage scores.

[0055] For example, when a supplier logs in to use the e-commerce platform, he needs to set up a supply rule table, where the matching fields include the industry to which his company belongs and the types of goods produced. For buyers, the number of times the buyer has participated in the Canton Fair, the company type and the nature of the company. After the supply rule table is set up, it must be reviewed by the backend operation management personnel before it can take effect. As shown in Table 1:

[0056] Table 1

[0057]

[0058] Furthermore, the server matches the purchasing information of the candidate buyers to be matched in each matching field through the matching rules corresponding to each field, determines the score corresponding to each matching field according to the matching situation, and then counts the total score of the scores corresponding to each matching field, and finally calculates the ratio of the total score to the total score, and uses the ratio as the probability value of the supplier matching the buyer to be matched.

[0059] It should be noted that, in the embodiment of the present application, when matching the purchasing information of the candidate buyers through the matching rules corresponding to each field, the total score can be directly determined, or a matching table can be generated, that is, it can be set according to actual needs, and the present application does not limit this.

[0060] For example, a matching table is generated as shown in Table 2.

[0061] Table 2

[0062]

[0063] Then, the total score is 60 points, and the total score is 80 points. The ratio of the total score to the total score is 75%, that is, the probability value of the supplier matching the buyer to be matched is 75%.

[0064] The embodiment of the present application uses the supply rule table set by the supplier to find a matching buyer in the e-commerce platform and calculate the specific matching degree between the two parties, so as to accurately match the purchasing information published by the buyer that meets the matching rule requirements to the supplier.

[0065] Furthermore, in order to recommend new buyers on the e-commerce platform to suppliers in a timely manner, when adding buyers of new purchasing categories, the server matches the supply information with the purchasing information of the new buyers through the buyer screening model, and determines the probability value of the match between the supplier and the new buyers. If the probability value is greater than the preset matching threshold, the new buyer is recommended to the supplier. If the probability value is not greater than the preset matching threshold, the new buyer is discarded.

[0066] In some embodiments of the present application, since the matching rules set by the supplier may be imperfect, after the server recommends the corresponding purchaser in the supply plan to the supplier, it will obtain other purchasers that other suppliers in the same industry are interested in. The same industry means having the same production products, that is, the same types of goods. In addition, when other suppliers browse the purchase messages of the purchaser, they will add the purchasers they are interested in to their favorite lists. The server obtains other purchasers that other suppliers are interested in by querying the favorite lists of other suppliers.

[0067] Then, in order to determine whether the supplier is interested in other buyers, the server will recommend other buyers to the supplier and receive the supplier's first feedback. If the first feedback result is that the supplier is interested, a communication channel between the supplier and other buyers will be established. If the first feedback result is that the supplier is not interested, the other buyers will be discarded.

[0068] In some embodiments of the present application, because the purchaser has purchased other types of goods from the supplier in the past, but currently wants to purchase the above-mentioned types of goods, he may not have asked the supplier.

[0069] Therefore, the server determines the supplier's historical buyers within a preset time period, and then recommends the historical buyers to the supplier to determine whether the supplier is interested in the historical buyers, and receives the supplier's second feedback. If the second feedback result is that the supplier is interested, a communication channel is established between the supplier and the historical buyers. If the second feedback result is that the supplier is not interested, the historical buyers are discarded.

[0070] The embodiment of the present application recommends historical purchasers within a preset time period to the supplier, that is, historical purchasers who have recently cooperated with the e-commerce platform, so as to timely understand the dynamic needs of customers and help establish long-term cooperative relationships with historical purchasers.

[0071] Based on the same idea, some embodiments of the present application also provide devices and non-volatile computer storage media corresponding to the above methods.

[0072] Figure 2 A schematic diagram of an online business opportunity mining device for suppliers provided in an embodiment of the present application includes:

[0073] at least one processor; and,

[0074] a memory communicatively connected to the at least one processor; wherein,

[0075] The memory stores instructions executable by the at least one processor, the instructions being executed by the at least one processor to enable the at least one processor to:

[0076] Obtain supply information related to suppliers; supply information includes product types and product inventory;

[0077] Searching for commodity categories in the e-commerce platform and identifying candidate buyers who have commodity category purchasing needs;

[0078] If the commodity type is a first-category commodity, the enterprise scale of the supplier is determined based on the inventory of the commodity; the storage period of the first-category commodity shall not exceed the preset storage threshold;

[0079] Determine the priority of candidate buyers based on the priority determination plan corresponding to the enterprise size and the purchasing information of candidate buyers;

[0080] According to the priority, the supply information is matched with the procurement information, a supply plan is generated, and the corresponding buyers in the supply plan are recommended to the supplier.

[0081] Some embodiments of the present application provide corresponding Figure 1 A non-volatile computer storage medium for online business opportunity mining for suppliers, storing computer executable instructions, wherein the computer executable instructions are configured as follows:

[0082] Obtain supply information related to suppliers; supply information includes product types and product inventory;

[0083] Searching for commodity categories in the e-commerce platform and identifying candidate buyers who have commodity category purchasing needs;

[0084] If the commodity type is a first-category commodity, the enterprise scale of the supplier is determined based on the inventory of the commodity; the storage period of the first-category commodity shall not exceed the preset storage threshold;

[0085] Determine the priority of candidate buyers based on the priority determination plan corresponding to the enterprise size and the purchasing information of candidate buyers;

[0086] According to the priority, the supply information is matched with the procurement information, a supply plan is generated, and the corresponding buyers in the supply plan are recommended to the supplier.

[0087] Each embodiment in this application is described in a progressive manner, and the same or similar parts between the embodiments can be referred to each other, and each embodiment focuses on the differences from other embodiments. In particular, for the device and medium embodiments, since they are basically similar to the method embodiments, the description is relatively simple, and the relevant parts can be referred to the partial description of the method embodiments.

[0088] The devices and media provided in the embodiments of the present application correspond one-to-one to the methods. Therefore, the devices and media also have similar beneficial technical effects as the corresponding methods. Since the beneficial technical effects of the methods have been described in detail above, the beneficial technical effects of the devices and media will not be repeated here.

[0089] Those skilled in the art will appreciate that embodiments of the present invention may be provided as methods, systems, or computer program products. Therefore, the present invention may take the form of a complete hardware embodiment, a complete software embodiment, or an embodiment combining software and hardware. Moreover, the present invention may take the form of a computer program product implemented on one or more computer-usable storage media (including but not limited to disk storage, CD-ROM, optical storage, etc.) containing computer-usable program code.

[0090] The present invention is described with reference to flowcharts and / or block diagrams of methods, devices (systems), and computer program products according to embodiments of the present invention. It should be understood that each process and / or block in the flowchart and / or block diagram, as well as the combination of processes and / or blocks in the flowchart and / or block diagram, can be implemented by computer program instructions. These computer program instructions can be provided to a processor of a general-purpose computer, a special-purpose computer, an embedded processor, or other programmable data processing device to produce a machine, so that the instructions executed by the processor of the computer or other programmable data processing device generate instructions for implementing the processes in the flowchart and / or block diagram. Figure 1 A process or multiple processes and / or boxes Figure 1 A device that provides the functions specified in a block or multiple blocks.

[0091] These computer program instructions may also be stored in a computer-readable memory capable of directing a computer or other programmable data processing device to operate in a specific manner, so that the instructions stored in the computer-readable memory produce an article of manufacture comprising an instruction device, which implements the process Figure 1 A process or multiple processes and / or boxes Figure 1 A function specified in one or more boxes.

[0092] These computer program instructions can also be loaded onto a computer or other programmable data processing device so that a series of operating steps are executed on the computer or other programmable device to produce a computer-implemented process, thereby providing instructions for implementing the process. Figure 1 A process or multiple processes and / or boxes Figure 1 The steps for the functions specified in one or more boxes.

[0093] In a typical configuration, a computing device includes one or more processors (CPU), input / output interfaces, network interfaces, and memory.

[0094] The memory may include non-permanent storage in a computer-readable medium, random access memory (RAM) and / or non-volatile memory in the form of read-only memory (ROM) or flash RAM. The memory is an example of a computer-readable medium.

[0095] Computer readable media include permanent and non-permanent, removable and non-removable media that can be implemented by any method or technology to store information. Information can be computer readable instructions, data structures, program modules or other data. Examples of computer storage media include, but are not limited to, phase change memory (PRAM), static random access memory (SRAM), dynamic random access memory (DRAM), other types of random access memory (RAM), read-only memory (ROM), electrically erasable programmable read-only memory (EEPROM), flash memory or other memory technology, compact disk read-only memory (CD-ROM), digital versatile disk (DVD) or other optical storage, magnetic cassettes, magnetic tape magnetic disk storage or other magnetic storage devices or any other non-transmission media that can be used to store information that can be accessed by a computing device. As defined herein, computer readable media does not include temporary computer readable media (transitory media), such as modulated data signals and carrier waves.

[0096] It should also be noted that the terms "include", "comprises" or any other variations thereof are intended to cover non-exclusive inclusion, so that a process, method, commodity or device including a series of elements includes not only those elements, but also other elements not explicitly listed, or also includes elements inherent to such process, method, commodity or device. In the absence of more restrictions, the elements defined by the sentence "comprises a ..." do not exclude the existence of other identical elements in the process, method, commodity or device including the elements.

[0097] The above is only an embodiment of the present application and is not intended to limit the present application. For those skilled in the art, the present application may have various changes and variations. Any modification, equivalent replacement, improvement, etc. made within the technical principle of the present application should all fall within the protection scope of the present application.

Claims

1. A method for mining online business opportunities for suppliers, characterized in that: The method comprises: Obtaining supply information related to suppliers; the supply information includes commodity types and commodity inventory; Retrieving the commodity category in the e-commerce platform and determining candidate buyers who have procurement needs for the commodity category; If the commodity type is a first category commodity, the enterprise scale of the supplier is determined according to the inventory of the commodity; the storage time limit of the first category commodity is not greater than a preset storage threshold; Determine the priority of the candidate purchaser according to the priority determination scheme corresponding to the enterprise scale and the purchasing information of the candidate purchaser; According to the priority, the supply information is matched with the purchase information to generate a supply plan, and the purchaser corresponding to the supply plan is recommended to the supplier; Determining the enterprise scale of the supplier according to the inventory of the goods specifically includes: Determine whether the inventory of the product is greater than a preset quantity N; If so, the enterprise scale of the supplier is the first enterprise scale; The step of determining the priority of the candidate purchaser according to the priority determination scheme corresponding to the enterprise scale and the purchase information of the candidate purchaser specifically includes: Determine the time difference between the purchase time of the purchase information and the current time; Sorting the time differences from small to large to obtain a first sorting result queue; In the first sorting result queue, the priority of the candidate purchasers is determined; the smaller the value of the time difference is, the higher the priority is.

2. The method according to claim 1, characterized in that Determining the enterprise scale of the supplier according to the inventory of the goods specifically includes: Determine whether the inventory of the product is greater than a preset quantity N; If not, the enterprise size of the supplier is the second enterprise size; The step of determining the priority of the candidate purchaser according to the priority determination scheme corresponding to the enterprise scale and the purchase information of the candidate purchaser specifically includes: Determine the purchase unit price of the purchase information; Sorting the purchase unit prices from high to low to obtain a second sorting result queue; In the second sorting result queue, the priority of the candidate purchasers is determined; the higher the value of the purchase unit price, the higher the priority.

3. The method according to claim 1, characterized in that The matching of the supply information with the purchase information according to the priority to determine the supply plan specifically includes: According to the priorities, extracting multiple candidate buyers from high to low, and determining the multiple candidate buyers as buyers to be matched; Matching the supply information with the purchase information through a buyer screening model to determine a probability value of matching the supplier with the buyer to be matched; If the probability value is greater than a preset matching threshold, the purchaser to be matched is output to the supply plan.

4. The method according to claim 3, characterized in that The matching of the supply information with the purchase information through the purchaser screening model to determine the probability value of the supplier matching the purchaser to be matched specifically includes: Determine a supply rule table of the supplier; the supply rule table includes matching fields, percentage scores, and matching rules; Scoring each matching field in the supply rule table to determine a percentage score of each matching field in the supply rule table; Calculate the total score of the percentage scores; In each matching field, the purchasing information is matched according to the matching rule to determine a score corresponding to each matching field; Counting the total score of the scores corresponding to the matching fields; The ratio of the total score to the total score is determined, and the ratio is used as a probability value of the supplier matching the purchaser to be matched.

5. The method according to claim 3, characterized in that: If the probability value is greater than a preset matching threshold, after outputting the to-be-matched purchaser to the supply plan, the method further includes: If a new buyer who purchases the commodity type is added, the supply information is matched with the purchase information of the new buyer through the buyer screening model to determine the probability value of the supplier matching the new buyer; If the probability value is greater than the preset matching threshold, the new purchaser is recommended to the supplier.

6. The method according to claim 1, characterized in that After recommending to the supplier the purchaser corresponding to the supply plan, the method further includes: Identify other buyers who may be of interest to other suppliers in the same industry as the supplier; recommending the other buyers to the supplier to determine whether the supplier is interested in the other buyers; receiving a first feedback from the supplier and obtaining a first feedback result; If the first feedback result is interest, a communication channel is established between the supplier and the other purchaser.

7. The method according to claim 1, characterized in that After recommending to the supplier the purchaser corresponding to the supply plan, the method further includes: Determining historical purchasers of the supplier within a preset time period; recommending the historical purchaser to the supplier to determine whether the supplier is interested in the historical purchaser; receiving a second feedback from the supplier and obtaining a second feedback result; If the second feedback result is interest, a communication channel is established between the supplier and the historical purchaser.

8. An online business opportunity mining device for suppliers, characterized in that: include: at least one processor; as well as, a memory communicatively connected to the at least one processor; wherein, The memory stores instructions executable by the at least one processor, the instructions being executed by the at least one processor to enable the at least one processor to: Obtaining supply information related to suppliers; the supply information includes commodity types and commodity inventory; Retrieving the commodity category in the e-commerce platform and determining candidate buyers who have procurement needs for the commodity category; If the commodity type is a first category commodity, the enterprise scale of the supplier is determined according to the inventory of the commodity; the storage time limit of the first category commodity is not greater than a preset storage threshold; Determine the priority of the candidate purchaser according to the priority determination scheme corresponding to the enterprise scale and the purchasing information of the candidate purchaser; According to the priority, the supply information is matched with the purchase information to generate a supply plan, and the purchaser corresponding to the supply plan is recommended to the supplier; Determining the enterprise scale of the supplier according to the inventory of the goods specifically includes: Determine whether the inventory of the product is greater than a preset quantity N; If so, the enterprise scale of the supplier is the first enterprise scale; The step of determining the priority of the candidate purchaser according to the priority determination scheme corresponding to the enterprise scale and the purchase information of the candidate purchaser specifically includes: Determine the time difference between the purchase time of the purchase information and the current time; Sorting the time differences from small to large to obtain a first sorting result queue; In the first sorting result queue, the priority of the candidate purchasers is determined; the smaller the value of the time difference is, the higher the priority is.

9. A non-volatile computer storage medium for online business opportunity mining for suppliers, storing computer executable instructions, characterized in that: The computer executable instructions are configured to: Obtaining supply information related to suppliers; the supply information includes commodity types and commodity inventory; Retrieving the commodity category in the e-commerce platform and determining candidate buyers who have procurement needs for the commodity category; If the commodity category is the first category of commodities, the enterprise scale of the supplier is determined according to the inventory of the commodities; The storage period of the first category of goods is not greater than a preset storage threshold; Determine the priority of the candidate purchaser according to the priority determination scheme corresponding to the enterprise scale and the purchasing information of the candidate purchaser; According to the priority, the supply information is matched with the purchase information to generate a supply plan, and the purchaser corresponding to the supply plan is recommended to the supplier; Determining the enterprise scale of the supplier according to the inventory of the goods specifically includes: Determine whether the inventory of the product is greater than a preset quantity N; If so, the enterprise scale of the supplier is the first enterprise scale; The step of determining the priority of the candidate purchaser according to the priority determination scheme corresponding to the enterprise scale and the purchase information of the candidate purchaser specifically includes: Determine the time difference between the purchase time of the purchase information and the current time; Sorting the time differences from small to large to obtain a first sorting result queue; In the first sorting result queue, the priority of the candidate purchasers is determined; the smaller the value of the time difference is, the higher the priority is.

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