Transaction inquiry matching method and device and storage medium
By automatically matching intention and inquiry information through a matching engine and calculating weight values based on the time and quantity of intention, the problem of low efficiency and poor reliability in investment transactions in existing technologies is solved, thereby achieving automation and improved accuracy in investment transactions.
Patent Information
- Authority / Receiving Office
- CN · China
- Patent Type
- Applications(China)
- Current Assignee / Owner
- Filing Date
- 2025-12-17
- Publication Date
- 2026-03-27
AI Technical Summary
In existing technologies, investment transactions conducted manually suffer from low efficiency and poor reliability.
The system uses a matching engine to automatically match intention and inquiry information, calculates weight values based on the time and quantity of intentions, and sorts them according to the weight values to automate investment transactions and optimize them under multiple conditions.
It improves the accuracy and efficiency of investment transaction matching and automates the investment transaction process.
Smart Images
Figure CN121746071A_ABST
Abstract
Description
Technical Field
[0001] This application relates to the field of computer technology, and more specifically, to a transaction inquiry matching method, device, and storage medium. Background Technology
[0002] In the investment and trading process in the financial market, investment managers first need to determine their investment intentions. Then, traders manually compile the investment intentions and inquiry information, and inquire about, quote, and provide feedback on the transaction results to the counterparty.
[0003] However, existing technologies for investment transactions via manual methods suffer from low efficiency and poor reliability. Summary of the Invention
[0004] The purpose of this application is to address the shortcomings of the prior art by providing a transaction inquiry and matching method, device, and storage medium to solve the problems of low efficiency and poor reliability in investment transactions conducted manually in the prior art.
[0005] To achieve the above objectives, the technical solution adopted in this application is as follows: In a first aspect, this application provides a transaction inquiry matching method applied to an electronic device, wherein the electronic device is equipped with a matching engine, and the method includes: Obtain a set of intention information from a first user and a set of inquiry information from a second user, wherein the set of intention information includes at least one set of intention information and the set of inquiry information includes at least one set of inquiry information; Run the matching engine, which traverses each inquiry in the inquiry information set, and for the current inquiry, matches the current inquiry with each intention in the intention information set to determine at least one candidate intention corresponding to the current inquiry. The matching engine determines the weight value of each candidate intention information based on the intention delivery time and intention delivery amount of each candidate intention information; The matching engine distributes the inquiry quantity corresponding to each inquiry information to each of the candidate intention information according to the weight value of each candidate intention information, thereby obtaining the inquiry result of each candidate intention information; Based on the inquiry results of each candidate intention information and the preset business template, generate and execute business instructions.
[0006] Optionally, the intention information includes: intended product information, transaction direction, and intended transaction type; the inquiry information includes: inquiry product information, transaction direction, and inquiry transaction type. The step of matching the current inquiry with each piece of intent information in the intent information set to determine at least one candidate intent information corresponding to the current inquiry information includes: Determine whether the intent information includes an intent product identifier; If the intention information does not include an intention product identifier, then the intention product information and transaction direction of the intention information are matched with the inquiry product information and transaction direction of the inquiry information to determine at least one candidate intention information corresponding to the inquiry information. If the intention information includes an intention product identifier, then the transaction direction of the intention information is matched with the transaction direction of the inquiry information to determine at least one candidate intention information corresponding to the inquiry information; Matching the intended transaction type and the inquiry transaction type to determine at least one candidate intended transaction information corresponding to the inquiry information.
[0007] Optionally, the step of matching the intended product information and transaction direction of the intention information with the inquiry product information and transaction direction of the inquiry information to determine at least one candidate intention information corresponding to the inquiry information includes: Based on the inquiry product information and the intended product information, at least one initial intention information corresponding to the inquiry information is determined; The initial intention information is filtered according to the transaction direction of the inquiry information, and the initial intention information that is consistent with the transaction direction is selected as candidate intention information.
[0008] Optionally, the inquiry information includes: a specified user identifier; The step of matching the intended transaction type and the inquiry transaction type to determine at least one candidate intended transaction information corresponding to the inquiry information includes: If a specified user identifier exists in the inquiry information, at least one target candidate intention information corresponding to the specified user identifier is determined, and the intention transaction type of the target candidate intention information and the inquiry transaction type are matched to determine at least one alternative intention information corresponding to the inquiry information in the target candidate intention information. If the inquiry information does not contain a specified user identifier, then the at least one candidate intention information corresponding to the inquiry information is determined by matching the intended transaction type and the inquiry transaction type.
[0009] Optionally, determining the weight value of each candidate intention information based on the intention delivery time and intention delivery amount includes: Obtain the first weight corresponding to the issuance time and the second weight corresponding to the issuance quantity; The weight value of the candidate intention information is determined based on the preset weight model, the first weight, the second weight, the intention delivery time of the candidate intention information, and the intention delivery amount.
[0010] Optionally, determining the weight value of the candidate intention information based on a preset weight model, the first weight, the second weight, the intention delivery time of the candidate intention information, and the intention delivery quantity includes: The first weight, the second weight, the intention delivery time and intention delivery amount of the candidate intention information are input into the weight model to calculate the weight value of the candidate intention information. The weighting model is: score = W1 × TIME + W2 × AMOUNT, where score is the weight value, W1 is the first weight, W2 is the second weight, TIME is the intention delivery time, and AMOUNT is the intention delivery amount.
[0011] Optionally, the step of allocating the inquiry quantity corresponding to each inquiry information to each of the candidate intention information according to the weight value of each candidate intention information, to obtain the inquiry result of each candidate intention information, includes: The candidate intention information is sorted according to the weight value of each candidate intention information to obtain a list of intention information; Traverse the list of intent information, starting from the candidate intent information with the largest weight value in the list of intent information, and split the inquiry quantity to the candidate intent information according to the intention delivery quantity of the candidate intent information, until the inquiry quantity is equal to zero, to obtain the split inquiry quantity of each candidate intent information. Based on the breakdown of the inquiry volume for each candidate intention information, the inquiry results for each candidate intention information are generated.
[0012] Optionally, the step of generating and executing business instructions based on the inquiry results of each candidate intention information and a preset business template includes: At least one query keyword is extracted from the query results; Fill the corresponding positions of the inquiry keywords into the business template to obtain and execute the business instructions.
[0013] Secondly, embodiments of this application also provide an electronic device, including: a processor, a storage medium, and a bus, wherein the storage medium stores machine-readable instructions executable by the processor, and when the electronic device is running, the processor communicates with the storage medium via the bus, and the processor executes the machine-readable instructions to perform the steps of a transaction inquiry matching method as described in any one of the first aspects.
[0014] Thirdly, embodiments of this application also provide a computer-readable storage medium storing a computer program, which, when executed by a processor, performs the steps of a transaction inquiry matching method as described in any one of the first aspects.
[0015] The beneficial effects of this application are: by automatically matching intention information and inquiry information through a matching engine, calculating weight values based on the intention delivery time and intention delivery volume of the intention information, and sorting according to the weight values, investment transactions can be automated. Furthermore, by optimizing the matching results through multi-dimensional conditions and weight values, the accuracy and efficiency of investment transaction matching can be improved.
[0016] To make the above-mentioned objectives, features and advantages of this application more apparent and understandable, preferred embodiments are described below in detail with reference to the accompanying drawings. Attached Figure Description
[0017] To more clearly illustrate the technical solutions of the embodiments of this application, the accompanying drawings used in the embodiments will be briefly introduced below. It should be understood that the following drawings only show some embodiments of this application and should not be regarded as a limitation of the scope. For those skilled in the art, other related drawings can be obtained based on these drawings without creative effort.
[0018] Figure 1 This illustration shows an application scenario provided by an embodiment of this application. Figure 2 A flowchart of a transaction inquiry and matching method provided in an embodiment of this application is shown; Figure 3 This document illustrates a flowchart of a method for determining candidate intention information, as provided in an embodiment of this application. Figure 4 This document illustrates a flowchart of a method for determining candidate intention information, as provided in an embodiment of this application. Figure 5 This document illustrates a flowchart illustrating yet another method for determining candidate intention information provided in an embodiment of this application. Figure 6 A flowchart illustrating a method for determining weight values according to an embodiment of this application is shown; Figure 7 This document illustrates a flowchart of a method for generating inquiry results, as provided in an embodiment of this application. Figure 8 This document illustrates a flowchart of a method for generating business instructions according to an embodiment of this application. Figure 9 This paper presents an overall flowchart of a transaction inquiry and matching method provided in an embodiment of this application; Figure 10This illustration shows a schematic diagram of a transaction inquiry and matching device provided in an embodiment of this application; Figure 11 A schematic diagram of the structure of an electronic device provided in an embodiment of this application is shown. Detailed Implementation
[0019] To make the objectives, technical solutions, and advantages of the embodiments of this application clearer, the technical solutions of the embodiments of this application will be clearly and completely described below with reference to the accompanying drawings. Obviously, the described embodiments are only some embodiments of this application, and not all embodiments. The components of the embodiments of this application described and shown in the accompanying drawings can generally be arranged and designed in various different configurations. Therefore, the following detailed description of the embodiments of this application provided in the accompanying drawings is not intended to limit the scope of the claimed application, but merely represents selected embodiments of this application. All other embodiments obtained by those skilled in the art based on the embodiments of this application without inventive effort are within the scope of protection of this application.
[0020] It should be noted that the term "comprising" will be used in the embodiments of this application to indicate the presence of the features declared thereafter, but does not exclude the addition of other features.
[0021] In the current financial investment and trading field, investment transactions heavily rely on manual processes. Specifically, investment managers' investment intentions need to be manually compiled by traders, and transaction inquiry results are mainly fed back through instant messaging tools. This traditional model is an operational paradigm formed in the early stages of financial market development. In traditional scenarios with smaller transaction volumes and slower market pace, it could basically meet basic trading needs and was therefore widely used in the industry for a long time.
[0022] Investment managers' investment intentions are scattered across the personal work devices of different traders or departments, lacking a unified centralized information management platform and real-time sharing mechanism. When price matching is required, traders need to spend a significant amount of time collecting investment intention information across departments and personnel. This not only prolongs information acquisition time but also may result in omissions or delays during information transmission, causing some valid investment intentions to be excluded from the price matching scope, thus reducing information utilization and the comprehensiveness of the matching. Secondly, the matching process between intentions and prices relies entirely on manual comparison, leading to low trading efficiency and insufficient matching accuracy.
[0023] Therefore, how to automate investment transactions and improve the accuracy and efficiency of investment transaction matching has become a problem that needs to be solved.
[0024] like Figure 1The diagram illustrates an application scenario of a transaction inquiry matching method. An electronic device is equipped with a transaction inquiry matching system, which includes a matching engine. The scenario involves two types of tasks: investment managers and traders. Investment managers can input users' investment needs into the system, forming a set of intention information. Traders can input market inquiry information into the system, forming a set of inquiry information. The matching engine matches the intention information set and the inquiry information set, enabling the splitting of the inquiry information. It then pushes the corresponding intention list, the split inquiry volume, and the score to the investment manager's trading terminal for confirmation. After confirmation, the system converts the matching results into standardized trading instructions and executes them.
[0025] Next, combine Figure 1 The application scenarios shown are for Figure 2 The transaction inquiry matching method shown is explained below, such as Figure 2 As shown, the method includes: S201. Obtain the set of intention information of the first user and the set of inquiry information of the second user.
[0026] The intention information set includes at least one intention information set, and the inquiry information set includes at least one inquiry information set.
[0027] Reference Figure 1 The first user can be Figure 1 The first user can be an investment manager, and the second user can be a trader. Intent information can be uploaded to the electronic device by the first user via trading terminal, API, or batch file import. Quotation information can be uploaded to the electronic device by the second user via trading terminal, API, text semantic recognition, or batch file import.
[0028] After receiving intention information and inquiry information, electronic devices can clean, format, and structure the intention information from different sources, establish standardized fields, and persistently store them in a database to obtain a set of intention information. Similarly, they can clean, format, and structure the inquiry information from different sources, establish standardized fields, and persistently store them in a database to obtain a set of inquiry information.
[0029] Taking financial investment transactions as an example, the standardized fields for intention information can include bond code, bond name, maturity date, yield, etc., while the standardized fields for inquiry information can include bond code, bond name, trading day, yield, net price, full price, etc.
[0030] S202. Run the matching engine. The matching engine traverses each inquiry in the inquiry information set. For the current inquiry, it matches the current inquiry with each intention in the intention information set to determine at least one candidate intention corresponding to the current inquiry.
[0031] The matching engine in the electronic device is activated. The engine iterates through each current inquiry in the inquiry information set and compares it with all intention information in the intention information set according to rules. The intention information that meets the matching conditions is then selected as the candidate intention information corresponding to the current inquiry information.
[0032] In one possible implementation, the queuing information can be traversed according to the urgency of each queuing information in the queuing information set. For example, the queuing information can be sorted according to the number of queuing information and the upload time of the queuing information, and the queuing information with a large number of queuing information and an early upload time can be processed first.
[0033] The current inquiry information can be a specific inquiry that the matching engine is currently comparing while iterating through the inquiry information.
[0034] Optionally, for the current inquiry information that has been traversed, the full set of intention information in the intention information set can be filtered and matched, so as to obtain at least one candidate intention information corresponding to the current inquiry information from the intention information set.
[0035] The candidate information can be information that matches the current inquiry information according to preset matching rules after being compared by the matching engine.
[0036] S203. The matching engine determines the weight value of each candidate intention information based on the intention delivery time and intention delivery amount of each candidate intention information.
[0037] Optionally, the intention submission time can be the specific time when the first user submits the intention information to the electronic device. The intention submission quantity can be the transaction quantity specified in the intention information. The weight value is used to measure the priority of the candidate intention information; the higher the weight value, the higher the priority of the candidate intention information.
[0038] It should be noted that determining the weight value based on the intention delivery time and the intention delivery quantity is only one possible implementation method given in this application. The weight value can also be determined according to the urgency of each candidate intention information. For example, the weight value can be determined according to the deadline and the intention delivery quantity of each candidate intention information. Candidate intention information with a higher intention delivery quantity and a closer deadline can be given a higher weight value, thereby giving it a higher priority.
[0039] S204. The matching engine allocates the inquiry quantity corresponding to each candidate intention information to each candidate intention information according to the weight value of each candidate intention information, and obtains the inquiry result of each candidate intention information.
[0040] The inquiry volume can be the total quantity or total resources desired to be traded as specified in the inquiry information. The matching engine can determine the priority of each candidate intention information according to its weight value, and then allocate the inquiry volume to each candidate intention information according to the priority to ensure that the total amount is allocated.
[0041] The inquiry results can be the corresponding data of the candidate intentions and the split inquiry volume after the candidate intention information is sorted by weight and split by inquiry volume. The inquiry results include the final inquiry volume allocated to the candidate intention information and the core fields of the candidate intention information.
[0042] S205. Generate and execute business instructions based on the inquiry results of each candidate intention information and the preset business template.
[0043] The preset business template can be a pre-configured standardized instruction format template, which includes fixed fields required by the business instruction and reserved fill positions. The field format can be pre-configured according to the interface requirements of the transaction system.
[0044] Optionally, keyword fields corresponding to reserved fill positions can be pre-configured in the inquiry results of the candidate intention information. When generating business instructions, keywords are extracted from the candidate intention information according to the keyword fields and filled into the reserved fill positions to obtain business instructions.
[0045] In this embodiment, the matching engine automatically matches intention information and inquiry information, calculates weight values based on the intention delivery time and quantity of the intention information, and sorts them according to the weight values. This can automate investment transactions, and by optimizing the matching results through multi-dimensional conditions and weight values, the accuracy and efficiency of investment transaction matching can be improved.
[0046] Optionally, the intention information includes: intended product information, transaction direction, and intended transaction type; the inquiry information includes: inquiry product information, transaction direction, and inquiry transaction type.
[0047] The transaction direction defines the type of transaction, i.e., buying or selling. The intended transaction type and the inquiry transaction type differentiate the business categories of the transaction, such as spot trading and repurchase transactions in bond trading, and subscription and redemption in fund trading. The intended transaction type and the inquiry transaction type limit the scope of the business scenarios for the intended and inquiry transactions.
[0048] The following is a further explanation of how the above process of matching the current inquiry with the various intention information sets to determine at least one candidate intention information corresponding to the current inquiry information is performed. Figure 3 As shown, the above step S202 includes: S301. Determine whether the intent information includes the intended product identifier.
[0049] The intended product identifier can be a unique code or identifier for the product, such as a bond code for a bond, a stock code for a stock, or a fund code for a fund.
[0050] S302. If the intention information does not include the intention product identifier, then the intention product information and transaction direction of the intention information are matched with the inquiry product information and transaction direction of the inquiry information to determine at least one candidate intention information corresponding to the inquiry information.
[0051] If the intent information does not include the intended product identifier, it can be considered a vague intent, without specifying a particular product category. The target of the intent information is products that meet a certain category of characteristics, rather than a specific product.
[0052] When the intended product identifier is not included, the intended information can be filtered from the dimensions of intended product information and transaction direction, and the intended information that matches the inquiry product information and transaction direction can be used as candidate intended information.
[0053] S303. If the intention information includes an intention product identifier, then match the transaction direction of the intention information with the transaction direction of the inquiry information to determine at least one candidate intention information corresponding to the inquiry information.
[0054] If the intention information includes an intended product identifier, then the intention information can be considered a precise intention. In this case, the target of the intention information is a type of product indicated by the intended product identifier. Matching can then be performed from the transaction direction dimension, matching inquiry information that matches the product indicated by the intended product identifier with the intention information, thereby determining at least one candidate intention information corresponding to the inquiry information.
[0055] S304. Match the intended transaction type and the inquiry transaction type to determine at least one candidate intended transaction information corresponding to the inquiry information.
[0056] After identifying candidate intention information, matching can be performed based on the transaction type, and candidate intention information whose transaction type matches the inquiry information can be selected as potential intention information.
[0057] It should be noted that the order of the dimensions matched in steps S301-S304 above can be changed. For example, matching can be performed first based on the intended transaction type and the inquiry transaction type, and then matching can be performed based on the product intention identifier, transaction direction and product information. The specific order is not limited in this application.
[0058] The following is a further explanation of how the intended product information and transaction direction based on the above-mentioned intention information are matched with the inquiry product information and transaction direction in the inquiry information to determine at least one candidate intention information corresponding to the inquiry information. Figure 4 As shown, when the intent information is ambiguous, the above step S302 includes: S401. Match the inquiry product information and the intended product information to determine at least one initial intention information corresponding to the inquiry information.
[0059] Optionally, the information on the intended product includes: product type, product term range, and product source; the information on the product for which a quote is requested includes: product type, product term range, and product source.
[0060] Among these, "product type" can refer to the specific category of the traded product. For example, in the bond market, it can be subdivided into government bonds, corporate bonds, and company bonds; in the fund market, it can be subdivided into money market funds, bond funds, and equity funds. "Product maturity range" can refer to the duration of the traded product. "Product source" can refer to the issuing entity or management institution of the product.
[0061] By matching inquiry product information and intended product information, initial intention information that matches the product characteristics of the inquiry product information can be filtered out from all intention information.
[0062] S402. Filter the initial intention information according to the transaction direction of the inquiry information, and obtain the initial intention information that is consistent with the transaction direction as candidate intention information.
[0063] Based on the initial intention information obtained through screening, the transaction direction of the initial intention information can be further filtered, and the intentions that are consistent with the transaction direction of the inquiry can be retained as candidate intention information.
[0064] It should be noted that the execution order of steps S401 and S402 can be reversed or executed simultaneously. That is, the transaction direction can be matched first, followed by the product information, or the transaction direction and product information can be filtered at the same time to finally obtain candidate intention information.
[0065] For example, a first user submits a vague intention to the system without a bond code, and a second user submits inquiry information for a certain type of bond. The system filters the intention information based on the term range, product type, and product source in the inquiry information to obtain initial intention information that is consistent with the term range, product type, and product source of the inquiry information. Then, the initial intention information is filtered according to the transaction direction to obtain initial intention information that is consistent with the transaction direction of the inquiry information as candidate intention information.
[0066] Optionally, the inquiry information includes: a specified user identifier.
[0067] The inquiry information can specify a first user. If the inquiry information specifies a first user, it can include a specified user identifier. The specified user identifier can be the identifier of the specified first user.
[0068] The above steps, which match the intended transaction type and the inquiry transaction type to determine at least one candidate intended transaction information corresponding to the inquiry information, are as follows: Figure 5 As shown, it includes: S501. If a specified user identifier exists in the inquiry information, at least one target candidate intention information corresponding to the specified user identifier is determined, and the intention transaction type and inquiry transaction type of the target candidate intention information are matched to determine at least one alternative intention information corresponding to the inquiry information in the target candidate intention information.
[0069] The target candidate intention information corresponding to the specified user identifier can be the intention information submitted by the first user indicated by the specified user identifier.
[0070] If the inquiry information includes a specified user identifier, then candidate intention information can be filtered according to the specified user identifier. The candidate intention information uploaded by the first user indicated by the specified user identifier is determined as the target candidate intention information. Based on the matching of the intention transaction type and the inquiry transaction type, the target candidate intention information with the same intention transaction type and inquiry transaction type is selected as the candidate intention information.
[0071] For example, assuming the candidate intention information includes the intentions of Manager Zhang and Manager Li, if the user of the inquiry instruction is Manager Zhang, then Manager Zhang's intention information can be used as the target candidate intention information. Subsequently, only the target candidate intention information of Manager Zhang will be matched for transaction type to avoid interference from irrelevant user intentions.
[0072] S502. If there is no specified user identifier in the inquiry information, then match the intended transaction type and the inquiry transaction type to determine at least one candidate intended information corresponding to the inquiry information.
[0073] If the inquiry information does not have a specified user identifier, it means that no first user has been specified. In this case, it can be matched according to the intended transaction type and the inquiry transaction type, and the intended transaction information corresponding to the intended transaction type that is consistent with the inquiry transaction type will be used as the candidate intended transaction information.
[0074] If the number of candidate information corresponding to the inquiry information is one, the inquiry information and the candidate information can be directly matched to generate the inquiry result of the candidate information. Based on the inquiry result of the candidate information and the preset business template, business instructions can be generated and executed.
[0075] If there are multiple candidate intentions corresponding to the inquiry information, the inquiry quantity can be split among the multiple candidate intentions. The following is a further explanation of determining the weight value of each candidate intention based on the intention submission time and intention submission quantity. Figure 6 As shown, the above step S203 includes: S601. Obtain the first weight corresponding to the issuance time and the second weight corresponding to the issuance amount.
[0076] The first weight is a pre-set coefficient used to measure the contribution of the intention delivery time to the weight value, and the second weight is a pre-set coefficient used to measure the contribution of the intention delivery amount to the weight value.
[0077] S602. Determine the weight value of the candidate intention information based on the preset weight model, the first weight, the second weight, the intention delivery time of the candidate intention information, and the intention delivery amount.
[0078] The first weight, the second weight, the intention delivery time of the candidate intention information, and the intention delivery amount are input into the weight model to calculate the weight value of the candidate intention information.
[0079] The weighting model is: score = W1 × TIME + W2 × AMOUNT, where score is the weight value, W1 is the first weight, W2 is the second weight, TIME is the time of intention delivery, and AMOUNT is the amount of intention delivery.
[0080] In one possible implementation, the time interval between the intention delivery time and the current time can be calculated, and a weight value can be calculated based on the intention delivery time and the intention delivery amount.
[0081] For example, assuming the intention delivery time is 8:00, the intention delivery amount is 1000, the first weight is 0.6, the second weight is 0.4, and the current time is 9:00, then the TIME in the above formula can be determined to be 23, and the weight value score_ = 0.6×23 + 0.4×1000 = 13.8 + 400 = 413.8 is calculated.
[0082] In this embodiment of the application, by quantifying the impact of the intention delivery time and the intention delivery quantity on the weight value, the ranking of candidate intention information can be standardized, avoiding subjective bias.
[0083] In another possible implementation, a dynamic weight model can be established, incorporating dynamic factors such as market fluctuations, user historical trading preferences, and product risk levels into the dynamic weight model to establish a multi-factor dynamic weight system, thereby enabling the weight parameters to be automatically optimized as the scenario changes.
[0084] To assign weights to market volatility, real-time data can be introduced, and the volatility of the real-time data can be monitored. Different volatility values correspond to different weight values, thereby dynamically adjusting the weight values of market factors based on the volatility of the real-time data.
[0085] To weight users' historical transaction preferences, historical behavior profiles of the first and second users can be created based on their historical data, and then the weights of user preference factors can be adjusted. For example, if 80% of the first user's historical transactions involve products within 3 years, then the weight of the first user's term matching can be automatically increased by 10%.
[0086] The weighting of product risk levels can be adjusted according to the product risk level, for example, automatically reducing the quantity weighting of high-risk products.
[0087] The weighted model can be expressed as follows: score=(W1×TIME)×M+(W2×AMOUNT)×U+(W3×RISK)×R Where M is the market activity coefficient, U is the user preference coefficient, R is the risk adjustment coefficient, and W3 is the risk weight.
[0088] The following explains the process of allocating the inquiry quantity corresponding to each candidate intention information to each candidate intention information based on the weight value of each candidate intention information, thereby obtaining the inquiry result for each candidate intention information. Figure 7 As shown, the above step S204 includes: S701. Sort each candidate intention information according to its weight value to obtain a list of intention information.
[0089] S702. Traverse the list of intent information, starting from the candidate intent information with the largest weight value in the list, and allocate the inquiry quantity to the candidate intent information according to the intended delivery quantity of the candidate intent information, until the inquiry quantity is equal to zero, and obtain the allocated inquiry quantity of each candidate intent information.
[0090] Optionally, if the candidate intention information is sorted from largest to smallest according to the weight value to obtain a list of intention information, the inquiry quantity can be split starting from the first candidate intention information in the list, first satisfying the candidate intention information that is ranked first, until the total amount split is consistent with the inquiry quantity.
[0091] S703. Generate the inquiry results for each candidate intention information based on the split inquiry volume of each candidate intention information.
[0092] If the split inquiry volume meets the quantity of candidate intention information to be issued, then the candidate intention information and the split inquiry volume can be recorded as the inquiry result of the candidate intention information.
[0093] If the split inquiry volume does not meet the quantity of candidate intention information to be issued, the candidate intention information and the split inquiry volume can be recorded, and the candidate intention information can continue to be matched with inquiry information until the split inquiry volume meets the quantity of candidate intention information to be issued.
[0094] The following is a further explanation of how business instructions are generated and executed based on the inquiry results of each candidate intention and the preset business template, such as... Figure 8 As shown, the above step S205 includes: S801. Extract at least one query keyword from the query results.
[0095] S802. Fill each inquiry keyword into the corresponding position in the business template to obtain and execute the business instruction.
[0096] The inquiry keywords can be pre-configured. The inquiry keywords include keywords for intent information and the split inquiry volume. By filling the inquiry keywords into the preset fill positions of the business template, business instructions can be obtained.
[0097] In the business scenario of investment transactions, after the inquiry result is generated, the inquiry result can be sent to the first user for transaction confirmation. After confirmation, the above steps S801-S802 are executed to generate a business instruction, and the business instruction is sent to the transaction system for execution. After the transaction system completes the execution, the execution result is fed back to the user terminal corresponding to the intention information and the inquiry information.
[0098] Next, combine Figure 9 This section describes the overall process of this application. (Refer to...) Figure 9After entering the inquiry information and intention information, it can first determine whether the intention product identifier is included. If the intention product identifier is not included, fuzzy intention matching is performed, and matching is performed based on the intention product information and the inquiry product information. If the intention product identifier is included, precise intention matching is performed, and precise matching is performed based on the intention product identifier. Then, matching is performed based on the transaction direction, specified user identifier, and product type to obtain at least one candidate intention information. If multiple candidate intention information are included, the weight value is calculated and sorted from largest to smallest according to the weight value. Then, the inquiry volume is split according to the sorting result, and finally, the inquiry result is generated.
[0099] Based on the same inventive concept, this application also provides a transaction inquiry matching device corresponding to the transaction inquiry matching method. Since the principle of the device in this application is similar to the transaction inquiry matching method described above in this application, the implementation of the device can refer to the implementation of the method, and the repeated parts will not be described again.
[0100] Figure 10 A schematic diagram of a transaction inquiry and matching device provided in an embodiment of this application is shown.
[0101] The acquisition module 1001 is used to acquire the intention information set of the first user and the inquiry information set of the second user. The intention information set includes at least one intention information and the inquiry information set includes at least one inquiry information. The matching module 1002 is used to run the matching engine, which traverses each inquiry information in the inquiry information set, and for the current inquiry information that has been traversed, matches the current inquiry with each intention information in the intention information set to determine at least one candidate intention information corresponding to the current inquiry information. The determination module 1003 is used by the matching engine to determine the weight value of each candidate intention information based on the intention delivery time and intention delivery amount of each candidate intention information. The splitting module 1004 is used by the matching engine to split the inquiry quantity corresponding to the inquiry information to each candidate intention information according to the weight value of each candidate intention information, so as to obtain the inquiry result of each candidate intention information. The generation module 1005 is used to generate and execute business instructions based on the inquiry results of each candidate intention information and the preset business template.
[0102] Optionally, the intention information includes: intended product information, transaction direction, and intended transaction type; the inquiry information includes: inquiry product information, transaction direction, and inquiry transaction type. Matching module 1002 is used for: Determine whether the intent information includes the identifier of the intended product; If the intention information does not include the intention product identifier, then the intention product information and transaction direction of the intention information are matched with the inquiry product information and transaction direction of the inquiry information to determine at least one candidate intention information corresponding to the inquiry information. If the intention information includes an intention product identifier, then the transaction direction of the intention information is matched with the transaction direction of the inquiry information to determine at least one candidate intention information corresponding to the inquiry information; Matching is performed based on the type of intended transaction and the type of inquiry transaction to determine at least one candidate intended transaction corresponding to the inquiry information.
[0103] Matching module 1002 is used for: Match the inquiry product information and the intended product information to determine at least one initial intention information corresponding to the inquiry information; The initial intention information is filtered according to the transaction direction of the inquiry information, and the initial intention information that is consistent with the transaction direction is used as candidate intention information.
[0104] Optionally, the inquiry information includes: a specified user identifier; Module 1003 is used for: If a specified user identifier exists in the inquiry information, at least one target candidate intention information corresponding to the specified user identifier is determined, and the intention transaction type and inquiry transaction type of the target candidate intention information are matched to determine at least one alternative intention information corresponding to the inquiry information in the target candidate intention information. If no specified user identifier is found in the inquiry information, the system will match the intended transaction type with the inquiry transaction type to determine at least one candidate intended transaction information corresponding to the inquiry information.
[0105] Module 1003 is used for: Obtain the first weight corresponding to the issuance time and the second weight corresponding to the issuance quantity; The weight values of the candidate intention information are determined based on the preset weight model, the first weight, the second weight, the intention delivery time of the candidate intention information, and the intention delivery quantity.
[0106] Module 1003 is used for: Input the first weight, the second weight, the intention delivery time of the candidate intention information, and the intention delivery amount into the weight model to calculate the weight value of the candidate intention information. The weighting model is: score = W1 × TIME + W2 × AMOUNT, where score is the weight value, W1 is the first weight, W2 is the second weight, TIME is the time of intention delivery, and AMOUNT is the amount of intention delivery.
[0107] Split module 1004, used for: The candidate information is sorted according to its weight value to obtain a list of candidate information. Iterate through the list of intent information, starting with the candidate intent information with the highest weight value in the list, and split the inquiry volume to the candidate intent information according to the intended delivery volume of the candidate intent information, until the inquiry volume is equal to zero, and obtain the split inquiry volume of each candidate intent information. Based on the breakdown of the inquiry volume for each candidate intention information, the inquiry results for each candidate intention information are generated.
[0108] Module 1005 is used for: Extract at least one query keyword from the query results; Fill each inquiry keyword into the corresponding position in the business template to obtain and execute the business instructions.
[0109] In this embodiment, the matching engine automatically matches intention information and inquiry information, calculates weight values based on the intention delivery time and quantity of the intention information, and sorts them according to the weight values. This can automate investment transactions, and by optimizing the matching results through multi-dimensional conditions and weight values, the accuracy and efficiency of investment transaction matching can be improved.
[0110] Figure 11 This illustration shows a schematic diagram of the structure of an electronic device provided in an embodiment of this application, including: a processor 1101, a storage medium 1102, and a bus 1103. The storage medium 1102 stores machine-readable instructions executable by the processor 1101. When the electronic device runs a transaction inquiry matching method as described in the embodiment, the processor 1101 communicates with the storage medium 1102 via the bus 1103. The processor 1101 executes the machine-readable instructions. The preamble of the method item of the processor 1101 executes the steps in the above-mentioned transaction inquiry matching method.
[0111] This application also provides a computer-readable storage medium storing a computer program that is executed by a processor, which performs the steps in the above-described transaction inquiry and matching method.
[0112] In this embodiment, the computer program, when run by the processor, can also execute other machine-readable instructions to perform other methods as described in the embodiments. For details on the specific execution steps and principles, please refer to the description of the embodiments, which will not be repeated here.
[0113] In the embodiments provided in this application, it should be understood that the disclosed apparatus and methods can be implemented in other ways. The apparatus embodiments described above are merely illustrative. For example, the division of units is only a logical functional division, and in actual implementation, there may be other division methods. Furthermore, multiple units or components may be combined or integrated into another system, or some features may be ignored or not executed. Additionally, the displayed or discussed mutual couplings, direct couplings, or communication connections may be through some communication interfaces; indirect couplings or communication connections between devices or units may be electrical, mechanical, or other forms.
[0114] The units described as separate components may or may not be physically separate. The components shown as units may or may not be physical units; that is, they may be located in one place or distributed across multiple network units. Some or all of the units can be selected to achieve the purpose of this embodiment according to actual needs.
[0115] In addition, the functional units in the embodiments provided in this application can be integrated into one processing unit, or each unit can exist physically separately, or two or more units can be integrated into one unit.
[0116] If the aforementioned functions are implemented as software functional units and sold or used as independent products, they can be stored in a computer-readable storage medium. Based on this understanding, the technical solution of this application, in essence, or the part that contributes to the prior art, or a portion of the technical solution, can be embodied in the form of a software product. This computer software product is stored in a storage medium and includes several instructions to cause a computer device (which may be a personal computer, server, or network device, etc.) to execute all or part of the steps of the methods described in the various embodiments of this application. The aforementioned storage medium includes various media capable of storing program code, such as USB flash drives, portable hard drives, read-only memory (ROM), random access memory (RAM), magnetic disks, or optical disks.
[0117] It should be noted that similar labels and letters in the following figures indicate similar items. Therefore, once an item is defined in one figure, it does not need to be further defined and explained in subsequent figures. In addition, the terms "first", "second", "third", etc. are used only to distinguish descriptions and should not be construed as indicating or implying relative importance.
[0118] Finally, it should be noted that the above-described embodiments are merely specific implementations of this application, used to illustrate the technical solutions of this application, and not to limit them. The protection scope of this application is not limited thereto. Although this application has been described in detail with reference to the foregoing embodiments, those skilled in the art should understand that any person skilled in the art can still modify or easily conceive of changes to the technical solutions described in the foregoing embodiments, or make equivalent substitutions for some of the technical features, within the scope of the technology disclosed in this application; and these modifications, changes, or substitutions do not cause the essence of the corresponding technical solutions to deviate from the spirit and scope of the technical solutions of the embodiments of this application. All should be covered within the protection scope of this application. Therefore, the protection scope of this application should be determined by the protection scope of the claims.
Claims
1. A transaction inquiry and matching method, characterized in that, Applied to an electronic device in which a matching engine is deployed, the method includes: Obtain a set of intention information from a first user and a set of inquiry information from a second user, wherein the set of intention information includes at least one set of intention information and the set of inquiry information includes at least one set of inquiry information; Run the matching engine, which traverses each inquiry in the inquiry information set, and for the current inquiry, matches the current inquiry with each intention in the intention information set to determine at least one candidate intention corresponding to the current inquiry. The matching engine determines the weight value of each candidate intention information based on the intention delivery time and intention delivery amount of each candidate intention information; The matching engine distributes the inquiry quantity corresponding to each inquiry information to each of the candidate intention information according to the weight value of each candidate intention information, thereby obtaining the inquiry result of each candidate intention information; Based on the inquiry results of each candidate intention information and the preset business template, generate and execute business instructions.
2. The method according to claim 1, characterized in that, The intention information includes: intended product information, transaction direction, and intended transaction type; the inquiry information includes: inquiry product information, transaction direction, and inquiry transaction type. The step of matching the current inquiry with each piece of intent information in the intent information set to determine at least one candidate intent information corresponding to the current inquiry information includes: Determine whether the intent information includes an intent product identifier; If the intention information does not include an intention product identifier, then the intention product information and transaction direction of the intention information are matched with the inquiry product information and transaction direction of the inquiry information to determine at least one candidate intention information corresponding to the inquiry information. If the intention information includes an intention product identifier, then the transaction direction of the intention information is matched with the transaction direction of the inquiry information to determine at least one candidate intention information corresponding to the inquiry information; Matching the intended transaction type and the inquiry transaction type to determine at least one candidate intended transaction information corresponding to the inquiry information.
3. The method according to claim 2, characterized in that, The step of matching the intended product information and transaction direction of the intended information with the inquiry product information and transaction direction of the inquiry information to determine at least one candidate intended information corresponding to the inquiry information includes: Based on the inquiry product information and the intended product information, at least one initial intention information corresponding to the inquiry information is determined; The initial intention information is filtered according to the transaction direction of the inquiry information, and the initial intention information that is consistent with the transaction direction is selected as candidate intention information.
4. The method according to claim 2, characterized in that, The inquiry information includes: a specified user identifier; The step of matching the intended transaction type and the inquiry transaction type to determine at least one candidate intended transaction information corresponding to the inquiry information includes: If a specified user identifier exists in the inquiry information, at least one target candidate intention information corresponding to the specified user identifier is determined, and the intention transaction type of the target candidate intention information and the inquiry transaction type are matched to determine at least one alternative intention information corresponding to the inquiry information in the target candidate intention information. If the inquiry information does not contain a specified user identifier, then the at least one candidate intention information corresponding to the inquiry information is determined by matching the intended transaction type and the inquiry transaction type.
5. The method according to claim 1, characterized in that, The step of determining the weight value of each candidate intention information based on the intention delivery time and intention delivery amount includes: Obtain the first weight corresponding to the issuance time and the second weight corresponding to the issuance quantity; The weight value of the candidate intention information is determined based on the preset weight model, the first weight, the second weight, the intention delivery time of the candidate intention information, and the intention delivery amount.
6. The method according to claim 5, characterized in that, The step of determining the weight value of the candidate intention information based on a preset weight model, the first weight, the second weight, the intention delivery time of the candidate intention information, and the intention delivery quantity includes: The first weight, the second weight, the intention delivery time and intention delivery amount of the candidate intention information are input into the weight model to calculate the weight value of the candidate intention information. The weighting model is: score = W1 × TIME + W2 × AMOUNT, where score is the weight value, W1 is the first weight, W2 is the second weight, TIME is the intention delivery time, and AMOUNT is the intention delivery amount.
7. The method according to claim 1, characterized in that, The step of allocating the inquiry quantity corresponding to each inquiry information to each of the candidate intention information according to the weight value of each candidate intention information, and obtaining the inquiry result of each candidate intention information, includes: The candidate intention information is sorted according to the weight value of each candidate intention information to obtain a list of intention information; Traverse the list of intent information, starting from the candidate intent information with the largest weight value in the list of intent information, and split the inquiry quantity to the candidate intent information according to the intention delivery quantity of the candidate intent information, until the inquiry quantity is equal to zero, to obtain the split inquiry quantity of each candidate intent information. Based on the breakdown of the inquiry volume for each candidate intention information, the inquiry results for each candidate intention information are generated.
8. The method according to claim 1, characterized in that, The process of generating and executing business instructions based on the inquiry results of each candidate intention information and a preset business template includes: At least one query keyword is extracted from the query results; Fill the corresponding positions of the inquiry keywords into the business template to obtain and execute the business instructions.
9. An electronic device, characterized in that, include: The device includes a processor, a storage medium, and a bus, wherein the storage medium stores machine-readable instructions executable by the processor, and when the electronic device is running, the processor communicates with the storage medium via the bus, and the processor executes the machine-readable instructions to perform the steps of the transaction quote matching method as described in any one of claims 1 to 8.
10. A computer-readable storage medium, characterized in that, The computer-readable storage medium stores a computer program that, when executed by a processor, performs the steps of the transaction inquiry matching method as described in any one of claims 1 to 8.