Digital asset auction method and device, nonvolatile storage medium and electronic equipment

Abstract

The invention discloses a digital asset auction method and device, a nonvolatile storage medium and electronic equipment. The method comprises the steps that value vectors of digital assets are determined according to a preset asset evaluation item, and the value vectors of different types of digital assets are the same in dimension; clustering the digital assets according to the value vectors of the digital assets to obtain a plurality of digital asset groups; determining an auction demand of the target auction scene, and selecting digital assets from the digital asset group according to the auction demand to form a target digital asset auction packet; and auctioning the target digital asset auction package through the block chain. The technical problem that the auction efficiency is low due to the fact that the heterogeneous digital assets cannot be combined for auction after being packaged in the prior art is solved.

Description

TECHNICAL FIELD

[0001] The present application relates to the field of blockchains, and in particular, to a digital asset auction method and device, a nonvolatile storage medium, and an electronic device. BACKGROUND

[0002] In related technologies, different types of heterogeneous assets cannot be packaged and combined for auction when auctioning digital assets through a blockchain, resulting in low efficiency of blockchain digital asset auctions in related technologies.

[0003] To address the above problems, no effective solutions have been proposed so far. SUMMARY

[0004] Embodiments of the present application provide a digital asset auction method, device, nonvolatile storage medium, and electronic device to at least solve the technical problem of low auction efficiency due to the inability to package and combine heterogeneous digital assets for auction in related technologies.

[0005] According to an aspect of an embodiment of the present application, a digital asset auction method is provided, including: determining a value vector of a digital asset according to a preset asset evaluation item, wherein the value vectors of different types of digital assets have the same dimension; clustering the digital assets according to the value vector of the digital asset to obtain a plurality of digital asset groups; determining an auction requirement of a target auction scene, and selecting digital assets from the digital asset groups to form a target digital asset auction package according to the auction requirement; and auctioning the target digital asset auction package through a blockchain.

[0006] Optionally, selecting digital assets from the digital asset groups to form a target digital asset auction package according to the auction requirement includes: determining an auction requirement vector according to the auction requirement, wherein the dimension of the auction requirement vector is the same as the dimension of the value vector; determining candidate digital assets in the digital asset groups according to the auction requirement vector, wherein the similarity between the value vector of the candidate digital assets and the auction requirement vector is greater than a preset similarity threshold; and selecting the candidate digital assets to form the target digital asset auction package.

[0007] Optionally, selecting the candidate digital assets to form the target digital asset auction package comprises: determining a plurality of candidate digital asset auction packages, wherein the candidate digital assets in the candidate digital asset auction package come from the same digital asset group; determining an auction package evaluation value of the candidate digital asset auction package, and determining a target candidate digital asset auction package according to the auction package evaluation value, wherein the auction package evaluation value is used to reflect the estimated auction revenue of the candidate digital asset auction package, the higher the auction package evaluation value, the higher the estimated auction revenue, and the target candidate digital asset auction package is the candidate digital asset auction package with the highest auction package evaluation value in the plurality of candidate digital asset auction packages; updating the target candidate digital asset auction package according to the candidate digital assets not in the target candidate digital asset auction package to obtain the target digital asset auction package, wherein the auction package evaluation value of the target digital asset auction package is not lower than the auction package evaluation value of the target candidate digital asset auction package.

[0008] Optionally, updating the target candidate digital asset auction package according to the candidate digital assets not in the target candidate digital asset auction package comprises: traversing the candidate digital assets not in the target candidate digital asset auction package, and determining whether the auction package evaluation value of the target candidate digital asset auction package increases after the candidate digital assets traversed are used to replace the digital assets in the target candidate digital asset auction package; in the case where it is determined that the auction package evaluation value increases, using the candidate digital assets traversed to replace the digital assets in the target candidate digital asset auction package.

[0009] Optionally, determining a plurality of candidate digital asset auction packages comprises: determining whether there are digital assets with right conflicts in the candidate digital asset auction package; and deleting the candidate digital asset auction package with the digital assets with right conflicts.

[0010] Optionally, auctioning the target digital asset auction package through the blockchain comprises: determining an auction object expected to be purchased by the bidder, wherein the auction object comprises the digital assets in the target digital asset auction package and the right type of the digital assets; and for the auction object with right conflicts, determining the bidder who successfully bids according to the bid price of the bidder.

[0011] Optionally, auctioning the target digital asset auction package through the blockchain comprises: receiving a first bid price sent by the bidder; determining historical auction behavior information of the bidder; adjusting the first bid price according to the historical auction behavior information to obtain a second bid price, and taking the second bid price as the bid price of the bidder.

[0012] According to another aspect of the embodiments of the present application, a digital asset auction device is also provided, including: a first processing module configured to determine a value vector of a digital asset according to a preset asset evaluation item, wherein the value vectors of different types of digital assets have the same dimension; a second processing module configured to cluster the digital assets according to the value vector of the digital asset to obtain a plurality of digital asset groups; a third processing module configured to determine an auction demand of a target auction scene, and select digital assets from the digital asset groups to form a target digital asset auction package according to the auction demand; and a fourth processing module configured to auction the target digital asset auction package through a blockchain.

[0013] According to another aspect of the embodiments of the present application, a non-volatile storage medium is also provided, which stores a program, wherein the program controls a device in which the non-volatile storage medium is located to perform the digital asset auction method when the program is running.

[0014] According to another aspect of the embodiments of the present application, an electronic device is also provided, including a memory and a processor, wherein the processor is configured to run a program stored in the memory, and the program performs the digital asset auction method when the program is running.

[0015] According to another aspect of the embodiments of the present application, a computer program product is also provided, including a computer program, which implements the digital asset auction method when executed by a processor.

[0016] In the embodiments of the present application, the value vector of the digital asset is determined according to the preset asset evaluation item, wherein the value vectors of different types of digital assets have the same dimension; the digital assets are clustered according to the value vector of the digital asset to obtain a plurality of digital asset groups; the auction demand of the target auction scene is determined, and the digital assets are selected from the digital asset groups to form the target digital asset auction package according to the auction demand; and the target digital asset auction package is auctioned through the blockchain, thereby realizing the unified evaluation of different types of digital assets by determining the value vector of the digital asset, achieving the purpose of combining and auctioning the different types of digital assets, and realizing the technical effect of improving the digital asset auction efficiency, thereby solving the technical problem of low auction efficiency caused by the inability to combine and auction the packaged heterogeneous digital assets in the related art. BRIEF DESCRIPTION OF DRAWINGS

[0017] The accompanying drawings, which are included to provide a further understanding of the present application, form a part of the present application and illustrate the illustrative embodiments of the present application and the explanation of the present application, and do not constitute improper limitations on the present application. In the drawings:

[0018] Figure 1 is a structural schematic diagram of a computer terminal (and a mobile device) provided according to the embodiments of the present application;

[0019] Figure 2 is a flowchart of a digital asset auction method according to an embodiment of the present application;

[0020] Figure 3 is a flowchart of a digital asset auction process according to an embodiment of the present application;

[0021] Figure 4 is a flowchart of an auction result clearing process according to an embodiment of the present application;

[0022] Figure 5 is a structural diagram of a digital asset auction system according to an embodiment of the present application;

[0023] Figure 6 is a structural diagram of a digital asset auction device according to an embodiment of the present application. DETAILED DESCRIPTION

[0024] In order to enable those skilled in the art to better understand the present application, the technical solutions in the embodiments of the present application will be described clearly and completely below with reference to the drawings in the embodiments of the present application. Obviously, the described embodiments are only a part of the embodiments of the present application, not all the embodiments. Based on the embodiments in the present application, all other embodiments obtained by those skilled in the art without creative labor should be within the scope of protection of the present application.

[0025] It should be noted that the terms "first", "second", and the like in the specification and claims of the present application and the above-described drawings are used to distinguish similar objects, and do not necessarily have to describe a specific order or sequence. It should be understood that the data thus used can be interchanged under appropriate circumstances, so that the embodiments of the present application described herein can be implemented in an order other than those illustrated or described herein. In addition, the terms "include" and "have" and any variations thereof are intended to cover non-exclusive inclusion, for example, a process, method, system, product or device that includes a series of steps or units does not have to be limited to those steps or units clearly listed, but can include other steps or units that are not clearly listed or inherent to these processes, methods, products or devices.

[0026] At present, with the development of emerging digital assets such as blockchain, NFT (non-fungible token), digital copyright, AI model assets, etc., the digital asset trading platforms in related technologies such as OpenSea, Blur, SuperRare, etc. mostly use single asset auction or fixed price sale mode, which is difficult to adapt to the increasingly complex digital asset forms and user collaborative purchase needs.

[0027] And in the related art, heterogeneous digital assets cannot be combined for auction, and digital assets cannot be split or dynamically allocated, resulting in users obtaining rights in terms of "usage rights" and "commercial authorization" and other fine-grained dimensions.

[0028] There is also a problem of lack of multi-bidder collaboration mechanism in the related art. High-value assets are difficult for ordinary users to jointly bid for, and there is a lack of joint bidding contract support. And there is a lack of anti-cheating and reputation mechanism, there are risks such as "fake account string tags" and "maliciously raising bids", and there is a lack of effective prevention and control. Moreover, the transaction lifecycle is missing, and after the auction ends, the platform cannot control the reasonable transfer of assets, resulting in a large amount of expired resources being wasted.

[0029] Therefore, there is an urgent need for a novel joint auction and dynamic allocation mechanism that can support asset heterogeneity, fine-grained rights trading, on-chain collaboration, and anti-cheating mechanisms.

[0030] To solve the above problems, the related solutions are provided in the embodiments of the present application, which are described in detail below.

[0031] According to the embodiments of the present application, a method embodiment of a digital asset auction method is provided. It should be noted that the steps shown in the flowchart of the accompanying drawings can be executed in a computer system such as a set of computer executable instructions, and although a logical order is shown in the flowchart, in some cases, the steps shown or described herein can be executed in a different order.

[0032] The method embodiment provided by the embodiments of the present application can be executed in a mobile terminal, a computer terminal or a similar computing device. Figure 1 A hardware structure block diagram of a computer terminal (or mobile device) for implementing a digital asset auction method is shown. As Figure 1 shown, the computer terminal 10 (or mobile device 10) can include one or more processors 102 (the processor 102 can include but is not limited to a microprocessor MCU or a programmable logic device FPGA processing device), a memory 104 for storing data, and a transmission device 106 for communication functions. In addition, it can also include a display, an input / output interface (I / O interface), a universal serial bus (USB) port (which can be included as one of the ports of the BUS bus), a network interface, a power supply and / or a camera. Those skilled in the art can understand that Figure 1 The structure shown is only schematic, which does not limit the structure of the above-mentioned electronic device. For example, the computer terminal 10 can also include more or fewer components than those shown in Figure 1 or have a different configuration than Figure 1 shown.

[0033] It should be noted that the one or more processors 102 and / or other data processing circuitry described above can be referred to herein generally as "data processing circuitry". The data processing circuitry can be embodied in whole or in part as software, hardware, firmware, or any combination thereof. In addition, the data processing circuitry can be a single standalone processing module, or incorporated in whole or in part within any of the other elements of the computer terminal 10 (or mobile device 10). As referred to in embodiments of the present application, the data processing circuitry functions as a processor to control, for example, selection of variable resistance terminal paths connected to the interface.

[0034] The memory 104 can be used to store software programs of application software and modules, such as program instructions / data storage means corresponding to the digital asset auction method in embodiments of the present application. The processor 102 executes various functional applications and data processing by running the software programs and modules stored in the memory 104, i.e. implements the digital asset auction method described above. The memory 104 can include a high-speed random access memory, and can also include a non-volatile memory, such as one or more magnetic storage devices, flash memory, or other non-volatile solid-state memory. In some examples, the memory 104 can further include a memory disposed remotely with respect to the processor 102, which can be connected to the computer terminal 10 (or mobile device 10) through a network. Examples of the network include, but are not limited to, the Internet, an intranet, a local area network, a mobile communication network, and combinations thereof.

[0035] The transmission device 106 is used to receive or send data via a network. Specific examples of the network can include a wireless network provided by a communication provider of the computer terminal 10. In one example, the transmission device 106 includes a network adapter (NIC), which can be connected to other network devices through a base station so as to communicate with the Internet. In one example, the transmission device 106 can be a radio frequency (RF) module, which is used to communicate with the Internet in a wireless manner.

[0036] The display can be, for example, a touch screen type liquid crystal display (LCD), which can enable a user to interact with the user interface of the computer terminal 10 (or mobile device 10).

[0037] Under the above operating environment, embodiments of the present application provide a digital asset auction method, as shown in Figure 2 The method includes the following steps:

[0038] In step S202, a value vector of the digital asset is determined according to a preset asset evaluation item, wherein the value vectors of different types of digital assets have the same dimension. In step S204, a value vector of the digital asset is determined according to a preset asset evaluation item, wherein the value vectors of different types of digital assets have the same dimension.

[0039] Need to note that heterogeneous assets cannot be directly compared, such as:

[0040] The value of a copyrighted music is embodied in "number of plays x authorized fee";

[0041] The value of an AI model is embodied in "number of calls x inference accuracy";

[0042] An NFT artwork may be embodied in "rarity x collection heat".

[0043] In the technical solution provided in step S202, the value vector of the digital asset is determined to realize the value anchoring and normalization of the digital asset. These differentiated indicators are compressed into a unified vector space, for example:

[0044] Asset A (AI model): [0.8, 0.6, 0.9], Asset B (copyright music): [0.7, 0.9, 0.4], Asset C (NFT art): [0.6, 0.5, 0.95].

[0045] In this way, different types of heterogeneous digital assets are converted into value vectors with the same dimensions, and their "similarity" and "value size" can be calculated in the same coordinate system, thereby realizing the combination auction of heterogeneous digital assets.

[0046] In some embodiments of the present application, each dimension of the value vector can correspond to a preset asset evaluation item. In order to determine the value vector of the digital asset, the relevant information of each preset asset evaluation item of the digital asset can be obtained. The preset asset evaluation item can include on-chain transaction data, off-chain heat index, and asset attribute index, etc. The on-chain transaction data can include historical transaction price, transaction frequency, number of failed auctions, etc. The off-chain heat index can include search volume, social media mentions, download volume, rating, etc. The asset attribute index can include rarity (whether unique), functional integrity (whether independent or dependent on other resources), copyright status.

[0047] The relevant information of the digital asset in the preset asset evaluation item can be mapped to a value in the preset value interval by the evaluation model, and the preset value interval can be [0, 1] or other intervals. In this way, indicators with different dimensions and different units of measurement can be mapped to a unified value vector space. For example, the "number of plays" of a copyrighted music is mapped to a heat score between 0 and 1, and the "inference performance" of an AI model is mapped to a standardized function score. The structure of the evaluation model is not limited in the present application.

[0048] In some embodiments of the present application, a machine learning regression model (such as XGBoost, random forest) can also be combined to predict the potential market value of a digital asset, so that new assets or assets without transaction history can be valued.

[0049] In some embodiments of the present application, the value vector corresponding to the digital asset can be a feature vector: [value anchor, usage scenario encoding, function type, validity period length, right type encoding, demand heat]. The usage scenarios include education scenarios, entertainment scenarios, commercial scenarios, etc., and can use one-hot encoding. The function type can include computing, storage, and vision, etc. The right type can include ownership, usage right, and profit sharing right, etc. And the function type and right type can also use one-hot encoding.

[0050] In some embodiments of the present application, the value anchor of different digital assets can also be calculated using the following multi-factor weight formula, and the benchmark valuation of the digital asset can be determined: asset value anchor = a x historical transaction price index + b x heat score + g x function scarcity + d x quality coefficient (a, b, g, d can be dynamically adjusted according to market and strategy).

[0051] In some embodiments of the present application, for various non-standard heterogeneous assets, a hash + storage proof method can be used to generate a unique ID of the digital asset, and register its corresponding meta-asset contract model file / audio / video file on the chain. And a permission control mechanism (such as DRM or zk access control) can be introduced, and the buy side can perform the following operations through the auction after obtaining the resource: one-time download, authorized use by period, re-authorization to third parties, etc.

[0052] In addition, for copyright assets, a chain-based permission verification mechanism (such as ERC-5484, ERC-5192, etc.) can be used to ensure that the buyer obtains the right to "use but not copy", "use within a certain time limit", or "release within a certain region" after bidding. And each bidder needs to have a DID (decentralized identity). If the bidder needs to obtain copyright resources, he must verify the "compliant identity" on the chain, and sign the copyright contract terms on the chain (to prevent plagiarism / secondary dissemination, etc.).

[0053] Step S204, clustering the digital assets according to the value vector of the digital assets to obtain a plurality of digital asset groups;

[0054] As an optional implementation, when clustering the digital assets, the Euclidean distance or cosine similarity between different digital assets can be calculated by using the value vectors of the different digital assets, so as to cluster the different digital assets according to the Euclidean distance or cosine similarity, and obtain a plurality of digital asset groups. The average value center of the digital asset group can be determined according to the value vectors of the digital assets in the digital asset group.

[0055] In some embodiments of the present application, the correlation of different digital assets can also be adjusted according to the auction situation of different digital assets. The specific adjustment manner can be to determine a weight coefficient for the Euclidean distance or cosine similarity between different digital assets, and determine the result obtained by multiplying the original Euclidean distance or cosine similarity by the weight coefficient as the adjusted Euclidean distance or adjusted cosine similarity. For example, if a group of digital assets are often purchased separately by buyers, their correlation is reduced, that is, a larger weight coefficient (which can be greater than 1) is assigned, and if digital assets of different groups are often bundled and purchased by the same buyer in the auction, their similarity is increased in the next round of clustering, that is, a smaller weight coefficient (which can be less than 1) is assigned.

[0056] When clustering the digital assets, K-Means or spectral clustering (Spectral Clustering) clustering method can be used, or for assets with graph relationship (such as two assets are often purchased together), graph-based community discovery algorithm (Louvain or Label Propagation) can also be used.

[0057] Step S206, determining the auction demand of the target auction scene, and selecting digital assets from the digital asset groups to form a target digital asset auction package according to the auction demand;

[0058] In some embodiments of the present application, the overall value maximization and complementarity between assets need to be considered when determining the target digital asset auction package. The following formula can be used to measure the value of the digital asset package:

[0059] Package value = Σ (asset value vector of each digital asset in the package x weight) - conflict penalty term

[0060] The above weight can be determined according to the historical transaction records of the digital assets. For example, a larger weight can be assigned to a digital asset with a higher historical transaction success rate or a higher average transaction price. A lower weight can be assigned to a digital asset with a lower historical transaction success rate or a lower average transaction price.

[0061] The conflict penalty term refers to a penalty value of a bundle value determined according to the value of the conflicting objects in the case where it is determined that there are two mutually conflicting auction objects in the digital asset bundle. The auction object is composed of a digital asset and an auction right type corresponding to the digital asset. The conflict penalty refers to the fact that two or more auction objects cannot be successfully auctioned at the same time. For example, the use right of a digital asset within a period of time and the long-term exclusive use right of the exclusive use right. The value of the conflict penalty term can be determined according to the average value of the auction objects with conflict penalty. When there are multiple groups of mutually interfering conflicting auction objects, the sum of the average values of the values corresponding to each group of conflicting auction objects can be determined as the value of the conflict penalty term.

[0062] In addition, in order to avoid the influence of the conflict penalty term, it can be stipulated as a rule to be followed when generating a digital asset bundle that there cannot be auction right conflicts between different auction objects in the digital asset auction bundle.

[0063] In some embodiments of the present application, the step of selecting digital assets from the digital asset group to form the target digital asset auction bundle according to the auction demand includes: determining an auction demand vector according to the auction demand, wherein the dimension of the auction demand vector is the same as the dimension of the value vector; determining a candidate digital asset in the digital asset group according to the auction demand vector, wherein the similarity between the value vector of the candidate digital asset and the auction demand vector is greater than a preset similarity threshold; and selecting the candidate digital asset to form the target digital asset auction bundle.

[0064] In some embodiments of the present application, the candidate digital assets in the target digital asset auction bundle do not necessarily come from the same candidate asset group. The candidate digital assets can be preferentially selected from the same candidate group to form the target digital asset auction bundle (because the semantic / usage scenario / value vector similarity of the assets in the group is high, the synergistic effect within the combination is strong, and the user understanding cost is low). However, when the cross-group combination is obviously superior to the single-group combination in terms of “synergistic value / expected return / potential for circulation”, a hybrid auction bundle across candidate groups can be constructed as the target digital asset auction bundle.

[0065] As an optional implementation, the step of selecting the candidate digital assets to form the target digital asset auction package comprises: determining a plurality of candidate digital asset auction packages, wherein the candidate digital assets in the candidate digital asset auction package come from the same digital asset group; determining an auction package evaluation value of the candidate digital asset auction package, and determining a target candidate digital asset auction package according to the auction package evaluation value, wherein the auction package evaluation value is used to reflect the estimated auction income of the candidate digital asset auction package, the higher the auction package evaluation value, the higher the estimated auction income, and the target candidate digital asset auction package is the candidate digital asset auction package with the highest auction package evaluation value in the plurality of candidate digital asset auction packages; updating the target candidate digital asset auction package according to the candidate digital assets not in the target candidate digital asset auction package to obtain the target digital asset auction package, wherein the auction package evaluation value of the target digital asset auction package is not lower than the auction package evaluation value of the target candidate digital asset auction package.

[0066] In some embodiments of the present application, the step of updating the target candidate digital asset auction package according to the candidate digital assets not in the target candidate digital asset auction package comprises: traversing the candidate digital assets not in the target candidate digital asset auction package, and determining whether the auction package evaluation value of the target candidate digital asset auction package increases after the candidate digital assets traversed replace the digital assets in the target candidate digital asset auction package; in the case of determining that the auction package evaluation value increases, the candidate digital assets traversed replace the digital assets in the target candidate digital asset auction package.

[0067] As an optional implementation, the step of determining a plurality of candidate digital asset auction packages comprises: determining whether there are digital assets with right conflicts in the candidate digital asset auction package; and deleting the candidate digital asset auction package with the digital assets with right conflicts.

[0068] In some embodiments of the present application, the target digital asset auction package can be determined in the following way:

[0069] First, define the scenario and demand vector (Scenario Profile).

[0070] Each target auction scenario (for example, commercial audio authorization, voice synthesis service, cross-media marketing package) defines a scenario vector S, and the dimension is consistent with the asset value vector: S = [s1, s2,..., sn] (for example, preference function, regional restriction, authorization period, audience size, etc. Weight) The scenario can be generated by the seller / platform / history auction data (also can let the initiator fill in the target purpose label).

[0071] Second, calculate the match score of the candidate digital asset to the scenario.

[0072] The cosine similarity or normalized dot product between the value vector of a candidate digital asset and the auction demand vector of the target auction scenario can be used as the degree of fit of the candidate digital asset to the target auction scenario. The calculation formula is: match_i = cosine(V_i,S) or match_i = V_i·S (match_i->[0,1], which indicates the degree of fit of the asset to the scenario).

[0073] The third step is constraint filtering (hard constraints).

[0074] Before entering a combined search, a non-violation-compliant filter is applied, including checks for rights conflicts, time / regional conflicts, compliance, and identity requirements. Rights conflict checks include: if two assets contain mutually exclusive rights (e.g., an exclusive commercial right to the same work and a non-exclusive commercial right to another), they are prohibited from entering the same package simultaneously. Time / regional conflicts include: conflicts involving non-overlapping licensing periods / regions must be eliminated or adjusted. Compliance and identity requirements include: assets requiring specific compliant DIDs or qualifications exclude buyers who do not meet the criteria. These rules can be enforced off-chain or on-chain by a "contract generator + permission verification module".

[0075] The fourth step is to determine the evaluation function (combined scoring function) for the digital asset auction package.

[0076] Optionally, an auction package evaluation value U(B) can be calculated for each candidate digital asset auction package B. As an optimization objective, the formula for calculating the auction package evaluation value U(B) can be:

[0077] U(B)=X1*∑(i∈B)(match_i*value_i)+λX2*synergy(B)-λX3*conflict_penalty(B)+λX4*liquidity_score(B)

[0078] In the above formula, value_i represents the baseline value of the asset (from a certain dimension of the value vector or the output of the predictive model). match_i represents the matching degree of the scenario. synergy(B) represents the portfolio synergy gain, which is a reward given if the historical correlation / complementarity between assets is strong, that is, to increase U(B). conflict_penalty(B) represents the penalty given if there is marginal / potential conflict in the portfolio. liquidity_score(B) represents the subsequent circulation potential of the digital assets in the package (historical resale rate / attention). X1 to X4 and λ are adjustable hyperparameters that can be dynamically adjusted based on platform strategy / risk preference.

[0079] In some embodiments of this application, the synergistic combination gain can be calculated based on co-purchase frequency or graph similarity using the following formula:

[0080] synergy(B) = ∑((i,j)∈B) W(i,j), where W(i,j) is the weight from the history of co-purchase / co-browsing / complementary tags. Also, if the digital asset portfolio covers complementary functions, the value of synergy(B) can be further adjusted.

[0081] Step 5, portfolio search and optimization.

[0082] As an optional implementation, the portfolio optimization (NP-hard) process can be implemented with the following strategies:

[0083] Hierarchical candidate strategy (preferred): find top-K (by match_i*value_i) candidates in each digital asset portfolio first, generate the intra-portfolio candidate set (i.e., candidate digital asset auction package), so as to reduce the search space. Then calculate the U(B) of the candidate digital asset auction package combined by these "intra-portfolio first" strategy.

[0084] Heuristic / greedy + local search: for the target candidate digital asset package with the highest U(B), start from the highest match_i*value_i asset outside the package, traverse these outside candidates in the order of descending match_i*value_i, and replace the corresponding digital asset in the package with the traversed digital asset if the replacement can improve the overall U(B) of the package.

[0085] In some embodiments of the present application, an integer linear programming 0-1 knapsack variant can be used, where x1∈{0,1} represents whether the asset is in the package or not, and the goal is to maximize U(B). In addition, in the process of traversal, the weight conflict can be converted into a linear constraint. Suitable for scenarios with strict upper limit, budget or weight type constraints on in-package assets.

[0086] Step 6, multi-objective and auction format adaptation.

[0087] If the target candidate digital asset package is expected to have both "maximum revenue" and "high transaction probability", a transaction probability prediction evaluation item can be introduced into the scoring.

[0088] In addition, it should be noted that different auction methods will affect the optimization target, for example, Dutch auction values quick transaction more, English auction values highest premium more, so the adjustable hyperparameters can be adjusted according to the auction method.

[0089] Step 6, post-processing and contract

[0090] After the target digital asset auction package is determined, the Bundle-NFT metadata can be generated to explicitly specify the right split, validity period, re-authorization rules, and profit distribution path (clearing graph) of each digital asset in the package, and the corresponding smart contract is deployed / cast. The conflict resolution strategy and the reflux mechanism (expiration recycling) are written in the contract to ensure automatic execution after the auction.

[0091] In some embodiments of the present application, assuming that the scenario vector emphasizes "audio library coverage, license type (commercial), regional authorization, and time length". The top-20 can be selected from the "audio library candidate group", while considering the top-10 of the "AI voice model group". The match*value of each digital asset is calculated, and the asset auction package is searched. For example, if it is found that the cross-group combination of "audio library A + model M + commercial license C" brings 30% synergy than any single-group combination, and there is no right conflict, the cross-group combination can be taken as the target digital asset auction package, and the Bundle is generated and enters the joint auction pool.

[0092] In some embodiments of the present application, the following function can also be used to evaluate the digital asset package:

[0093] Score(B)=V(B)×P(B)×L(B)

[0094] Where V(B) is the normalized predicted auction price of the digital asset package, P(B) is the normalized predicted auction success probability, and L(B) represents the normalized evaluation result of the subsequent flow potential of the digital asset. The predicted auction success rate can be the normalized calculation result of the average predicted auction success rate of each auction object or digital asset in the package, or the overall rate of the digital asset package. L(B) can be the normalized calculation result of the average subsequent flow potential of each digital asset in the package.

[0095] In some embodiments of the present application, the predicted auction price of the digital asset package can be determined according to the sum of the benchmark values of each digital asset in the package, the average matching degree between different assets, the synergy, the auction reserve price / reserve price, the historical transaction price of similar packages, and the expected exposure. Information such as amount. And the overall bid rate of the package digital asset package can be determined according to the predicted number of participants in the auction, the exposure, the difference between the predicted price and the reserve price, the auction mode, the historical transaction rate of similar packages, etc.

[0096] In addition, when determining the flow potential of the digital asset, the flow potential evaluation result of the digital asset can be determined according to the reselling rate of similar assets, the historical reselling multiple, the secondary length and depth (such as the number of buyers / number of orders), whether the asset allows re-authorization, compatibility score, etc.

[0097] Step S208, auctioning the target digital asset auction package through the blockchain.

[0098] In some embodiments of the present application, after obtaining the target digital asset auction package, a contract containing all resources can be automatically generated by the digital asset auction system according to the use purpose, bidding form and other information of the target digital asset package. The contract can define the following contents: delivery logic of all assets, clear separation of ownership and use right of digital assets; benefit distribution logic (such as secondary distribution of copyright digital assets after transaction).

[0099] In some embodiments of the present application, the step of auctioning the target digital asset auction package through the blockchain includes: determining an auction object expected to be purchased by a bidder, wherein the auction object includes a digital asset in the target digital asset auction package and a right type of the digital asset; and for an auction object with a right conflict, determining a bidder who successfully bids according to a bidding price of the bidder.

[0100] As an optional implementation, the step of auctioning the target digital asset auction package through the blockchain includes: receiving a first bidding price sent by a bidder; determining historical auction behavior information of the bidder; adjusting the first bidding price according to the historical auction behavior information to obtain a second bidding price, and taking the second bidding price as the bidding price of the bidder.

[0101] In some embodiments of the present application, a digital asset auction process as shown in Figure 3 includes the following steps:

[0102] Step S302, heterogeneous asset collection and normalized modeling.

[0103] Optionally, a user (asset initiator) can submit multiple types of heterogeneous digital assets, such as NFT, AI model files, copyright certificates, etc., to form an initial asset set; the system calls the "heterogeneous asset value anchoring module", based on historical transaction data on the chain, market heat indicators (such as page views, collections) and a preset evaluation algorithm, to perform normalized processing on different forms of assets, eliminate value dimension differences, and calculate a unified asset value anchor to provide a benchmark for subsequent packaging and pricing.

[0104] Step S304, asset fragmentation cutting and right demarcation.

[0105] Optionally, the digital asset auction system can perform "fragmentation cutting" on the normalized assets according to the use of the assets (such as commercial use, non-commercial use), time period (such as 1 month authorization, 1 year authorization), function authority (such as calling right, modification right) and other dimensions; at the same time, fine-grained rights are marked for each asset fragment, such as "commercial communication right" of NFT, "API calling right" of AI model, "limited regional use right" of copyright file, etc., so that users can select specific right fragments according to their needs to participate in the auction.

[0106] Step S306, joint auction pool construction and bottom price dynamic setting.

[0107] Optionally, the system merges and packages the asset fragments or complete assets with marked rights according to the scene relevance (such as "film copyright + music NFT"), generates joint auction objects, and enters the joint auction pool; the platform opens a user intention bidding channel, and users can submit their expected bid range for the auction object; the system dynamically calculates and sets the auction bottom price according to the number of users participating in the intention and the intention bid distribution, to avoid too high or too low bottom price leading to flow or loss of income.

[0108] Step S308, user participation in auction (single / multiple bidding).

[0109] Optionally, users access the system through browsers, DApps or mobile applications, select target auction objects: if it is single bidding, directly submit the bid amount, and the system records and updates the bid ranking in real time; if it is multiple joint bidding, users can initiate or join a joint bidding body, and the system automatically generates a "right cooperation smart contract" to clearly define the contribution ratio of joint bidding body members, the subsequent right allocation ratio (such as use right, profit right) and exit mechanism; the contract content is written into the blockchain to ensure that it cannot be tampered with, and the joint bidding body participates in the auction as a whole.

[0110] Step S310, bid weight adjustment based on reputation and anti-cheating management.

[0111] Optionally, the system can calculate the real-time reputation score of each bidding user according to the user's historical on-chain transaction behavior (such as whether to perform, whether to have malicious bidding records), other user feedback evaluation, asset use effect data (such as AI model calling success rate); the reputation score is mapped to the bid weight adjustment factor, and under the same bid amount, the bid weight of high-reputation users is higher, and they have priority in bidding; at the same time, the bid of low-reputation users is strictly monitored, and if behaviors such as "fake account string bidding" and "malicious bid raising" are detected, the bid weight of the user is automatically reduced or the bidding permission is limited.

[0112] Step S312, confirmation of auction result and on-chain record.

[0113] Optionally, after the end of the auction period, the system determines the highest weight bidder (single or joint bidder) as the winning bidder; the auction results (winning bidder information, final transaction price, right scope), joint bidder's right allocation scheme, and other key information are written into the blockchain through the "data record contract", realizing traceability of the auction process and non-tamperability of the results; at the same time, the auction results are pushed to the winning bidder and the non-winning bidder, and the non-winning bidder can choose to participate in other auctions or wait for asset reflux.

[0114] Step S314, right delivery and intelligent clearing after winning the bid.

[0115] Optionally, after the system triggers the "intelligent clearing contract", the winning bidder completes the payment of funds at the final transaction price, and the payment record is synchronized to the chain; the contract automatically performs right delivery, grants the winning bidder the asset fragment rights (such as opening the AI model API calling permission, issuing the copyright authorization certificate), and clearly defines the effective period of right use; if it is a joint winning bid, the contract automatically splits the asset use right, governance right (such as asset resale decision voting right), and resale income distribution right according to the preset proportion and distributes them to the member accounts of the joint bidder.

[0116] Step S316, asset right life cycle management and reflux.

[0117] Optionally, the system can monitor the asset rights in real time according to the effective period of right use agreed upon at the time of winning the bid; when the rights expire, the "life cycle reflux contract" is automatically triggered to recover the expired asset rights (such as closing the API calling permission and recovering the copyright authorization); the recovered assets can be re-entered into the joint auction pool after re-evaluation and right valuation, and enter the next round of auction circulation, avoiding the sinking of expired assets and improving asset circulation efficiency.

[0118] In some embodiments of the present application, an auction result clearing process as shown in Figure 4 is also provided. As shown in Figure 4 , the process includes the following steps:

[0119] Step S402, structured analysis of auction results.

[0120] Optionally, the bid records of each participating user / joint bidder, the final auction results (winning bidder information, transaction price), and the right allocation ratio can be received. The received data is structured and processed to extract key information (such as the rights that the winning bidder should obtain and the allocation ratio of joint members), and a "resource-right statement" for clearing is generated to ensure that the data format is adapted to the subsequent clearing link.

[0121] Step S404, on-chain reputation dynamic weight calculation.

[0122] Optionally, the historical performance records, transaction feedback, and compliance of the participants' rights usage can be obtained from the on-chain behavior log and scoring system. According to the preset algorithm (such as weighted average method), the credit weight of each participant (especially the members of the joint bid body) is dynamically calculated to provide weight basis for the rights allocation. High-credit participants can obtain reasonable inclination in rights allocation (such as priority in selecting profit distribution methods).

[0123] Step S406, the rights allocation rules are executed.

[0124] Optionally, the preset rights weight model of the digital asset auction system can be called to allocate the rights (content access rights, data income, service permissions, etc.) of the winning bidder in combination with the "resource-rights statement" and the dynamic credit weight. Customized allocation strategies (linear, step, and dynamic credit weighting) are supported. For example, when a joint bid is won, the usage rights and profit rights are split according to the comprehensive score of the members' investment proportion and credit weight to generate detailed rights allocation details.

[0125] Step S408, the optimal clearing path is constructed.

[0126] Optionally, the "debt offset network minimum transfer algorithm" in graph theory can be used to analyze the fund / rights correlation between participants (such as the investment and profit relationship between members of the joint bid body). A multi-lateral clearing path is constructed to reduce repeated transfer links, lower clearing costs and time, and simplify multiple transfers into key transfers between core nodes through debt offset.

[0127] Step S410, asset transfer and on-chain record.

[0128] Optionally, the on-chain smart contract can be called to perform the transfer operation of funds (bid settlement), points, and data rights. The transfer process supports the non-revocable feature and generates an audit log to record the transfer amount, rights transfer content, timestamp, and other information. All clearing operations and results are written to the blockchain through the "data record contract" to ensure transparent, traceable, and tamper-proof clearing.

[0129] In the embodiments of the present application, the value vector of the digital asset is determined according to the preset asset evaluation project, wherein the value vectors of different types of digital assets have the same dimension; the digital assets are clustered according to the value vectors of the digital assets to obtain a plurality of digital asset groups; the auction demand of the target auction scene is determined, and digital assets are selected from the digital asset groups to form a target digital asset auction package according to the auction demand; and the target digital asset auction package is auctioned through the blockchain. The value vector of the digital asset is used to realize the unified evaluation of different types of digital assets, achieve the purpose of combining and packaging different types of digital assets for auction, thereby realizing the technical effect of improving the efficiency of digital asset auction, and further solving the technical problem of low auction efficiency caused by the inability to combine and auction the packaged heterogeneous digital assets in related technologies.

[0130] The embodiments of the present application provide a digital asset auction system as shown in Figure 5 It can be seen from Figure 5 that the system includes a user terminal layer 50, a front-end service layer 52, a digital asset auction processing layer 54, and a storage and external interface layer 56. The digital asset auction layer 54 further includes an on-chain contract module 540, an identity and reputation module 542, a data analysis and matching module 544, and a monitoring and governance module 546. The digital asset auction processing layer 54 can be used to execute the following digital asset auction method: determining the value vector of the digital asset according to the preset asset evaluation project, wherein the value vectors of different types of digital assets have the same dimension; clustering the digital assets according to the value vectors of the digital assets to obtain a plurality of digital asset groups; determining the auction demand of the target auction scene, and selecting digital assets from the digital asset groups to form a target digital asset auction package according to the auction demand; and auctioning the target digital asset auction package through the blockchain.

[0131] In some embodiments of the present application, the user terminal layer 50 includes a browser, a DApp, or a mobile application. The user can perform the following operations through the user terminal layer 50: initiating bidding, participating in bidding, viewing bidding results, authorizing rights and interests, viewing reputation points, etc.

[0132] In some embodiments of the present application, the front-end service layer 52 includes a gateway for providing user identity recognition, speech control, permission verification, transaction request preprocessing, and other services.

[0133] In some embodiments of the present application, the following sub-contracts can be included in the on-chain contract module 540: Fragment bidding management contract: responsible for the reception, matching and bid verification of multiple bidding fragments; Joint bidding coordination contract: control logic for multi-party consensus and cooperative bidding; Smart clearing contract: on-chain settlement of the proportion of interests according to the auction results; Reputation and weight matching contract: dynamically adjust the weight distribution ratio according to the participation history; Data record contract: ensure the on-chain traceability and non-tamperability of the whole bidding process.

[0134] In some embodiments of the present application, the identity and reputation module 542, also known as DID&Reputation Oracle, can be used to obtain the on-chain identity and past behavior of the user by integrating third-party platforms, evaluate the bidding reputation of the user and feed back to the data analysis and matching module 544 of the digital asset auction system. The data analysis and matching module 544 determines the adjustment weight of the user's bid according to the user's bidding reputation.

[0135] In some embodiments of the present application, the data analysis and matching module 544 can be used to realize functions such as dynamic bidding data aggregation, calculation of bid adjustment weight according to reputation score, resource value evaluation, etc., to support the weight matching mechanism and clearing logic of the auction process.

[0136] In some embodiments of the present application, the monitoring and governance module 546, also known as (Audit&DAO), is used to support the implementation of on-chain governance mechanisms (such as Snapshot voting) and smart auditing, thereby realizing real-time monitoring and parameter adjustment governance of the running state of the bidding mechanism.

[0137] In some embodiments of the present application, the storage and external interface layer 56, also known as Off-chain Support, is used to provide off-chain storage support functions. In addition, the storage and external interface layer 56 can also include IPFS / Arweave and other distributed storage networks, which are used to store large-scale resource descriptions, bidding process logs, historical data snapshots and other non-sensitive information.

[0138] In some embodiments of the present application, the digital asset auction device as shown in Figure 5 The process of auctioning digital assets through a blockchain includes the following steps:

[0139] First, the user submits a combination package composed of multiple assets (NFT + model file + copyright certificate);

[0140] Second, the system calls the asset value anchoring module to uniformly value and generate a joint bidding pool;

[0141] Third, the user participates in the intention bid voting, and the system dynamically sets the reserve price according to the number of intentions;

[0142] Fourth, support users to select different "permission fragments" for bidding, such as "commercial rights" of NFT or "calling rights" of AI model;

[0143] Fifth, if multiple users form a joint bidding body, the system automatically generates a smart equity contract and writes it on the chain.

[0144] Sixth, the system weights the bidding results according to user reputation history to prevent malicious bidding.

[0145] Seventh, after the bidding is successful, all contract executions and asset attributions are written on the chain.

[0146] Eighth, the asset sets a "useful life", and when it expires, it automatically triggers a recycling contract to return the asset to the next auction pool.

[0147] Embodiments of the present application provide a digital asset auction device, Figure 6 is a structural schematic diagram of the device. From Figure 6 It can be seen that the device comprises: a first processing module 60 configured to determine a value vector of a digital asset according to a preset asset evaluation item, wherein the value vectors of different types of digital assets have the same dimension; a second processing module 62 configured to cluster the digital assets according to the value vector of the digital asset to obtain a plurality of digital asset groups; a third processing module 64 configured to determine an auction demand of a target auction scene, and select digital assets from the digital asset groups to form a target digital asset auction package according to the auction demand; and a fourth processing module 66 configured to auction the target digital asset auction package through a blockchain.

[0148] In some embodiments of the present application, the step of the third processing module 64 selecting digital assets from the digital asset groups to form a target digital asset auction package according to the auction demand comprises: determining an auction demand vector according to the auction demand, wherein the dimension of the auction demand vector is the same as the dimension of the value vector; determining a candidate digital asset in the digital asset groups according to the auction demand vector, wherein the similarity between the value vector of the candidate digital asset and the auction demand vector is greater than a preset similarity threshold; and selecting the candidate digital asset to form the target digital asset auction package.

[0149] In some embodiments of the present application, the step of selecting candidate digital assets to form the target digital asset auction package by the third processing module 64 comprises: determining a plurality of candidate digital asset auction packages, wherein the candidate digital assets in the candidate digital asset auction package come from the same digital asset group; determining the auction package evaluation value of the candidate digital asset auction package, and determining the target candidate digital asset auction package according to the auction package evaluation value, wherein the auction package evaluation value reflects the estimated auction revenue of the candidate digital asset auction package, the higher the auction package evaluation value, the higher the estimated auction revenue, and the target candidate digital asset auction package is the candidate digital asset auction package with the highest auction package evaluation value among the plurality of candidate digital asset auction packages; updating the target candidate digital asset auction package according to the candidate digital assets not in the target candidate digital asset auction package to obtain the target digital asset auction package, wherein the auction package evaluation value of the target digital asset auction package is not lower than the auction package evaluation value of the target candidate digital asset auction package.

[0150] In some embodiments of the present application, the step of updating the target candidate digital asset auction package by the third processing module 64 according to the candidate digital assets not in the target candidate digital asset auction package comprises: traversing the candidate digital assets not in the target candidate digital asset auction package, and determining whether the auction package evaluation value of the target candidate digital asset auction package increases after the candidate digital assets traversed replace the digital assets in the target candidate digital asset auction package; in the case of determining that the auction package evaluation value increases, the candidate digital assets traversed replace the digital assets in the target candidate digital asset auction package.

[0151] In some embodiments of the present application, the step of determining a plurality of candidate digital asset auction packages by the third processing module 64 comprises: determining whether there are digital assets with right conflicts in the candidate digital asset auction package; deleting the candidate digital asset auction package with digital assets with right conflicts.

[0152] In some embodiments of the present application, the step of auctioning the target digital asset auction package by the fourth processing module 66 through the blockchain comprises: determining the auction object expected to be purchased by the bidder, wherein the auction object comprises the digital assets in the target digital asset auction package and the right type of the digital assets; for the auction object with right conflicts, determining the bidder who successfully bids according to the bid price of the bidder.

[0153] In some embodiments of the present application, the step of auctioning the target digital asset auction package by the fourth processing module 66 through the blockchain comprises: receiving the first bid price sent by the bidder; determining the historical auction behavior information of the bidder; adjusting the first bid price according to the historical auction behavior information to obtain the second bid price, and taking the second bid price as the bid price of the bidder.

[0154] It should be noted that each module in the above digital asset auction device can be a program module (for example, a program instruction set for implementing a certain specific function) or a hardware module. For the latter, it can be in the following form, but is not limited to: each module is a processor, or the functions of each module are implemented by a processor.

[0155] According to the embodiments of the present application, a non-volatile storage medium is also provided, and the non-volatile storage medium stores a program. When the program runs, the non-volatile storage medium controls the device where the non-volatile storage medium is located to perform the following digital asset auction method: determining a value vector of a digital asset according to a preset asset evaluation item, wherein the value vectors of different types of digital assets have the same dimension; clustering the digital assets according to the value vectors of the digital assets to obtain a plurality of digital asset groups; determining an auction demand of a target auction scene, and selecting digital assets from the digital asset groups to form a target digital asset auction package according to the auction demand; and auctioning the target digital asset auction package through a blockchain.

[0156] According to the embodiments of the present application, an electronic device is also provided, which includes a memory and a processor. The processor is configured to run a program stored in the memory. When the program runs, the electronic device performs the following digital asset auction method: determining a value vector of a digital asset according to a preset asset evaluation item, wherein the value vectors of different types of digital assets have the same dimension; clustering the digital assets according to the value vectors of the digital assets to obtain a plurality of digital asset groups; determining an auction demand of a target auction scene, and selecting digital assets from the digital asset groups to form a target digital asset auction package according to the auction demand; and auctioning the target digital asset auction package through a blockchain.

[0157] According to the embodiments of the present application, a computer program product is also provided, which includes a computer program. When the computer program is executed by a processor, the computer program implements the following digital asset auction method: determining a value vector of a digital asset according to a preset asset evaluation item, wherein the value vectors of different types of digital assets have the same dimension; clustering the digital assets according to the value vectors of the digital assets to obtain a plurality of digital asset groups; determining an auction demand of a target auction scene, and selecting digital assets from the digital asset groups to form a target digital asset auction package according to the auction demand; and auctioning the target digital asset auction package through a blockchain.

[0158] In the above embodiments of the present application, the description of each embodiment has its own focus, and the parts not described in detail in a certain embodiment can be referred to the related description of other embodiments.

[0159] In several embodiments provided in the present application, it should be understood that the disclosed technology can be implemented by other ways. Among them, the above-mentioned device embodiments are only schematic, for example, the division of the units can be a logical function division, and actual implementation can have another division mode, for example, a plurality of units or components can be combined or integrated into another system, or some features can be ignored or not executed. In addition, the coupling or direct coupling or communication connection between the displayed or discussed each other can be indirect coupling or communication connection through some interfaces, units or modules, which can be electrical or other forms.

[0160] The units described as separate components can or can not be physically separate, and the components shown as units can or can not be physical units, that is, they can be located in one place, or they can be distributed to multiple units. Part or all of the units can be selected according to actual needs to achieve the purpose of the embodiment.

[0161] In addition, each functional unit in each embodiment of the present application can be integrated in one processing unit, or each unit can be physically present alone, or two or more units can be integrated in one unit. The integrated unit can be realized in the form of hardware or in the form of a software functional unit.

[0162] The integrated unit, if realized in the form of a software functional unit and sold or used as an independent product, can be stored in a computer readable storage medium. Based on this understanding, the technical solutions of the present application essentially or the part that contributes to the related art or the whole or part of the technical solutions can be embodied in the form of a software product. The computer software product is stored in a storage medium, including a plurality of instructions for causing a computer device (which can be a personal computer, a server or a network device, etc.) to execute all or part of the steps of the method described in each embodiment of the present application. The foregoing storage medium includes: U disk, read-only memory (ROM, Read-Only Memory), random access memory (RAM, Random Access Memory), mobile hard disk, magnetic disk or optical disk and various program codes that can be stored in the medium.

[0163] The above is only the preferred embodiment of the present application, and it should be pointed out that for ordinary skilled in the art, without departing from the principles of the present application, a number of improvements and refinements can be made, which should be considered as the protection scope of the present application.

Claims

1. A digital asset auction method, characterized in that, include: Based on preset asset evaluation items, the value vector of digital assets is determined, wherein the value vector dimension of different types of digital assets is the same. The digital assets are clustered based on their value vectors to obtain multiple digital asset groups. Determine the auction requirements for the target auction scenario, and select digital assets from the digital asset group to form a target digital asset auction package based on the auction requirements; The target digital asset auction package will be auctioned via blockchain.

2. The digital asset auction method according to claim 1, characterized in that, The selection of digital assets from the digital asset group to form the target digital asset auction package based on the auction requirements includes: Based on the auction demand, an auction demand vector is determined, wherein the dimension of the auction demand vector is the same as the dimension of the value vector; Based on the auction demand vector, candidate digital assets are determined in the digital asset group, wherein the similarity between the value vector of the candidate digital asset and the auction demand vector is greater than a preset similarity threshold. The candidate digital assets are selected to form the target digital asset auction package.

3. The digital asset auction method according to claim 2, characterized in that, The selection of the candidate digital assets to form the target digital asset auction package includes: Multiple candidate digital asset auction packages are identified, wherein the candidate digital assets in the candidate digital asset auction packages come from the same group of digital assets; The auction package evaluation value of the candidate digital asset auction package is determined, and the target candidate digital asset auction package is determined based on the auction package evaluation value. The auction package evaluation value is used to reflect the estimated auction revenue of the candidate digital asset auction package. The higher the auction package evaluation value, the higher the estimated auction revenue. The target candidate digital asset auction package is the candidate digital asset auction package with the highest corresponding auction package evaluation value among the multiple candidate digital asset auction packages. The target candidate digital asset auction package is updated based on the candidate digital assets that are not in the target candidate digital asset auction package to obtain the target digital asset auction package, wherein the auction package evaluation value of the target digital asset auction package is not lower than the auction package evaluation value of the target candidate digital asset auction package.

4. The digital asset auction method according to claim 3, characterized in that, Updating the target candidate digital asset auction package based on candidate digital assets not in the target candidate digital asset auction package includes: Traverse the candidate digital assets that are not in the target candidate digital asset auction package, and determine whether the auction package evaluation value of the target candidate digital asset auction package increases after the traversed candidate digital asset replaces the digital asset in the target candidate digital asset auction package. If it is determined that the evaluation value of the auction package increases, the digital assets in the target candidate digital asset auction package are replaced with the candidate digital assets that have been traversed.

5. The digital asset auction method according to claim 2, characterized in that, Several candidate digital asset auction packages have been identified, including: Determine whether there are any digital assets with conflicting rights in the candidate digital asset auction package; Remove the candidate digital asset auction package containing digital assets with conflicting rights.

6. The digital asset auction method according to claim 1, characterized in that, The auction package of the target digital assets, auctioned via blockchain, includes: The auction object that the bidders wish to purchase is determined, wherein the auction object includes the digital assets in the target digital asset auction package, and the rights type of the digital assets; For auction items with conflicting rights, the successful bidder shall be determined based on the bid price offered by the bidder.

7. The digital asset auction method according to claim 1, characterized in that, The auction package of the target digital assets, auctioned via blockchain, includes: Receive the first bid price sent by the bidder; Determine the bidder's historical auction behavior information; The first bidding price is adjusted based on the historical auction information to obtain a second bidding price, which is then used as the bidding price for the bidder.

8. A digital asset auction device, characterized in that, include: The first processing module is used to determine the value vector of digital assets based on preset asset evaluation items, wherein the value vector dimensions of different types of digital assets are the same. The second processing module is used to cluster the digital assets based on their value vectors to obtain multiple digital asset groups. The third processing module is used to determine the auction requirements of the target auction scenario and select digital assets from the digital asset group to form a target digital asset auction package based on the auction requirements. The fourth processing module is used to auction the target digital asset auction package via blockchain.

9. A non-volatile storage medium, characterized in that, The non-volatile storage medium stores a program, wherein when the program is executed, it controls the device where the non-volatile storage medium is located to execute the digital asset auction method according to any one of claims 1 to 7.

10. An electronic device, characterized in that, include: A memory and a processor, the processor being configured to run a program stored in the memory, wherein the program, when running, executes the digital asset auction method according to any one of claims 1 to 7.

11. A computer program product, characterized in that, It includes a computer program that, when executed by a processor, implements the digital asset auction method according to any one of claims 1 to 7.

Images