WO2021139434A1

WO2021139434A1 - Method and apparatus for electronic certificate-based virtual resource allocation, and electronic device

Info

Publication number: WO2021139434A1
Application number: PCT/CN2020/132062
Authority: WO
Inventors: 王璐; 宋奚淼; 季婧
Original assignee: 支付宝(杭州)信息技术有限公司
Priority date: 2020-01-11
Filing date: 2020-11-27
Publication date: 2021-07-15
Also published as: CN111275481A

Abstract

A method for electronic certificate-based virtual resource allocation, the method comprising: receiving an electronic certificate acquisition request sent by a client, the electronic certificate acquisition request comprising a user identifier (102); in response to the electronic certificate acquisition request, determining whether a target user corresponding to the user identifier is a key user, the key user comprising a potential user that creates a user relationship group by means of the client (104); if the target user is a key user, allocating the electronic certificate to the target user, the electronic certificate being used for obtaining a preset collection right of a virtual resource, and the virtual resource being a virtual resource issued orientated to the user relationship group and shared by the members in the user relationship group (106).

Description

Virtual resource allocation method and device based on electronic certificate, and electronic equipment

Technical field

This application relates to the field of communication technology, and in particular to a virtual resource allocation method and device based on electronic credentials, and electronic equipment.

Background technique

With the development of network technology, a variety of virtual resource allocation methods have emerged. Taking the allocation of virtual resources in the form of "red envelopes" as an example, users can put e-cards, gifts, etc. into the "red envelopes", and then distribute them to a user individually or to a group. All members of the group To collect. However, as virtual resource allocation scenarios become more and more abundant, how to improve the interactivity when allocating virtual resources is of great significance for improving user experience.

Summary of the invention

This specification proposes a virtual resource allocation method based on electronic credentials. The method includes: receiving an electronic credential acquisition request sent by a client; wherein, the electronic credential acquisition request includes a user identification; in response to the electronic credential acquisition request, determining and Whether the target user corresponding to the user identifier is a key user; wherein, the key user includes potential users who create a user relationship group through the client; if the target user is the key user, report to the target user Allocate electronic vouchers; wherein, the electronic vouchers are used to obtain preset virtual resource receiving permissions; the virtual resources are issued to the user relationship group and shared by group members in the user relationship group Virtual resources.

Optionally, the key user further includes: a creator user of a user relationship group that has been created; and a user in the user relationship group that has been created that has the authority to add group members to the user relationship group.

Optionally, the virtual resource includes a repayment-free limit of a credit account.

Optionally, the user relationship group is a family relationship group composed of several generations of users with family relationships; the potential users include potential householders in the family relationship group; the method further includes: determining users based on user data Based on the determined family relationship between users, generate a family relationship tree diagram composed of several generations of users with family relationships; determine the family relationship group in the family relationship group based on the family relationship tree diagram Potential head of household.

Optionally, the determining the potential heads of households in the family relationship group based on the family relationship tree diagram includes: extracting the generation in the middle of the family relationship tree diagram, and collecting data within a preset period of time The user with the highest user activity is the potential head of the household.

Optionally, the determining whether the target user corresponding to the user ID is a key user includes: obtaining behavior data of the target user corresponding to the user ID; using the obtained behavior data as a prediction sample and inputting it to the prediction The model performs predictive calculation to obtain the probability value of the user creating a user relationship group through the client; wherein the predictive model uses the behavior data of the user who created the user relationship group through the client as a training sample , The machine learning model obtained by training; determine whether the probability value reaches the threshold; if so, determine that the target user is a key user.

Optionally, determining whether the target user corresponding to the user identifier is a key user in a user relationship group includes: matching the user identifier with a user identifier in the key user set; wherein, the key user The user set includes the determined user identification of the key user; if the user identification matches any user identification in the key user set, it is determined that the target user corresponding to the user identification is the key user.

Optionally, the method further includes: obtaining user behavior data corresponding to the user identification in the key user set; using the obtained behavior data as a prediction sample, and inputting the obtained behavior data into a prediction model for prediction calculation to obtain the user The probability value of creating a user relationship group through the client; wherein the prediction model is a machine learning model obtained by training using the behavior data of users who have created the user relationship group through the client as a training sample; and deleting; In the key user set, the user identifier of the user whose probability value is lower than the threshold is used to correct the key user in the key user set.

Optionally, the method further includes: determining whether the target user has created a user relationship group; if the target user has created a user relationship group, querying group members in the user relationship group, and reporting to the user relationship group Each group member in the group is assigned the electronic certificate respectively.

Optionally, the method further includes: in response to the issuance event corresponding to the preset virtual resource, determining a number of users from a set of users to which the electronic vouchers are allocated; and creating a user relationship group for the plurality of users The group members in the group release the virtual resources.

Optionally, the distributing the virtual resources to the group members in the user relationship groups created by the plurality of users includes: before a preset time, to the user relationship groups created by the plurality of users The group members who join the user relationship group release the virtual resources.

This specification also proposes an electronic voucher-based virtual resource allocation device. The device includes: a receiving module that receives an electronic voucher acquisition request sent by a client; wherein the electronic voucher acquisition request includes a user identification; and a determination module is responsive to An electronic credential acquisition request to determine whether the target user corresponding to the user ID is a key user; wherein the key user includes potential users who create a user relationship group through the client; the allocation module, if the target user is The key user allocates an electronic voucher to the target user; wherein the electronic voucher is used to obtain a preset virtual resource collection authority; the virtual resource is issued to a user relationship group, and is issued by the user A virtual resource shared by group members in a relationship group.

Optionally, the user relationship group is a family relationship group formed by several generations of users with family relationships; the potential users include potential householders in the family relationship group; the determining module further: determines users based on user data Based on the determined family relationship between users, generate a family relationship tree diagram composed of several generations of users with family relationships; determine the family relationship group in the family relationship group based on the family relationship tree diagram Potential head of household.

Optionally, the determining module further: extracts a generation in the middle of the family relationship tree diagram and a user with the highest user activity in a preset period of time as a potential householder.

Optionally, the determining module: obtains the behavior data of the target user corresponding to the user identification; uses the obtained behavior data as a prediction sample, and inputs the obtained behavior data into a prediction model for prediction calculation, and obtains that the user passes through the client The probability value of creating a user relationship group; wherein the prediction model is a machine learning model obtained by training using behavior data of users who have created a user relationship group through the client as a training sample; and determining whether the probability value is Reach the threshold; if yes, determine that the target user is a key user.

Optionally, the determination module: matches the user identification with a user identification in the key user set; wherein the key user set includes the determined user identification of the key user; if the user identification matches Any user identification in the key user set is matched, and a target user corresponding to the user identification is determined to be the key user.

Optionally, the device further includes: a correction module, which obtains user behavior data corresponding to the user identification in the key user set; uses the obtained behavior data as a prediction sample, and inputs it into the prediction model for prediction calculation to obtain The probability value of the user creating a user relationship group through the client; wherein, the prediction model is a machine learning obtained by using the behavior data of the user who created the user relationship group through the client as a training sample Model; delete the user identification of the user whose probability value is lower than the threshold in the key user set, so as to correct the key user in the key user set.

Optionally, the allocation module: determines whether the target user has created a user relationship group; if the target user has created a user relationship group, query the group members in the user relationship group, and then Each group member in the user relationship group is assigned the electronic certificate respectively.

Optionally, it further includes: an issuance module, in response to the issuance event corresponding to the preset virtual resource, determining a number of users from the set of users to which the electronic vouchers are allocated; Group members in the user relationship group release the virtual resources.

Optionally, the issuance module further: distributes the virtual resource to group members who have joined the user relationship group before a preset time among the user relationship groups created by the several users.

In this manual, a virtual resource allocation mode is proposed to allocate electronic vouchers to potential users who create user relationship groups through the client to receive virtual resources distributed to user relationship groups and shared by user relationship groups; Since electronic vouchers can only be issued to potential users who create user relationship groups, and virtual resources obtained based on the electronic vouchers can be shared by group members in the user relationship group; therefore, users can be promoted to create user relationship groups through the client The enthusiasm of the group helps to create and promote the user relationship group.

Description of the drawings

Fig. 1 is a flowchart of a method for allocating virtual resources based on electronic credentials according to an exemplary embodiment;

Fig. 2 is a schematic diagram of an electronic credential display interface provided by an exemplary embodiment;

Fig. 3 is a schematic diagram of a member user in a family relationship group receiving an electronic certificate according to an exemplary embodiment;

Fig. 4 is a schematic diagram of members in a family relationship group receiving virtual resources according to an exemplary embodiment;

Fig. 5 is a schematic structural diagram of an electronic device provided by an exemplary embodiment;

Fig. 6 is a block diagram of an apparatus for allocating virtual resources based on electronic credentials according to an exemplary embodiment.

Detailed ways

In this manual, a virtual resource allocation mode is proposed to allocate electronic vouchers to potential users who create user relationship groups through the client to receive virtual resources issued to user relationship groups and shared by user relationship groups In implementation, after receiving the electronic credential acquisition request sent by the client, the server can respond to the electronic credential acquisition request to determine whether the target user corresponding to the user ID in the electronic credential acquisition request is through the client Potential users who create a user relationship group; if yes, you can assign an electronic voucher to the target user; where the electronic voucher is used to obtain a preset virtual resource collection authority; the virtual resource is issued for the user relationship group, And a virtual resource shared by group members in the user relationship group.

In the above technical solution, because the electronic vouchers can only be issued to potential users who create user relationship groups, and the virtual resources received based on the electronic vouchers can be shared by group members in the user relationship groups; therefore, user access can be improved The enthusiasm of the client to create user relationship groups is helpful to the creation and promotion of user relationship groups.

In order to enable those skilled in the art to better understand the technical solutions in the application, the following will clearly and completely describe the technical solutions in the embodiments of the application in conjunction with the drawings in the embodiments of the application. Obviously, the described The embodiments are only a part of the embodiments of the present application, rather than all the embodiments. Based on the embodiments in this application, all other embodiments obtained by those of ordinary skill in the art without creative work should fall within the protection scope of this application.

Please refer to FIG. 1, which is a virtual resource allocation method based on electronic credentials provided by an embodiment of the present application, and the method performs step 102 to step 106.

Step 102: Receive an electronic credential acquisition request sent by the client; where the electronic credential acquisition request includes a user identification.

Step 104: In response to the electronic credential acquisition request, determine whether the target user corresponding to the user ID is a key user; wherein, the key user includes potential users who create a user relationship group through the client.

Step 106: If the target user is the key user, assign an electronic voucher to the target user; wherein, the electronic voucher is used to obtain a preset virtual resource receiving authority; the virtual resource is a user-oriented relationship group A virtual resource distributed by the group and shared by group members in the user relationship group.

The above-mentioned virtual resources may include any type of electronic resources that can be issued to user relationship groups and shared by group members in the user relationship group; in the illustrated embodiment, the above-mentioned virtual resources may specifically Including the waiver limit for credit accounts.

Of course, in practical applications, the aforementioned electronic resources can include, in addition to the exemption limit of credit accounts, such as electronic funds (such as "red envelopes"), electronic items, electronic resources, electronic prizes, etc., which can be listed among group members. The electronic resources shared between each other will not be listed one by one in this manual.

The above electronic vouchers include any type of electronic vouchers used to obtain the assigned permissions of the preset virtual resources; that is, the above electronic vouchers can be used as vouchers when the user extracts the virtual resources from the server.

For example, in one embodiment, a certain number of different types of electronic vouchers can be pre-configured on the server, and different types of electronic vouchers can be issued to a specific user group according to certain issuing rules; and users can collect multiple electronic vouchers. When the number of types of electronic vouchers collected reaches the preset threshold, the allocation authority of the virtual resources in the preset virtual resource collection is obtained; the specific form of the above-mentioned electronic vouchers is not restricted, and can be It is character strings, numbers, characters, passwords, virtual cards, and so on. For example, in an example, the above electronic certificate may specifically be a special virtual card that is issued by the server to a specific user group and can participate in the lottery of the credit account's free repayment amount.

The above-mentioned user relationship group may specifically include a user group formed by several users with user relationships; for example, in an embodiment, the above-mentioned user relationship group may specifically include a family relationship formed by several generations of users with family relationships. Group.

The above key users may specifically refer to the key users related to the user relationship group; in this specification, the above key users may specifically include potential users who create user relationship groups through the client; In the specification, the above-mentioned key users can include not only potential users who create user relationship groups through the client, but also the creator users of the user relationship groups that have been created, and the user relationship groups that have been created. Users with permissions to add group members to the group, and so on.

In this manual, the user can perform a specific electronic certificate receiving operation through the client to receive the electronic certificate from the server; among them, the specific operation type of the electronic certificate receiving operation performed by the user through the client is not performed in this manual Special limitation; In the illustrated embodiment, the above-mentioned client can be an AR (Augmented Reality) client, and the user can scan a specific offline target through the AR client to trigger the server to issue to the user Electronic vouchers; for example, the user can use the AR client to scan the pre-determined graphic logo deployed offline to trigger the server to issue electronic vouchers for the user; or, the user can also use the AR client for any or specific The person’s face is scanned in an image to trigger the server to issue an electronic certificate for the user.

In practical applications, in addition to the above-described electronic certificate receiving operation, the user can also interact with other users who have social relationships with the user to obtain electronic certificates held by other users.

In the illustrated embodiment, in addition to issuing electronic vouchers to the user, the server can also issue some virtual props to the user, and the user can use these virtual props to "rob" the electronic vouchers held by other users; For example, in implementation, these virtual items can be special electronic vouchers. After the user "uses" these special electronic vouchers, he can select a specific user from other users who have social relationships, and select a specific user from other users who have social relationships. The electronic certificate is randomly selected from the electronic certificate and used as one's own.

In another embodiment shown, the server can also issue some virtual props to the user, and the user can use these virtual props to trigger the server to select an electronic voucher from other users' electronic voucher, and " Copy" the electronic certificate, and then issue the "copy" electronic certificate to the user.

In this manual, when the client monitors that the user performs any of the above-described electronic credential receiving operations, it can send an electronic credential acquisition request to the server; where the electronic credential acquisition request may include the user’s user Identification; for example, taking the foregoing client as a payment client as an example, the user identification may specifically be the payment account of the user.

When the server receives the electronic credential acquisition request sent by the client, it can acquire the user ID carried in the electronic credential acquisition request to determine whether the user corresponding to the user ID is a key user.

Among them, the above-mentioned key users may specifically include potential users who create user relationship groups through the client. The aforementioned potential users refer to users with a high probability of creating user relationship groups through the client.

In the illustrated embodiment, taking the above-mentioned user relationship group as an example of a family relationship group composed of several generations of users with family relationships, due to the potential householder in the family relationship group, the user relationship group created by the client The needs of the family relationship group; therefore, in this scenario, the above-mentioned potential user may specifically be a potential householder in the family relationship group.

In implementation, the server can determine the family relationship between users based on the user data stored in the background; then based on the determined family relationship between users, it generates a family relationship tree composed of several generations of users with family relationships. Figure; Among them, it should be noted that the server determines the specific method of family relationship between users based on the user data stored in the background, which is not described in detail in this specification; for example, in actual applications, it can be based on the background stored The user information between users can be clarified to determine the relationship between users, and the family relationship between users can be predicted through interaction data between users in the absence of user information that can clarify between users.

After the server generates the family relationship tree diagram, the potential householder in the family relationship group can be determined based on the family relationship tree diagram; among them, the householder in the family relationship group is usually located in the family relationship tree diagram For example, the generation in the range of 25-45 years of age; therefore, in the illustrated embodiment, the generation located in the middle of the family relationship tree can be extracted and set in the preset The user with the highest user activity in the period of time is the potential householder.

It should be noted that the user activity described above can be specifically evaluated by using account indicators related to the user account as an evaluation factor; among them, the specific type of the above user account can usually be related to the specific type of the above virtual resource; for example, Take the above virtual resource as an example of the repayment-free limit of the credit account. In this scenario, when evaluating the user’s activity, you can extract the user’s credit account based on the credit limit and transaction within a preset period of time. Indicators such as the number of transactions, the total transaction amount, and the number of transactions whose transaction amount is greater than the threshold are used to evaluate user activity.

Among them, the specific evaluation method when evaluating user activity is not specifically limited in this specification; in practical applications, training samples can be constructed based on the indicators listed above, and the machine learning model can be trained based on the constructed training samples , And then evaluate the user’s activity based on the machine learning model, which will not be described in detail in this specification.

After the server determines the potential householder in the family relationship group based on the above-mentioned family relationship tree diagram, it can regard the potential householder as the above-mentioned key user, and add the user ID of the potential householder to the preset set of key users in.

Among them, the above-mentioned key user set is created by the server in the background, and is used to maintain a set of determined user identities of the key users.

In another embodiment shown, the above-mentioned key users may include not only potential users who create user relationship groups through the client, but also creator users of user relationship groups that have been created, and users who have created user relationship groups. A combination of one or more users in the user relationship group such as users with the permission to add group members to the user relationship group.

In this case, the server can traverse the user relationship groups that have been created, query the creator user of each user relationship group that has been created, and those user relationship groups that have added groups to the user relationship group. Users with the rights of group members; then, the obtained user IDs of these users can also be added to the above-mentioned key user set.

Of course, in practical applications, the above-mentioned key users may also only include potential users who create user relationship groups through the client, but not the other types of key users described above.

In the illustrated embodiment, when determining whether the user corresponding to the user identification carried in the electronic credential acquisition request is a key user, the server may match the user identification with the user identification in the key user set; If the user ID matches any user ID in the above-mentioned key user set, it can be determined that the target user corresponding to the user ID is the above-mentioned key user.

Among them, it should be noted that since the key user set contains potential users who are determined by the server to create user relationship groups through the client, it is still uncertain whether such potential users will eventually create user relationship groups; Therefore, in actual applications, there may still be a large number of potential users in the above-mentioned key user set who may not eventually create a user relationship group.

Based on this, in this specification, it is also possible to filter the key users whose behavior characteristics in the key user set do not match the behavior characteristics of the user group by learning the behavior characteristics of the user group that has created the user relationship group, and then To achieve the purpose of revising the key users in the above-mentioned key user set.

In implementation, the server can obtain the behavior data of a number of users who have created user relationship groups through the client as training samples to train a prediction model; wherein, the above prediction model can specifically be used to predict the user relationship created by the user Probabilistic machine learning model of the group; wherein, the above-mentioned behavior data may specifically include any form of user behavior characteristics, which is not specifically limited in this specification; the specific type of the above-mentioned machine learning model is not specifically defined in this specification. Limit; For example, in practical applications, a supervised machine learning model such as logistic regression can be used.

After the above-mentioned machine learning model training is completed, the server can obtain the user's behavior data corresponding to the user identification in the above-mentioned key user set; use the obtained behavior data as a prediction sample and input it into the prediction model for prediction calculation to obtain the above-mentioned key The probability value of each key user in the user set that creates a user relationship group through the client; then, the server can compare the predicted probability value of each key user in the above-mentioned key user set with a threshold to determine the probability of each key user Whether the probability value reaches the threshold; further, the user identification of the key user whose probability value is lower than the threshold in the key user set can be deleted from the key user set to complete the correction of the key user in the key user set.

In this way, some of the key users in the above key user set that may not create a user relationship group can be filtered out from the above key user set, so that no user relationship group will eventually be created in the above key user set. The number of users.

In this specification, when the server determines whether the user corresponding to the user ID carried in the above electronic credential acquisition request is a key user, in addition to the above description, it can directly match the user ID with the user ID in the above key user set. In addition to the method, a machine learning model can also be used to directly predict the probability of the user creating a user relationship group, and based on the predicted probability to determine whether the user is a key user.

In the illustrated embodiment, the server can still obtain the behavior data of several users who have created user relationship groups through the client as training samples to train a prediction model; wherein, the above prediction model can also be specifically A machine learning model used to predict the probability of a user creating a user relationship group; when the above machine learning model training is completed, the server can obtain the user behavior data corresponding to the user ID carried in the above electronic credential acquisition request; The behavior data of is used as a prediction sample, and input to the prediction model for prediction calculations to obtain the probability value of the user creating a user relationship group through the client; then, the probability value of the user creating a user relationship group can be compared with a threshold value, It is determined whether the probability value of the user creating a user relationship group reaches the threshold; if it is, the probability of the user creating a user relationship group is higher at this time, then the user can be determined as the above-mentioned key user.

In this specification, after the server determines that the user corresponding to the user ID carried in the above electronic credential acquisition request is a key user, it can assign the above electronic credential to the key user; for example, in practical applications, the above server can carry A probability model, which is specifically used to calculate a probability for the user to receive the above electronic voucher based on the user's various user index data. When the server allocates the electronic vouchers to the user, it can first call the above-mentioned probability model, and calculate the probability that the user receives the above-mentioned electronic vouchers based on the user's various user indicators, and then provide the user with the calculated probability Allocate the above electronic vouchers.

Among them, the above probability model is a specific calculation method for the user to calculate the probability of receiving the above electronic voucher, which will not be described in detail in this specification.

In this manual, after the server determines that any key user can receive the electronic certificate, it can further determine whether the key user has created a user relationship group; if the user has created a user relationship group, it can report to the user relationship group. Each group member in the group is assigned the electronic certificate; for example, in implementation, the server can send the electronic certificate acquisition prompt corresponding to the electronic certificate to the client where each group member is located to remind each group The group members receive the e-voucher.

After each group member obtains the electronic voucher through the client, the client can generate a corresponding display picture for the obtained electronic voucher, and add the generated display picture to the display corresponding to the electronic voucher in the electronic voucher display interface The location is displayed to the first user to hold the electronic credential on the user's client.

In this specification, the above-mentioned virtual resources can be issued specifically in the form of extracting several users from the user set allocated with electronic vouchers for issuing; in implementation, the server can determine in real time whether the above-mentioned virtual resources meet the issuing conditions; For example, the virtual resource can be set to a release time, and when the release time is reached, the virtual resource is considered to meet the issuance condition; when the virtual resource meets the issuance condition, the server can respond to the preset virtual resource The corresponding issuance instruction determines a number of users from the set of users who are assigned electronic vouchers; for example, a method of randomly selecting a number of users can also be used to calculate the probability of each user receiving virtual resources through a probability model. The method of extracting several users from the user set of the electronic credential is not particularly limited in this manual; then, the server can determine the group members in the user relationship group created by the several users, and report to the several users The group members in the created user relationship group distribute the above virtual resources; for example, in implementation, the server can send the receipt of the above virtual resources to the client where each group member is located (for example, it can be a winning reminder ) To remind each group member to receive virtual resources.

In the illustrated embodiment, the server is issuing the above virtual resources to the group members in the user relationship groups created by the above several users. Specifically, the server may issue the above virtual resources to the user relationship groups created by the above several users. The group members who joined the user relationship group before the preset time release the above-mentioned virtual resources.

Wherein, the above-mentioned preset time may specifically be the time of issuance of the above-mentioned virtual resource, or may be any designated time before the above-mentioned issuance time, which is not particularly limited in this specification.

The technical solutions in the above embodiments will be described in detail below in conjunction with specific application scenarios.

In the illustrated scenario of red envelope distribution of "five lucky points award", the above-mentioned client may be a payment client. The above-mentioned server may be a payment platform docked with the Alipay client. The above-mentioned virtual resource collection may refer to the operator of the payment platform; or, the enterprise fund account of an enterprise cooperating with the operator of the payment platform. The funds under the corporate fund account are the total amount of funds used to issue red envelopes to users.

The above electronic vouchers can include five types of virtual lucky cards such as "Shoukangfu", "Youaifu", "Fuqiangfu", "Jiahefu" and "Caiwangfu". When the user collects the above 5 types of virtual lucky cards, You can automatically obtain the permission to receive red envelopes.

In addition to the above 5 types of virtual foca, the server can also issue some special virtual foca as virtual items to the user; for example, the special virtual foca can be a "blessing card"; the user can get blessed by "using" The card can interact with other users with social relationships. On the basis that the electronic vouchers held by other users are not reduced, randomly "copy" and obtain the electronic vouchers held by other users.

In addition to the above-mentioned five types of virtual fortune cards, the above electronic voucher may also include a "family portrait" special fortune card; the "family portrait" special fortune card is used to participate in the "help the whole family to spend money" Sweepstakes can only be issued to potential users who may create a "My Home" family group by the client; among them, "Huabe" is a credit account; the prize of "Help the whole family Huabei" is created to users The "My Home" family group provides a certain amount of "repayment-free quota" that can be shared by family members in the "My Home" family group. Among them, "My Home" is a family relationship group created by the user through the payment client.

Please refer to Figure 2. Figure 2 is a schematic diagram of an electronic voucher display interface shown in this specification.

As shown in Figure 2, the above electronic voucher display interface can be specifically the "My Fortune Card" interface; in this interface, the corresponding display location can be provided for the above 5 types of virtual Fortune cards and the "Family Fortune Card" held by the user .

Please continue to refer to Figure 2. In actual applications, the special virtual lucky cards issued by the server to users can also include special lucky cards such as "universal lucky cards" and "huahua cards"; that is, the payment platform's special virtual lucky cards. The operator can flexibly customize virtual props corresponding to various functions for users based on actual needs, which will not be listed one by one in this manual.

Please refer to FIG. 3, which is a schematic diagram of the member users in a family relationship group receiving the "family portrait card" shown in this specification.

As shown in Figure 3, the server can obtain the "My Home" family group created by the user when assigning the "Family Portrait Card" to potential users who may create "My Home" and "Family Groups" through the client. Each member in the group then sends a reminder of “Congratulations to your family for obtaining a family photo card” to the client of each member. After each member confirms the prompt for collection, the client can send the “Family Photo Card” in Store and display in the "My Fuca" interface.

It should be noted that when any user quits the "My Home" family group, the server can withdraw the "Family Portrait Card" assigned to the user, and the user no longer has the prize draw for "Helping the whole family return flowers" The "Family Photo Card" will not continue to be stored and displayed on the user's client.

Please refer to FIG. 4, which is a schematic diagram of a member winning a prize in a family relationship group shown in this specification;

As shown in Figure 4, the server can randomly select a number of users from the set of users who have obtained the "Family Portrait Card" as the winning users at a specified time, and obtain each of the "My Home" family groups created by each winning user. The members then send a winning reminder of "Congratulations on winning the prize for helping the whole family" to the client of each member. Each member can check the winning reminder to check related winning matters.

In the above technical solution, because the "Family Portrait Card" can only be issued to potential users who create the "My Home" family group, and the "Help the Family Photo Card" received based on the "Family Family Portrait Card" can be issued by the "My Family Card". "Shared by all members of the family group; therefore, it can increase the enthusiasm of users to create the "My Home" family group through the client, and help the creation and promotion of the "My Home" family group.

For example, because the "Help the whole family spend money" award can be shared by members of the "My Home" family group; therefore, users who have obtained the "Family Portrait Card", if the "My Home" family group has not been created yet, You can actively create a "My Home" family group before the "Help the whole family spend money" prize draws.

In another technical solution, the aforementioned "family card" can also be issued to those users who have created the "My Home" family group through the client, and those who have created the "My Home" family group. User distribution for adding new family members to the "My Home" family group; in the above technical solution, the creator of each "My Home" family group can be prompted, and the "My Home" family group has Users who add new family members to family members actively expand the family members in the "My Home" family group.

For example, because the "Help the whole family spend money" award can be shared by members of the "My Home" family group; therefore, users who have obtained the "Family Portrait Card", if the "My Home" family group has not been created yet , You can actively invite new family members to join the "My Home" family group before the "Help the whole family spends" grand prize draw, and expand the family members in the "My Home" family group, which is helpful Yu continues to improve the family members in the "My Home" family group, so that more users can join the "My Home" family group.

Corresponding to the foregoing method embodiment, this application also provides an embodiment of the device.

Corresponding to the foregoing method embodiments, this specification also provides an embodiment of an electronic credential-based virtual resource allocation device. The embodiments of the virtual resource allocation apparatus based on electronic credentials in this specification can be applied to electronic equipment. The device embodiments can be implemented by software, or can be implemented by hardware or a combination of software and hardware. Taking software implementation as an example, as a logical device, it is formed by reading the corresponding computer program instructions in the non-volatile memory into the memory through the processor of the electronic device where it is located. From the perspective of hardware, as shown in Figure 5, a hardware structure diagram of the electronic device where the virtual resource allocation device based on electronic credential of this specification is located, except for the processor, memory, network interface, and non-volatile memory shown in Figure 5 In addition to the volatile memory, the electronic device in which the device is located in the embodiment generally may include other hardware according to the actual function of the electronic device, which will not be repeated here.

Fig. 6 is a block diagram of an apparatus for allocating virtual resources based on electronic credentials according to an exemplary embodiment of the present specification.

Please refer to FIG. 6, the virtual resource allocation apparatus 60 based on electronic credentials can be applied to the electronic device shown in FIG. 5, and includes: a receiving module 601 that receives an electronic credential acquisition request sent by a client; wherein, the electronic The credential acquisition request includes a user identification; the determining module 602, in response to the electronic credential acquisition request, determines whether the target user corresponding to the user identification is a key user; wherein the key user includes creating a user relationship group through the client The allocation module 603, if the target user is the key user, allocate an electronic voucher to the target user; wherein the electronic voucher is used to obtain a preset virtual resource receiving authority; the virtual resource It is a virtual resource distributed to a user relationship group and shared by group members in the user relationship group.

In this embodiment, the key users further include: the creator user of the user relationship group that has been created; and the user who has the permission to add group members to the user relationship group in the created user relationship group.

In this embodiment, the virtual resource includes the repayment limit of the credit account.

In this embodiment, the user relationship group is a family relationship group composed of several generations of users with family relationships; the potential users include potential householders in the family relationship group; the determining module 602 is further: based on users Data determine the family relationship between users; based on the determined family relationship between users, generate a family relationship tree diagram composed of several generations of users with family relationships; determine the family relationship based on the family relationship tree diagram Potential heads of households in the group.

In this embodiment, the determining module 602 further: extracts the generation located in the middle of the family relationship tree diagram and the user with the highest user activity in a preset period of time as the potential householder.

In this embodiment, the determining module 602: obtains the behavior data of the target user corresponding to the user identification; uses the obtained behavior data as a prediction sample, and inputs the obtained behavior data into the prediction model for prediction calculation, and obtains that the user passes all the data. The client creates a probability value of a user relationship group; wherein the prediction model is a machine learning model obtained by training using behavior data of users who have created a user relationship group through the client as a training sample; and determining the Whether the probability value reaches the threshold; if so, it is determined that the target user is a key user.

In this embodiment, the determining module 602: matches the user identification with the user identification in the key user set; wherein, the key user set includes the determined user identification of the key user; if the The user ID matches any user ID in the key user set, and the target user corresponding to the user ID is determined to be the key user.

In this embodiment, the device 60 further includes: a correction module 604 (not shown in FIG. 6) to obtain user behavior data corresponding to the user identification in the key user set; and use the obtained behavior data as The prediction sample is input to the prediction model for prediction calculation to obtain the probability value of the user creating a user relationship group through the client; wherein the prediction model is the user who will create a user relationship group through the client The behavior data of is used as a training sample to train the machine learning model obtained; the user identification of the user whose probability value is lower than the threshold in the key user set is deleted, so as to correct the key user in the key user set.

In this embodiment, the allocation module 603: determines whether the target user has created a user relationship group; if the target user has created a user relationship group, query the group members in the user relationship group, Allocating the electronic certificate to each group member in the user relationship group.

In this embodiment, the device 60 further includes: an issuance module 605 (not shown in FIG. 6), in response to the issuance event corresponding to the preset virtual resource, from a collection of users who are assigned the electronic vouchers A number of users are determined in the database; and the virtual resource is issued to group members in a user relationship group created by the number of users.

In this embodiment, the issuance module 605 further: distributes the virtual resource to group members who have joined the user relationship group before a preset time among the user relationship groups created by the several users.

The systems, devices, modules, or units explained in the above embodiments may be specifically implemented by computer chips or entities, or implemented by products with certain functions. A typical implementation device is a computer. The specific form of the computer can be a personal computer, a laptop computer, a cellular phone, a camera phone, a smart phone, a personal digital assistant, a media player, a navigation device, an email receiving and sending device, and a game control A console, a tablet computer, a wearable device, or a combination of any of these devices.

In a typical configuration, the computer includes one or more processors (CPU), input/output interfaces, network interfaces, and memory.

The memory may include non-permanent memory in computer readable media, random access memory (RAM) and/or non-volatile memory, such as read-only memory (ROM) or flash memory (flash RAM). Memory is an example of computer readable media.

Computer-readable media include permanent and non-permanent, removable and non-removable media, and information storage can be realized by any method or technology. The information can be computer-readable instructions, data structures, program modules, or other data. Examples of computer storage media include, but are not limited to, phase change memory (PRAM), static random access memory (SRAM), dynamic random access memory (DRAM), other types of random access memory (RAM), read-only memory (ROM), electrically erasable programmable read-only memory (EEPROM), flash memory or other memory technology, CD-ROM, digital versatile disc (DVD) or other optical storage, Magnetic cassettes, disk storage, quantum memory, graphene-based storage media or other magnetic storage devices, or any other non-transmission media, can be used to store information that can be accessed by computing devices. According to the definition in this article, computer-readable media does not include transitory media, such as modulated data signals and carrier waves.

It should also be noted that the terms "include", "include" or any other variants thereof are intended to cover non-exclusive inclusion, so that a process, method, commodity or equipment including a series of elements includes not only those elements, but also Other elements that are not explicitly listed, or also include elements inherent to such processes, methods, commodities, or equipment. If there are no more restrictions, the element defined by the sentence "including a..." does not exclude the existence of other identical elements in the process, method, commodity, or equipment that includes the element.

The foregoing describes specific embodiments of this specification. Other embodiments are within the scope of the appended claims. In some cases, the actions or steps described in the claims can be performed in a different order than in the embodiments and still achieve desired results. In addition, the processes depicted in the drawings do not necessarily require the specific order or sequential order shown in order to achieve the desired results. In some embodiments, multitasking and parallel processing are also possible or may be advantageous.

The terms used in one or more embodiments of this specification are only for the purpose of describing specific embodiments, and are not intended to limit one or more embodiments of this specification. The singular forms of "a", "said" and "the" used in one or more embodiments of this specification and the appended claims are also intended to include plural forms, unless the context clearly indicates other meanings. It should also be understood that the term "and/or" as used herein refers to and includes any or all possible combinations of one or more associated listed items.

It should be understood that although the terms first, second, third, etc. may be used to describe various information in one or more embodiments of this specification, the information should not be limited to these terms. These terms are only used to distinguish the same type of information from each other. For example, without departing from the scope of one or more embodiments of this specification, the first information may also be referred to as second information, and similarly, the second information may also be referred to as first information. Depending on the context, the word "if" as used herein can be interpreted as "when" or "when" or "in response to determination".

The above descriptions are only preferred embodiments of one or more embodiments of this specification, and are not intended to limit one or more embodiments of this specification. All within the spirit and principle of one or more embodiments of this specification, Any modification, equivalent replacement, improvement, etc. made should be included in the protection scope of one or more embodiments of this specification.

Claims

A virtual resource allocation method based on electronic credentials, the method comprising:

Receiving an electronic credential acquisition request sent by the client; wherein the electronic credential acquisition request includes a user ID;

In response to the electronic credential acquisition request, determining whether the target user corresponding to the user ID is a key user; wherein, the key user includes potential users who create a user relationship group through the client;

If the target user is the key user, assign an electronic voucher to the target user; wherein, the electronic voucher is used to obtain a preset virtual resource collection authority; the virtual resource is issued to a user relationship group , And a virtual resource shared by group members in the user relationship group.
According to the method of claim 1, the key user further comprises:

The creator user of the user relationship group that has been created;

Users who have the permission to add group members to the user relationship group in the created user relationship group.
The method according to claim 1, wherein the virtual resource includes a repayment-free amount of a credit account.
The method according to claim 2, wherein the user relationship group is a family relationship group formed by several generations of users with family relationships; the potential users include potential householders in the family relationship group;

The method also includes:

Determine the family relationship between users based on user data;

Based on the determined family relationship between users, generate a family relationship tree diagram composed of several generations of users with family relationships;

The potential householder in the family relationship group is determined based on the family relationship tree diagram.
The method according to claim 4, wherein the determining a potential householder in the family relationship group based on the family relationship tree diagram comprises:

The user who is located in the middle generation in the family relationship tree diagram and has the highest user activity within a preset period of time is extracted as a potential householder.
The method according to claim 1, wherein the determining whether the target user corresponding to the user identifier is a key user comprises:

Acquiring behavior data of the target user corresponding to the user identification;

The acquired behavior data is used as a prediction sample and input into a prediction model for prediction calculation to obtain the probability value of the user creating a user relationship group through the client; wherein, the prediction model is to be created by the client Using the behavior data of users in the user relationship group as training samples, the machine learning model obtained by training;

It is determined whether the probability value reaches a threshold value; if so, it is determined that the target user is a key user.
The method according to claim 1, determining whether the target user corresponding to the user identifier is a key user in a user relationship group, comprising:

Matching the user identification with the user identification in the key user set; wherein the key user set includes the determined user identification of the key user;

If the user ID matches any user ID in the key user set, it is determined that the target user corresponding to the user ID is the key user.
The method according to claim 7, further comprising:

Obtaining user behavior data corresponding to the user identifier in the key user set;

The acquired behavior data is used as a prediction sample and input into a prediction model for prediction calculation to obtain the probability value of the user creating a user relationship group through the client; wherein, the prediction model is to be created by the client Using the behavior data of users in the user relationship group as training samples, the machine learning model obtained by training;

Delete the user identification of the user whose probability value is lower than the threshold in the key user set, so as to correct the key user in the key user set.
The method according to claim 1, further comprising:

Determining whether the target user has created a user relationship group;

If the target user creates a user relationship group, query group members in the user relationship group, and assign the electronic credentials to each group member in the user relationship group.
The method according to claim 1, further comprising:

In response to the issuance event corresponding to the preset virtual resource, a number of users are determined from the set of users to which the electronic vouchers are allocated;

Distribute the virtual resources to group members in the user relationship groups created by the several users.
The method according to claim 10, wherein the distributing the virtual resources to group members in the user relationship groups created by the plurality of users comprises:

Distribute the virtual resources to group members who have joined the user relationship group before a preset time in the user relationship groups created by the plurality of users.
A virtual resource allocation device based on an electronic certificate, the device comprising:

The receiving module receives an electronic credential acquisition request sent by the client; wherein the electronic credential acquisition request includes a user ID;

The determining module, in response to the electronic credential acquisition request, determines whether the target user corresponding to the user ID is a key user; wherein the key user includes potential users who create a user relationship group through the client;

The allocation module, if the target user is the key user, allocate an electronic voucher to the target user; wherein the electronic voucher is used to obtain a preset virtual resource receiving authority; the virtual resource is a user-oriented relationship group A virtual resource distributed by the group and shared by group members in the user relationship group.
The device according to claim 12, the key user further comprises:

The creator user of the user relationship group that has been created;

Users who have the permission to add group members to the user relationship group in the created user relationship group.
The apparatus according to claim 12, wherein the virtual resource includes a repayment-free amount of a credit account.
The apparatus according to claim 13, wherein the user relationship group is a family relationship group formed by several generations of users who have a family relationship; the potential users include potential householders in the family relationship group;

The determining module further:

Determine the family relationship between users based on user data;

Based on the determined family relationship between users, generate a family relationship tree diagram composed of several generations of users with family relationships;

The potential householder in the family relationship group is determined based on the family relationship tree diagram.
According to the device of claim 15, the determining module further:

The user who is located in the middle generation in the family relationship tree diagram and has the highest user activity within a preset period of time is extracted as a potential householder.
The device according to claim 12, the determining module:

Acquiring behavior data of the target user corresponding to the user identification;

The acquired behavior data is used as a prediction sample and input into a prediction model for prediction calculation to obtain the probability value of the user creating a user relationship group through the client; wherein, the prediction model is to be created by the client Using the behavior data of users in the user relationship group as training samples, the machine learning model obtained by training;

It is determined whether the probability value reaches a threshold value; if so, it is determined that the target user is a key user.
The device according to claim 12, the determining module:

Matching the user identification with the user identification in the key user set; wherein the key user set includes the determined user identification of the key user;

If the user ID matches any user ID in the key user set, it is determined that the target user corresponding to the user ID is the key user.
The device according to claim 18, further comprising:

The correction module obtains the user behavior data corresponding to the user identification in the key user set; uses the obtained behavior data as a prediction sample and inputs it into the prediction model for prediction calculation, and obtains that the user creates a user through the client The probability value of the relationship group; wherein the prediction model is a machine learning model obtained by training using the behavior data of users who have created a user relationship group through the client as a training sample; deleting the key user set, The user identification of the user whose probability value is lower than the threshold is used to correct the key user in the key user set.
The device according to claim 12, the distribution module:

Determining whether the target user has created a user relationship group;

If the target user creates a user relationship group, query group members in the user relationship group, and assign the electronic credentials to each group member in the user relationship group.
The device according to claim 12, further comprising:

The issuance module, in response to the issuance event corresponding to the preset virtual resource, determines a number of users from the set of users to which the electronic vouchers are allocated;

Distribute the virtual resources to group members in the user relationship groups created by the several users.
The device according to claim 21, the issuing module further:

Distribute the virtual resources to group members who have joined the user relationship group before a preset time in the user relationship groups created by the plurality of users.
An electronic device including:

processor;

A memory for storing processor executable instructions;

Wherein, the processor implements the method according to any one of claims 1-11 by running the executable instruction.
A computer-readable storage medium having computer instructions stored thereon, which, when executed by a processor, implement the steps of the method according to any one of claims 1-11.