CN117035960A

CN117035960A - Digital collection generation method, device, computer equipment and storage medium

Info

Publication number: CN117035960A
Application number: CN202310761695.4A
Authority: CN
Inventors: 肖天安; 林强; 钱巧娅; 王舒漫; 李佳宁
Original assignee: Bank of China Ltd
Current assignee: Bank of China Ltd
Priority date: 2023-06-26
Filing date: 2023-06-26
Publication date: 2023-11-10

Abstract

The application relates to a digital collection generation method, a digital collection generation device, a digital collection generation computer device, a digital collection storage medium and a digital collection storage medium. The method comprises the following steps: receiving a digital collection generation request triggered by a virtual target in the meta-universe, wherein the digital collection generation request carries collection information data and a user identifier; the user identification is the user identification of the virtual user in the meta universe; acquiring user characteristic data corresponding to the user identifier according to the user identifier; generating a target digital collection based on collection information data and user feature data; and setting a collection identifier for the target digital collection according to the user identifier, and storing the target digital collection in a preset blockchain storage area. By adopting the method, the distribution efficiency and the circulation convenience can be improved.

Description

Digital collection generation method, device, computer equipment and storage medium

Technical Field

The present application relates to the field of meta-space technology, and in particular, to a digital collection generation method, a digital collection generation device, a digital collection generation computer device, a digital collection storage medium, and a digital collection storage program product.

Background

In the financial industry, such as banking industry, articles with specific meanings, such as special periodicals, commemorative coins, mascot and the like and collection values can be issued regularly, and the collection can be issued to promote banks and create bank images and influences while meeting the user collection value-added requirements.

However, most of the collectibles released by banks are physical objects, such as entity commemorative coins, commemorative notes and the like, and the release of the entity collectibles has the problems of low release speed, high popularization cost, inconvenient circulation and small coverage of users.

Disclosure of Invention

In view of the above, it is desirable to provide a digital collection generation method, apparatus, computer device, computer-readable storage medium, and computer program product that can improve distribution efficiency and distribution convenience.

In a first aspect, the present application provides a digital collection generation method. The method comprises the following steps:

receiving a digital collection generation request triggered by a virtual target in a meta-universe, wherein the digital collection generation request carries collection information data and a user identifier; the user identifier is a user identifier of a virtual user in the meta-universe;

acquiring user characteristic data corresponding to the user identifier according to the user identifier;

generating a target digital collection based on the collection information data and the user feature data;

and setting a collection identifier for the target digital collection according to the user identifier, and storing the target digital collection in a preset blockchain storage area.

In one embodiment, the generating the target digital collection based on the collection information data and the user feature data includes:

carrying out data analysis on the collection information data to obtain basic structural characteristics of the target digital collection to be generated;

determining characteristic collection features matched with the user feature data according to the user feature data;

and combining the basic structure characteristic and the characteristic collection characteristic through a preset collection generation method to generate the target digital collection.

In one embodiment, the data analysis is performed on the collection information data to obtain an infrastructure feature of the target digital collection, including:

determining a data analysis method according to the data type of the collection information data;

and carrying out data analysis on the collection information data based on the data analysis method to obtain the basic structure characteristics of the target digital collection to be generated.

In one embodiment, the determining the feature collection feature matching the user feature data according to the user feature data includes:

inputting the user characteristic data into a preset attribute model for attribute extraction operation, and determining attribute keywords corresponding to the user characteristic data;

Determining a target feature material library corresponding to the attribute keywords according to the attribute keywords;

and determining characteristic collection features matched with the user feature data from the target feature material library based on the user identification.

In one embodiment, the determining, based on the user identification, the feature collection feature matching the user feature data from the target feature material library includes:

determining the identification grade of the user identification according to the user identification;

determining a candidate material list corresponding to the identification level from the target characteristic material library based on the identification level;

and screening out characteristic collection features matched with the user feature data from the candidate material list according to a preset screening rule.

In one embodiment, the method further comprises:

responding to the display instruction of the target digital collection, and determining the display address of the target digital collection;

generating a target collection summary according to the target digital collection;

and displaying the target collection summary and the target digital collection at the display address in an augmented reality mode.

In a second aspect, the application also provides a digital collection generation device. The device comprises:

The request receiving module is used for receiving a digital collection generation request triggered by a virtual target in the meta-universe, wherein the digital collection generation request carries collection information data and a user identifier; the user identifier is a user identifier of a virtual user in the meta-universe;

the data acquisition module is used for acquiring user characteristic data corresponding to the user identifier according to the user identifier;

the collection generation module is used for generating a target digital collection based on the collection information data and the user characteristic data;

and the storage module is used for setting a collection identifier for the target digital collection according to the user identifier and storing the target digital collection in a preset blockchain storage area.

In a third aspect, the present application also provides a computer device. The computer device comprises a memory and a processor, wherein the memory stores a computer program, and the processor realizes the steps of the digital collection generation method when executing the computer program.

In a fourth aspect, the present application also provides a computer-readable storage medium. The computer readable storage medium has stored thereon a computer program which, when executed by a processor, implements the steps of the digital collection generation method described above.

In a fifth aspect, the present application also provides a computer program product. The computer program product comprises a computer program which, when executed by a processor, implements the steps of the digital collection generation method described above.

According to the digital collection generation method, the device, the computer equipment, the storage medium and the computer program product, after the digital collection generation request triggered by the virtual target in the meta-universe is received, user characteristic data corresponding to the user identification is obtained according to the user identification of the virtual user in the meta-universe carried in the digital collection generation request, and the user characteristic data reflects the user characteristics to a certain extent. And generating the target digital collection in the meta universe based on the collection information data carried in the request and the user characteristic data. Because the dimension of the user characteristics is considered when the target digital collection is generated, the target digital collection can be better matched with the user characteristics, and the collection interest of the user is improved. The target digital collection identification is set according to the user identification, the target digital collection is stored in a preset blockchain storage area, and the value of the virtual digital collection in the meta universe is guaranteed, so that the virtual and real separation is broken through, the service coverage can be enlarged while the distribution efficiency of the digital collection is improved, and the circulation convenience of the collection is further improved.

Drawings

FIG. 1 is an application environment diagram of a digital collection generation method in one embodiment;

FIG. 2 is a flow diagram of a method of generating a digital collection in one embodiment;

FIG. 3 is a flow chart of a process for generating a target digital collection based on collection information data and user characteristic data in one embodiment;

FIG. 4 is a flowchart of a step of generating a target digital collection based on collection information data and user characteristic data in another embodiment;

FIG. 5 is a flow diagram of steps for determining feature collection characteristics matching user characteristic data based on user characteristic data in one embodiment;

FIG. 6 is a flowchart illustrating steps for determining feature collection features matching user feature data from a target feature library based on user identification in one embodiment;

FIG. 7 is a flow chart of a method of generating a digital collection in another embodiment;

FIG. 8 is a flow chart of a method of generating a digital collection in another embodiment;

FIG. 9 is a block diagram of a digital collection generating device according to one embodiment;

fig. 10 is an internal structural view of a computer device in one embodiment.

Detailed Description

The present application will be described in further detail with reference to the drawings and examples, in order to make the objects, technical solutions and advantages of the present application more apparent. It should be understood that the specific embodiments described herein are for purposes of illustration only and are not intended to limit the scope of the application.

The digital collection generation method provided by the embodiment of the application can be applied to an application environment shown in figure 1. The digital collection generation system 102 is integrated on the metauniverse 104, and communicates with the metauniverse 104 and a server 106 at the bank end through a network. The data storage system may store data that the digital collection generation system 102 needs to process. The data storage system may be integrated on the digital collection generation system 102 or may be located on a cloud or other network server. Digital collection generation system 102 receives a digital collection generation request triggered by a virtual target in meta-universe 104, the digital collection generation request carrying collection information data and a user identification, the user identification being a user identification originating from a virtual user in meta-universe 104. The digital collection generation system 102 obtains user characteristic data corresponding to the user identifier from the server 106 according to the user identifier, generates a target digital collection based on the collection information data and the user characteristic data, sets a collection identifier for the target digital collection according to the user identifier, and stores the target digital collection in a preset blockchain storage area. The metauniverse 104 may be any metauniverse platform that can implement real world virtualization and digitization, and provide a metauniverse user with a virtual space belonging to the user. Digital collection generation system 102, by integrating on meta-universe 104, can provide a virtual banking digital collection generation experience for users in meta-universe 104. A user may access the user space in meta-universe 104 through a particular terminal device to view, collect, or exchange digital collections, etc. The server 106 may be implemented as a stand-alone server or as a cluster of servers.

In one embodiment, as shown in fig. 2, a digital collection generation method is provided, and the method is applied to the digital collection generation system in fig. 1 for illustration, and includes the following steps:

step 202, receiving a digital collection generation request triggered by a virtual target in a meta-universe, wherein the digital collection generation request carries collection information data and a user identifier; the user identification is the user identification of the virtual user in the meta-universe.

The virtual target in the meta universe is a virtual user triggering the generation request of the digital collection. It can be understood that the virtual target and the owner of the digital collection can be the same virtual user or different virtual users, taking the digital collection such as the monument and the commemorative coin of the bank generated in the meta-universe by the bank as an example, the virtual target can be the bank user, the digital collection request can be generated by carrying out collection reservation triggering through the meta-universe platform, and the digital collection request can also be generated by a banking staff through triggering through the meta-universe platform. When the virtual target is a bank user, the virtual target and the owner of the digital collection at the moment can be the same user. When the virtual target is a banking staff, the virtual target and the user of the digital collection are different users.

The digital collection can be considered as a digital asset which is displayed in the virtual world and has unique identification and ownership information, namely digital collection data with the same collection value as the real collection. In banking industry, some real object collection data with specific meaning and collection value such as special periodicals, commemorative coins, mascot and the like are usually issued regularly, and the bank image and influence are created while the requirements of users are met. However, the current release of the real object collection has the problems of low release speed, high popularization cost, inconvenient circulation, small coverage of users and the like. In order to alleviate the problems of the real object collection, the service coverage range is enlarged, quick and convenient collection experience is created, and banking digital collections can be selectively built on a metauniverse platform.

The college information data is basic information data for generating a digital college, and the college information data is related to basic generation information of a banking digital college, for example, the college information data may include souvenir activity information of a bank generating the college, such as a tiger year souvenir activity, a bank year celebration souvenir activity, and the like, and college types of the digital college, such as a souvenir coin, a souvenir banknote, a souvenir mascot, and the like.

The user identification is user identification information of the digital collection owner in the meta-universe, and the display, circulation and the like of the digital collection are all required to be completed in the meta-universe, so that the digital collection owner naturally also needs to be a virtual user in the meta-universe.

Specifically, the virtual target in the meta-universe triggers and generates a digital collection generation request, and the digital collection generation system receives the digital collection generation request and acquires collection information data and user identification carried in the digital collection generation request.

In one embodiment, if the virtual target and the owner of the digital collection are the same user, the virtual target automatically records the user identifier of the user in the digital collection generation request when the generation of the digital collection generation request is triggered.

In one embodiment, if the virtual target is not the same user as the owner of the digital collection, the virtual target needs to input a user identification of the owner of the digital collection when triggering the generation of the digital collection generation request.

Step 204, obtaining user characteristic data corresponding to the user identifier according to the user identifier.

Wherein the user characteristic data is user characteristic data for reflecting user-related characteristics. The relevant information of the user, such as user preference, user occupation, user age, authority level of the user at the bank and the like, can be determined according to the user characteristic data.

Specifically, after the digital collection generating system acquires the user identification, the digital collection generating system searches the user characteristic data corresponding to the user identification from the data storage system of the bank server according to the user identification.

In one embodiment, in order to improve the security of data interaction, the digital collection generation system needs to establish communication connection with the bank server in advance to obtain the communication authority, and in the data transmission process, the preset encryption method can be used for encrypting and then transmitting the characteristic data of the user. The preset encryption method can be any encryption method capable of realizing data security transmission, such as a symmetric encryption algorithm, an asymmetric encryption algorithm, a signature encryption algorithm and the like.

Step 206, generating the target digital collection based on the collection information data and the user characteristic data.

Specifically, after acquiring the collection information data and the user characteristic data, the digital collection generation system can generate a target digital collection which meets the banking business requirements and meets the user characteristics according to the collection information data and the user characteristic data. It can be appreciated that the digital collection generation system may generate the target digital collection according to preset digital collection generation rules, for example, a pre-trained collection generation model, according to collection information data and user feature data.

And step 208, setting a collection identifier for the target digital collection according to the user identifier, and storing the target digital collection in a preset blockchain storage area.

The method is characterized in that a collection identifier is set for a target digital collection, and the target digital collection is stored in a blockchain to be a digital collection with a guarantee structure, which can be regarded as a process of setting a Non-homogeneous certificate, namely an NFT (Non-functional Token), which can carry out value attribution, circulation and virtual and real world separation, is an important means of setting up unclonable, tampered and divided encryption digital rights and interests proof in the blockchain technology, such as the irreproducibility and uniqueness, so that a bank digital collection based on the metauniverse is created, the bank digital collection is provided with a exclusive digital certificate, and is permanently stored on the blockchain and cannot be copied and tampered at will, and the core value is that contents such as daily physical currencies of banks are digitalized and recycled, and the digital ownership certificate of the virtual collection with the centralization of management and circulation is realized. Just because each NFT is unique, the uniqueness and ownership of the virtual collection is guaranteed.

Specifically, the digital collection generation system sets a collection identifier for a target digital collection according to a user identifier acquired from a digital collection generation request, and stores the target digital collection in a preset blockchain storage area.

In the digital collection generation method, after the digital collection generation request triggered by the virtual target in the meta-universe is received, user characteristic data corresponding to the user identification is obtained according to the user identification of the virtual user in the meta-universe carried in the digital collection generation request, and the user characteristic data reflects the user characteristics to a certain extent. And generating the target digital collection in the meta universe based on the collection information data carried in the request and the user characteristic data. Because the dimension of the user characteristics is considered when the target digital collection is generated, the target digital collection can be better matched with the user characteristics, and the collection interest of the user is improved. The target digital collection identification is set according to the user identification, the target digital collection is stored in a preset blockchain storage area, and the value of the virtual digital collection in the meta universe is guaranteed, so that the virtual and real separation is broken through, the service coverage can be enlarged while the distribution efficiency of the digital collection is improved, and the circulation convenience of the collection is further improved.

How to generate a target digital collection that meets both banking needs and meets user features is an important step in the overall digital collection generation method, and in one embodiment, generating a target digital collection based on collection information data and user feature data, as shown in fig. 3, includes:

and 302, carrying out data analysis on the collection information data to obtain the basic structural characteristics of the target digital collection to be generated.

The basic structure characteristic of the target digital stock is a general basic characteristic of the target digital stock, and a digital stock architecture with the general basic characteristic can be generated according to the basic structure characteristic of the target digital stock. It will be appreciated that the underlying structural features of the target digital collection are related to banking needs. For example, if the bank needs to push out the tiger year commemorative coin according to the business requirement, the digital collection generation system can analyze the collection information data, and the obtained basic structure characteristics can include the tiger year element characteristics, the commemorative coin structure characteristics and the like. If the bank needs to push out annual commemorative journals according to business requirements, the digital collection generation system analyzes the collection information data, and the obtained basic structure characteristics can comprise annual information characteristics of the bank, journal typesetting characteristics and the like.

Specifically, the digital collection generation system performs data analysis on collection information data acquired from the data collection generation request to obtain the basic structural characteristics of the target digital collection to be generated.

And step 304, determining the characteristic collection characteristics matched with the user characteristic data according to the user characteristic data.

The characteristic collection features are determined according to the user feature data, and can be matched with the user style, preference and the like. Through the characteristic collection characteristics, the digital collection generation system can add collection characteristics which are relevant to the user and can reflect the characteristics of the user on the basic structure of the target digital collection when the target digital collection is generated, so that the generated target digital collection can accord with the preference of the user.

Specifically, the digital stock generation system determines the characteristic stock characteristics matched with the user according to the user characteristic data after obtaining the user characteristic data according to the user identification.

Step 306, combining the basic structure characteristic and the characteristic collection characteristic through a preset collection generation method to generate the target digital collection.

Specifically, after the basic structural characteristics and the characteristic collection characteristics of the target digital collection are obtained, the digital collection generation system combines and adds the characteristic collection characteristics to the basic structural characteristics, so that the target digital collection which meets the banking business requirements and meets the characteristics of the user can be generated.

In the embodiment, the basic structure characteristics of the target digital stock are acquired through stock information data, and the characteristic stock characteristics matched with the user are generated through the user characteristic data, so that the target digital stock which meets the banking business requirements and meets the characteristics of the user is obtained through combination, the target digital stock can be better matched with the user, and the service coverage of the target digital stock is effectively enlarged.

Further, in one embodiment, as shown in fig. 4, the data parsing of the collection information data in step 302 to obtain the basic structural feature of the target digital collection to be generated may include:

step 402, determining a data analysis method according to the data type of the collection information data.

The digital collection generation system can acquire the basic structure characteristics of the target digital collection from the collection information data by carrying out data analysis on the collection information data. In order to improve the release efficiency of the digital collection, the digital collection generation system can not limit the data types of collection information data, namely, the collection information data can have various data formats, and when the bank generates the digital collection according to the service requirement, the collection information data submitted to the digital collection generation system can be information data of various data types. Such as the collection data information of character type, such as collection name, feature description, etc., or the collection data information, such as pictures, video logo, etc.

The input information data types are different, and the analysis modes for carrying out data analysis on the collection information data in the digital collection generation system are also different. For example, when the collection information data is a character type such as a collection name, a feature description, or the like, data analysis may be performed using a natural language processing (OCR) data analysis method or an optical character recognition (NLP) data analysis method. When the collection information data is of a data type such as a picture and a video logo, the data analysis can be performed by using relevant identification technologies such as picture identification.

Specifically, after acquiring the collection information data, the digital collection generation system determines the data type of the collection information data, and determines a corresponding data analysis method according to the data type. It can be understood that the collection information data may include a plurality of types of information data, and the digital collection generation system may determine a plurality of data analysis methods according to the collection information data, so as to analyze the collection data information.

And step 404, carrying out data analysis on the collection information data based on the data analysis method to obtain the basic structure characteristics of the target digital collection to be generated.

Specifically, the digital collection generation system performs corresponding data analysis operation on collection information data based on the determined data analysis method, and then the basic structural characteristics of the target digital collection to be generated can be obtained.

In this embodiment, the digital collection generation system may obtain a corresponding data analysis method according to the data type matching of the collection information data, so as to implement data analysis on the collection information data with various data types, so that the data type of the collection information data input by the user may not be limited when the digital collection is generated, and further, the issue efficiency of the digital collection is effectively improved.

The generation of the target digital stock through the characteristic stock features is an effective method for improving the satisfaction of the digital stock to the user. In some embodiments, as shown in fig. 5, determining a featured collection feature matching the user feature data from the user feature data includes:

step 502, inputting the user feature data into a preset attribute model to perform attribute extraction operation, and determining attribute keywords corresponding to the user feature data.

The preset attribute model is used for carrying out attribute extraction operation on the input user characteristic data so as to obtain an attribute keyword model corresponding to the user characteristic data. Attribute keywords are keywords that a user reflects the attributes of the user, and the Attribute keywords can characterize the attributes to which the user belongs. The specific classification of the attribute keywords is related to the division dimension in which the user needs to be attribute-divided, for example, if the user needs to be attribute-divided from the age of the user, the attribute keywords may be classified into young, middle-aged, elderly, and the like. If the user is to be classified according to the consumption preference of the user, the attribute keywords may be classified into household, mother and infant, electronic products, etc. The preset attribute model can be obtained by training and learning by a designer according to a large number of user characteristic training data and user attribute keywords in advance, and the corresponding attribute keywords can be accurately determined according to the user characteristic data.

Specifically, the digital collection generation system inputs the obtained user characteristic data into a preset attribute model, the preset attribute model performs attribute extraction operation on the user characteristic data, and determines attribute keywords corresponding to the user characteristic data, and the digital collection generation system acquires the attribute keywords output by the preset attribute model.

And step 504, determining a target feature material library corresponding to the attribute keywords according to the attribute keywords.

The characteristic material library is a preset material library for storing various characteristic product collection characteristics. It can be understood that the designer sets corresponding preset material libraries for various attributes in advance, and the preset material library corresponding to each attribute stores the characteristic collection features matched with the attribute.

Specifically, the digital collection generation system determines a target feature material library corresponding to the attribute keywords according to the acquired attribute keywords.

In one embodiment, a designer may bind each preset material library with its corresponding attribute keyword in advance, and generate a preset mapping table according to the corresponding relationship between the preset material library and the attribute keyword. After the digital collection generating system acquires the attribute keywords, a preset mapping table can be searched according to the attribute keywords, and a target feature material library corresponding to the attribute keywords is determined.

In one embodiment, a designer may bind the attribute keywords with the attributes corresponding to the attribute keywords in advance, and generate a preset attribute mapping table according to the corresponding relationship between each attribute keyword and each attribute. It will be appreciated that a plurality of attribute keywords may be included in an attribute. After the preset attribute mapping table is generated, a designer sets corresponding preset material libraries for all the attributes at the same time, binds all the preset material libraries with the corresponding attributes, and generates the preset material library mapping table according to the corresponding relation between the preset material libraries and the attributes. After the digital collection generating system acquires the attribute keywords, searching a preset attribute mapping table according to the attribute keywords, determining target attributes to which the attribute keywords belong, continuously searching a preset material library mapping table based on the target attributes, determining a characteristic material library corresponding to the target attributes, and determining the characteristic material library as a target characteristic material library corresponding to the attribute keywords.

And step 506, determining the characteristic collection features matched with the user feature data from the target feature material library based on the user identification.

Specifically, the user identifiers are different, and the characteristic collection features determined from the target feature material library are not necessarily the same. After determining a target feature material library corresponding to the attribute keywords, the digital stock generation system determines characteristic stock features matched with the user feature data from the target feature material library based on the user identification.

In the embodiment, the attribute model is arranged in the digital stock generation system, so that the attribute keywords corresponding to the user characteristic data can be rapidly and accurately determined, and the target characteristic stock is determined based on the attribute keywords, so that the characteristic stock characteristics selected from the stock can be ensured to be characteristic stock characteristics matched with the specific colors of the user, and the service coverage of the target digital stock is effectively enlarged.

Further, in one embodiment, as shown in fig. 6, determining, based on the user identification, a feature collection feature matching the user feature data from the target feature material library includes:

step 602, determining the identification level of the user identification according to the user identification.

The identification level of the user identification may be considered as the level of the user in the banking system. The user grades are different, and the rights possessed by the users are also different.

Specifically, the digital collection generating system calls a preset grade mapping table in the data storage library according to the obtained user identification, and searches and determines an identification grade corresponding to the user identification from the preset grade mapping table.

Step 604, determining a candidate material list corresponding to the identification level from the target feature material library based on the identification level.

The target digital stock has a certain collection and circulation value as the real stock created in the bank reality, so that the composition characteristics of the digital stock can be related to the grade of the stock owner when the target digital stock is generated. When a designer adds materials for the feature material library, grade authorities can be set for each material, the identification grades corresponding to the user identifications are different, and even if the attributes are the same, the candidate feature materials which can be selected are different.

Specifically, the digital collection generation system matches the determined identification level with the level authority of each feature material in the target feature material library, and generates a candidate feature material list according to candidate feature materials which can be used by the identification level obtained by matching.

And step 606, screening out the characteristic collection features matched with the user feature data from the candidate material list according to a preset screening rule.

The preset screening rules are rules preset for screening feature collection features meeting requirements. The preset screening rules can be determined according to the actual requirements of the user. For example, if the user is conscious of the timeliness of the material in the digital collection, the preset filtering rule may be determined as the filtering rule of the latest updated material. If the user is conscious of the user's popularity of the digital collection, the preset screening rule can be determined to be the screening rule of the material with highest popularity.

Specifically, after the candidate material list is determined, the digital stock generation system screens out characteristic stock features matched with the user feature data from the candidate material list according to a preset screening rule.

In the above embodiment, by determining the identification level corresponding to the user identification and selecting the feature collection feature matched with the user feature data according to the identification level, the collection circulation value of the target digital collection can be further ensured, and the virtual and real gap is opened.

The digital collection is a virtual digital product generated by virtue of the meta universe, and the display of the digital collection is a necessary means for reflecting the collection value of the digital collection and assisting better circulation of the digital collection.

In some embodiments, as shown in fig. 7, the digital collection generation method further includes:

step 702, determining a display address of the target digital collection in response to the display instruction of the target digital collection.

The display address of the target digital stock is address information for specifically displaying the digital stock to a user. It will be appreciated that the display address of the target digital collection may be the user terminal of the owner of the target digital collection. The target digital collection owner triggers a display instruction for generating the target digital collection, and instructs the digital collection generation system to display the target digital collection to the user on the user terminal. The display address of the target digital collection can also be a display address set by a bank, for example, in order to enable a user to watch the target digital collection matched with the target digital collection better, the bank can generate a display instruction according to a user request to instruct the digital collection generation system to display the target digital collection to the user at the display address set by the bank. It will be appreciated that the specific presentation format will vary from one terminal device to another that presents the address.

Specifically, the digital collection generation system determines a display address of the target digital collection from the display instruction in response to the display instruction of the target digital collection.

Step 704, generating a target collection summary according to the target digital collection.

The target collection summary is text information for reflecting collection design information of the target digital collection. Through the summary of the target collection, the user can know specific information such as the generation reason, design inspiration, collection description and the like of the target digital collection.

Specifically, the digital collection generation system generates a corresponding digital collection summary by using natural language processing on collection information data used for generating a target digital collection and feature data of the target digital collection specifically generated according to the generated target digital collection.

And step 706, displaying the target collection summary and the target digital collection at the display address in an augmented reality mode.

Among them, the augmented reality method is a method of displaying a target digital collection by an augmented reality (Augmented Reality, AR) technique. Is a technology for combining real world and virtual information based on computer real-time calculation and multi-sensor fusion. The augmented reality display mode is usually implemented by using a specific display terminal, so that digital collection display effects with different angles can be provided for users, for example, when the display address is the terminal address of the digital collection owner, the digital collection owner can display the collection through the terminal of the AR glasses, for example. When the display address is the terminal address of the bank, the bank can display the collection through an AR display screen, for example.

Specifically, after obtaining the summary of the target collection, the digital collection generation system blends the summary of the target collection into a display page of the target digital collection in an augmented reality mode, sends the processed display page to a display address, and displays the target digital collection to a user.

In one embodiment, the digital collection generation system can generate a display model of the target digital collection by using a video modeling mode to obtain a display page of the target digital collection, and the display page of the target digital collection can display the target digital collection from different angles and can display a summary of the target digital collection in a carousel mode so as to facilitate understanding of a user on the target digital collection.

In the embodiment, the target collection summary is generated and merged into the display page of the target digital collection, and the display page is sent to the display address for display through the augmented reality method, so that a user can comprehensively know the target digital collection matched with the characteristics of the user, and the circulation convenience of the target digital collection is further effectively improved.

In one embodiment, as shown in fig. 8, there is provided a digital collection generation method, which specifically includes the steps of:

Firstly, a banking staff triggers and generates a digital collection generation request on a meta-universe platform, wherein the digital collection generation request carries collection information data and user identification uploaded by the banking staff. It can be understood that the collection information data may be information data such as a collection name, description, picture, or video of the target digital collection to be generated.

The digital collection generation system receives the digital collection generation request, determines a data analysis method required for carrying out data analysis on the collection information data according to the data type of the collection information data, and carries out data analysis on the collection information data based on the data analysis method to obtain the basic structure characteristics of the target digital collection to be generated.

And simultaneously, acquiring user characteristic data corresponding to the user identifier according to the user identifier, inputting the user characteristic data into a preset attribute model for attribute extraction operation, and acquiring attribute keywords corresponding to the user characteristic data. And determining a target feature material library corresponding to the attribute keywords according to the attribute keywords, determining the identification level of the user identification based on the user identification, determining a candidate material list corresponding to the identification level from the target feature material library according to the identification level, and screening out the characteristic collection features matched with the user feature data from the candidate material list according to a preset screening rule.

And the digital collection generation system generates a target digital collection according to the obtained basic structure characteristics and the characteristic collection characteristics. And setting a unique collection identification for the target digital collection according to the user identification, and storing the target digital collection in a preset blockchain storage area.

When the target digital collection needs to be displayed to the user, banking staff or the user can trigger in the meta universe to generate a display instruction of the target digital collection, and the display instruction needs to carry a display address of the target digital collection. The digital collection generation system responds to the display instruction of the target digital collection, determines the display address of the target digital collection, then generates a target collection summary according to the target digital collection, generates a display page from the target collection summary and the target digital collection in an augmented reality mode, sends the display page to the display address, and displays the target digital collection to a user.

According to the digital collection generation method, the digital collections of the type can be quickly generated by inputting the information such as the name, description, pictures or videos of the products, and each collection has unique mark and ownership information. Compared with the traditional collection, the digital collection generated by the method has the advantages of high release speed, quick circulation, wide coverage of users and the like.

It should be understood that, although the steps in the flowcharts related to the embodiments described above are sequentially shown as indicated by arrows, these steps are not necessarily sequentially performed in the order indicated by the arrows. The steps are not strictly limited to the order of execution unless explicitly recited herein, and the steps may be executed in other orders. Moreover, at least some of the steps in the flowcharts described in the above embodiments may include a plurality of steps or a plurality of stages, which are not necessarily performed at the same time, but may be performed at different times, and the order of the steps or stages is not necessarily performed sequentially, but may be performed alternately or alternately with at least some of the other steps or stages.

Based on the same inventive concept, the embodiment of the application also provides a digital collection generation device for realizing the digital collection generation method. The implementation of the solution provided by the device is similar to the implementation described in the above method, so the specific limitation in the embodiments of the device for generating digital collection provided below may refer to the limitation of the method for generating digital collection hereinabove, and will not be repeated herein.

In one embodiment, as shown in fig. 9, there is provided a digital collection generation apparatus 900, including: a request receiving module 901, a data acquiring module 902, a collection generating module 903 and a storage module 904, wherein:

the request receiving module 901 is configured to receive a digital collection generation request triggered by a virtual target in the meta-universe, where the digital collection generation request carries collection information data and a user identifier; the user identification is the user identification of the virtual user in the meta-universe.

The data obtaining module 902 is configured to obtain user feature data corresponding to the user identifier according to the user identifier.

The collection generation module 903 is configured to generate a target digital collection based on collection information data and user feature data.

And the storage module 904 is configured to set a collection identifier for the target digital collection according to the user identifier, and store the target digital collection in a preset blockchain storage area.

According to the digital collection generation device, after the digital collection generation request triggered by the virtual target in the meta-universe is received, user characteristic data corresponding to the user identification is obtained according to the user identification of the virtual user in the meta-universe carried in the digital collection generation request, and the user characteristic data reflects the user characteristics to a certain extent. And generating the target digital collection in the meta universe based on the collection information data carried in the request and the user characteristic data. Because the dimension of the user characteristics is considered when the target digital collection is generated, the target digital collection can be better matched with the user characteristics, and the collection interest of the user is improved. The target digital collection identification is set according to the user identification, the target digital collection is stored in a preset blockchain storage area, and the value of the virtual digital collection in the meta universe is guaranteed, so that the virtual and real separation is broken through, the service coverage can be enlarged while the distribution efficiency of the digital collection is improved, and the circulation convenience of the collection is further improved.

In one embodiment, the collection generation module is further to: analyzing the collection information data to obtain the basic structural characteristics of the target digital collection to be generated; determining characteristic collection characteristics matched with the user characteristic data according to the user characteristic data; and combining the basic structure characteristic and the characteristic collection characteristic through a preset collection generation method to generate the target digital collection.

In one embodiment, the collection generation module is further to: determining a data analysis method according to the data type of the collection information data; and carrying out data analysis on the collection information data based on the data analysis method to obtain the basic structural characteristics of the target digital collection to be generated.

In one embodiment, the collection generation module is further to: inputting the user characteristic data into a preset attribute model to perform attribute extraction operation, and determining attribute keywords corresponding to the user characteristic data; determining a target feature material library corresponding to the attribute keywords according to the attribute keywords; and determining the characteristic collection characteristics matched with the user characteristic data from the target characteristic material library based on the user identification.

In one embodiment, the collection generation module is further to: determining the identification level of the user identification according to the user identification; determining a candidate material list corresponding to the identification level from the target characteristic material library based on the identification level; and screening out the characteristic collection features matched with the user feature data from the candidate material list according to a preset screening rule.

In one embodiment, the digital collection generating apparatus further includes: the display module is used for responding to the display instruction of the target digital collection and determining the display address of the target digital collection; generating a target collection summary according to the target digital collection; and displaying the summary of the target collection and the target digital collection at the display address in an augmented reality mode.

The above-described individual modules in the digital stock generation apparatus may be implemented in whole or in part by software, hardware, or a combination thereof. The above modules may be embedded in hardware or may be independent of a processor in the computer device, or may be stored in software in a memory in the computer device, so that the processor may call and execute operations corresponding to the above modules.

In one embodiment, a computer device is provided, which may be a server integrated with a digital collection generation system, and the internal structure diagram of which may be as shown in fig. 10. The computer device includes a processor, a memory, and a network interface connected by a system bus. Wherein the processor of the computer device is configured to provide computing and control capabilities. The memory of the computer device includes a non-volatile storage medium and an internal memory. The non-volatile storage medium stores an operating system, computer programs, and a database. The internal memory provides an environment for the operation of the operating system and computer programs in the non-volatile storage media. The database of the computer device is used for storing collection information data, user identification, user characteristic data, target digital collections and other data. The network interface of the computer device is used for communicating with an external terminal through a network connection. The computer program is executed by a processor to implement a digital collection generation method.

It will be appreciated by those skilled in the art that the structure shown in FIG. 10 is merely a block diagram of some of the structures associated with the present inventive arrangements and is not limiting of the computer device to which the present inventive arrangements may be applied, and that a particular computer device may include more or fewer components than shown, or may combine some of the components, or have a different arrangement of components.

In one embodiment, a computer device is provided comprising a memory and a processor, the memory having stored therein a computer program, the processor when executing the computer program performing the steps of:

receiving a digital collection generation request triggered by a virtual target in the meta-universe, wherein the digital collection generation request carries collection information data and a user identifier; the user identification is the user identification of the virtual user in the meta universe;

generating a target digital collection based on collection information data and user feature data;

In one embodiment, the processor when executing the computer program further performs the steps of:

Analyzing the collection information data to obtain the basic structural characteristics of the target digital collection to be generated;

determining characteristic collection characteristics matched with the user characteristic data according to the user characteristic data;

and carrying out data analysis on the collection information data based on the data analysis method to obtain the basic structural characteristics of the target digital collection to be generated.

inputting the user characteristic data into a preset attribute model to perform attribute extraction operation, and determining attribute keywords corresponding to the user characteristic data;

and determining the characteristic collection characteristics matched with the user characteristic data from the target characteristic material library based on the user identification.

Determining the identification level of the user identification according to the user identification;

and screening out the characteristic collection features matched with the user feature data from the candidate material list according to a preset screening rule.

responding to a display instruction of the target digital collection, and determining a display address of the target digital collection;

and displaying the summary of the target collection and the target digital collection at the display address in an augmented reality mode.

In one embodiment, a computer readable storage medium is provided having a computer program stored thereon, which when executed by a processor, performs the steps of:

In one embodiment, the computer program when executed by the processor further performs the steps of:

In one embodiment, a computer program product is provided comprising a computer program which, when executed by a processor, performs the steps of:

The user information (including but not limited to user equipment information, user personal information, etc.) and the data (including but not limited to data for analysis, stored data, presented data, etc.) related to the present application are information and data authorized by the user or sufficiently authorized by each party.

Those skilled in the art will appreciate that implementing all or part of the above described methods may be accomplished by way of a computer program stored on a non-transitory computer readable storage medium, which when executed, may comprise the steps of the embodiments of the methods described above. Any reference to memory, database, or other medium used in embodiments provided herein may include at least one of non-volatile and volatile memory. The nonvolatile Memory may include Read-Only Memory (ROM), magnetic tape, floppy disk, flash Memory, optical Memory, high density embedded nonvolatile Memory, resistive random access Memory (ReRAM), magnetic random access Memory (Magnetoresistive Random Access Memory, MRAM), ferroelectric Memory (Ferroelectric Random Access Memory, FRAM), phase change Memory (Phase Change Memory, PCM), graphene Memory, and the like. Volatile memory can include random access memory (Random Access Memory, RAM) or external cache memory, and the like. By way of illustration, and not limitation, RAM can be in the form of a variety of forms, such as static random access memory (Static Random Access Memory, SRAM) or dynamic random access memory (Dynamic Random Access Memory, DRAM), and the like. The databases referred to in the embodiments provided herein may include at least one of a relational database and a non-relational database. The non-relational database may include, but is not limited to, a blockchain-based distributed database, and the like. The processor referred to in the embodiments provided in the present application may be a general-purpose processor, a central processing unit, a graphics processor, a digital signal processor, a programmable logic unit, a data processing logic unit based on quantum computing, or the like, but is not limited thereto.

The technical features of the above embodiments may be arbitrarily combined, and all possible combinations of the technical features in the above embodiments are not described for brevity of description, however, as long as there is no contradiction between the combinations of the technical features, they should be considered as the scope of the description.

The foregoing examples illustrate only a few embodiments of the application and are described in detail herein without thereby limiting the scope of the application. It should be noted that it will be apparent to those skilled in the art that several variations and modifications can be made without departing from the spirit of the application, which are all within the scope of the application. Accordingly, the scope of the application should be assessed as that of the appended claims.

Claims

1. A digital collection generation method, the method comprising:

2. The method of claim 1, wherein the generating a target digital collection based on the collection information data and the user characteristic data comprises:

3. The method of claim 2, wherein the performing data analysis on the collection information data to obtain the infrastructure features of the target digital collection comprises:

4. The method of claim 2, wherein the determining, from the user feature data, a featured stock feature that matches the user feature data comprises:

5. The method of claim 4, wherein the determining, based on the user identification, a feature collection feature from the target feature library that matches the user feature data comprises:

6. The method according to any one of claims 1 to 5, further comprising:

7. A digital stock generation device, the device comprising:

8. A computer device comprising a memory and a processor, the memory storing a computer program, characterized in that the processor implements the steps of the method of any of claims 1 to 6 when the computer program is executed.

9. A computer readable storage medium, on which a computer program is stored, characterized in that the computer program, when being executed by a processor, implements the steps of the method of any of claims 1 to 6.

10. A computer program product comprising a computer program, characterized in that the computer program, when being executed by a processor, implements the steps of the method of any of claims 1 to 6.