An online editing method and system for digital resources

Abstract

The present disclosure relates to a method and system for online editing of digital resources, and relates to the field of computer technology; in the scenario of online editing of digital resources, an AI agent determines recommended resource content according to the resource information of the resource to be edited, the user identification information, and the hardware information of the electronic device, and further presents the recommended resource content and the resource to be edited to the user together. For the user, the recommended resource content can provide the user with resource editing ideas, and the user can use the recommended resource content according to needs to perform online editing operations on the resources. Therefore, this technical solution can provide the user with resource editing ideas, improve the intelligence of online editing of digital resources, and further improve the user's online editing experience of digital resources.

Description

Technical Field

[0001] The present disclosure relates to the field of computer technology, and in particular, to a method and system for online editing of digital resources. Background Art

[0002] Digital resources refer to information resources stored, processed, and disseminated in digital form, including various forms such as text, images, audio, and video, and are accessed and used through digital devices such as computers and networks. It is the sum of information resources published, stored, and utilized in digital form formed by the mutual integration of computer technology, communication technology, and multimedia technology.

[0003] Online editing of digital resources is one of the important functions of modern digital resource management, which allows users to perform real-time editing, collaboration, and management on various digital resources.

[0004] Currently, in the scenario of online editing of digital resources, although various functions can be supported for editing, it cannot provide users with editing ideas, has poor intelligence, and thus poor user experience. Summary of the Invention

[0005] The purpose of the present disclosure is to provide a method and system for online editing of digital resources, which can provide users with resource editing ideas, improve the intelligence of online editing of digital resources, and thus improve the user experience of online editing of digital resources.

[0006] To achieve the above purpose, in a first aspect, the present disclosure provides a method for online editing of digital resources, including: displaying a first resource editing interface on an electronic device, where the first resource editing interface is a display interface of a resource to be edited; obtaining user identification information, resource information of the resource to be edited, and hardware information of the electronic device; determining recommended resource content by an AI agent according to the resource information, the user identification information, and the hardware information; in response to detecting a usage requirement for the recommended resource content, displaying a second resource editing interface on the electronic device, where the second resource editing interface is a display interface of the resource to be edited and the recommended resource content; and in response to detecting an editing operation of the user on the second resource editing interface, displaying the edited resource according to the editing operation.

[0007] Optionally, the displaying a first resource editing interface on an electronic device includes: in response to detecting a selection operation of a target resource among multiple preset resources by the user, displaying the first resource editing interface on the electronic device, where the resource to be edited is the target resource; or, in response to detecting a resource upload operation of the user, displaying the first resource editing interface on the electronic device, where the resource to be edited is the resource uploaded by the user.

[0008] Optionally, the determination of the recommended resource content by the AI agent according to the resource information, the user identification information, and the hardware information includes: determining, by the AI agent according to the user identification information, user evaluation information for characterizing the user's resource editing ability; determining, by the AI agent according to the hardware information, hardware evaluation information for characterizing the resource content compatibility ability of the electronic device; and retrieving, by the AI agent according to the resource information, the user evaluation information, and the hardware evaluation information, in a preset resource content library to obtain the recommended resource content.

[0009] Optionally, the determination of the user evaluation information by the AI agent according to the user identification information includes: retrieving, by the AI agent, according to the user identification information in a preset user database, the preset user database including multiple registered user identification information and the historical resource editing information respectively corresponding to the multiple registered user identification information; if the AI agent retrieves, in the preset user database, a registered user identification information identical to the user identification information, determining the user evaluation information according to the historical resource editing information corresponding to the registered user identification information; if the AI agent does not retrieve, in the preset user database, a registered user identification information identical to the user identification information, determining reference user evaluation information according to the historical resource editing information respectively corresponding to the multiple registered user identification information, and determining the user evaluation information according to the reference user evaluation information and the preset user evaluation information.

[0010] Optionally, the preset resource content library includes various resource contents, the resource information and the resource content evaluation information respectively corresponding to different resource contents, the resource content evaluation information being used to characterize the secondary editing difficulty of the resource content, and the retrieval, by the AI agent according to the resource information, the user evaluation information, and the hardware evaluation information, in the preset resource content library to obtain the recommended resource content includes: retrieving, by the AI agent, according to the resource information in the preset resource content library to determine candidate resource contents, the resource information corresponding to the candidate resource contents matching the resource information; and determining, by the AI agent, from the candidate resource contents the recommended resource content according to the resource content evaluation information, the user evaluation information, and the hardware evaluation information corresponding to the candidate resource contents, the resource content evaluation information corresponding to the recommended resource content matching the user evaluation information and the hardware evaluation information.

[0011] Optionally, the AI intelligent agent is an internet-connected intelligent agent, and the online editing method further includes: obtaining the payment information of the user for resource editing; judging, by the AI intelligent agent according to the payment information, whether the recommended resource content matches the payment information; in the case where the recommended resource content does not match the payment information, searching, by the AI intelligent agent, in the internet according to the recommended resource content to obtain search resource content, and expanding the recommended resource content according to the search resource content to obtain the expanded recommended resource content, wherein the expansion of the recommended resource content includes at least one of the following: expansion of the quantity of the recommended resource content, expansion of the type of the recommended resource content, and expansion of the quality of the recommended resource content.

[0012] Optionally, the first resource editing interface includes an AI intelligent agent control and an editing function option control. Responding to detecting the usage requirement of the recommended resource content, displaying a second resource editing interface on the electronic device includes: responding to detecting a triggering operation of the user on the AI intelligent agent control, and displaying a second resource editing interface on the electronic device; or, responding to not detecting a triggering operation of the user on the editing function option control within a first preset duration, displaying a preset reminder message in the first resource editing interface, where the preset reminder message is used to indicate to turn on the resource editing assistance function after a second preset duration; responding to detecting an operation of the user on the preset reminder message, and / or not detecting an operation of the user on the preset reminder message within the second preset duration, and displaying a second resource editing interface on the electronic device.

[0013] Optionally, the second resource editing interface includes a storage control. The online editing method further includes: responding to detecting a triggering operation of the user on the storage control, determining, by the AI intelligent agent, storage information according to the content of the resource to be edited, the content of the resource to be stored, and the recommended resource content, where the storage information is used to represent the storage method and storage path of the resource to be stored, and the storage method includes at least one of direct storage, encrypted storage, and compressed storage; displaying the storage information; and responding to detecting a confirmation operation of the user on the target storage information of the storage information, and storing the resource to be stored according to the target storage information.

[0014] Optionally, a sharing control is included in the second resource editing interface, and the online editing method further includes: in response to detecting a triggering operation by the user on the sharing control, determining, by the AI agent, sharing information based on the content of the resource to be edited, the content of the resource to be shared, and the content of the recommended resource, where the sharing information is used to characterize the sharing method, sharing validity period, content to be shared, and secondary sharing permission of the resource to be shared, and wherein the sharing method includes at least one of direct sharing, sharing after encryption, and sharing after compression; displaying the sharing information; and in response to detecting a confirmation operation by the user on the target sharing information of the sharing information, sharing the resource to be shared according to the target sharing information.

[0015] In a second aspect, the present disclosure provides an online editing system for digital resources, including: a display module for displaying a first resource editing interface on an electronic device, where the first resource editing interface is a display interface of the resource to be edited; an acquisition module for acquiring user identification information, resource information of the resource to be edited, and hardware information of the electronic device; a determination module for determining, by the AI agent, content of a recommended resource based on the resource information, the user identification information, and the hardware information; the display module is further configured to, in response to detecting a usage requirement for the content of the recommended resource, display a second resource editing interface on the electronic device, where the second resource editing interface is a display interface of the resource to be edited and the content of the recommended resource; and in response to detecting an editing operation by the user on the second resource editing interface, display the edited resource according to the editing operation.

[0016] Through the above technical solution, in the scenario of online editing of digital resources, the AI agent determines the content of the recommended resource according to the resource information of the resource to be edited, the user identification information, and the hardware information of the electronic device, and further presents the content of the recommended resource and the resource to be edited to the user together. For the user, the content of the recommended resource can provide creative ideas for resource editing, and the user can use the content of the recommended resource according to needs to perform online editing operations on the resource. Therefore, this technical solution can provide creative ideas for resource editing for the user, improve the intelligence of online editing of digital resources, and further improve the user's online editing experience of digital resources.

[0017] Other features and advantages of the present disclosure will be described in detail in the subsequent specific implementation section. Description of the Drawings

[0018] The drawings are used to provide a further understanding of the present disclosure and constitute a part of the specification. They are used together with the following specific implementation to explain the present disclosure, but do not constitute a limitation to the present disclosure. In the drawings:

[0019] Figure 1It is a schematic diagram of an application scenario for online editing of digital resources shown according to an exemplary embodiment.

[0020] Figure 2 It is a flowchart of a method for online editing of digital resources shown according to an exemplary embodiment.

[0021] Figure 3 It is an example diagram of a first resource editing interface shown according to an exemplary embodiment.

[0022] Figure 4 It is an example diagram of a second resource editing interface shown according to an exemplary embodiment.

[0023] Figure 5 It is a block diagram of an online editing system for digital resources shown according to an exemplary embodiment.

[0024] Figure 6 It is a block diagram of an electronic device shown according to an exemplary embodiment. Detailed implementation manners

[0025] The following will detail the specific implementation manners of the present disclosure with reference to the accompanying drawings. It should be understood that the specific implementation manners described herein are only for explaining and interpreting the present disclosure, and are not used to limit the present disclosure.

[0026] Digital resources refer to information resources stored, processed, and disseminated in digital form, including various forms such as text, images, audio, and video, and are accessed and used through digital devices such as computers and networks. It is the sum of information resources published, accessed, and utilized in digital form formed by the mutual integration of computer technology, communication technology, and multimedia technology.

[0027] Online editing of digital resources is one of the important functions of modern digital resource management, which allows users to perform real-time editing, collaboration, and management on various digital resources.

[0028] Currently, in the scenario of online editing of digital resources, although various editing functions can be supported, it cannot provide editing creativity for users, has poor intelligence, and thus poor user experience.

[0029] For example, in some editing scenarios of online documents, users can edit online documents and various editing functions can be provided for users, such as: copy, reference, paste, etc. However, in this editing scenario, it does not intelligently provide editing creativity for users, such as: what content can be filled in the document, etc., resulting in poor intelligence in the online editing of resources and poor user experience.

[0030] In some online editing scenarios where creativity is more important, it especially affects the user experience.

[0031] Based on this, the embodiments of the present disclosure provide a technical solution. In the online editing scenario of digital resources, an AI agent determines recommended resource content according to the resource information of the resource to be edited, user identification information, and the hardware information of the electronic device, and further presents the recommended resource content and the resource to be edited to the user together. For the user, the recommended resource content can provide resource editing ideas for the user, and the user can use the recommended resource content according to needs to perform online editing operations on the resources.

[0032] Therefore, this technical solution can provide resource editing ideas for users, improve the intelligence of online editing of digital resources, and further improve the user experience of online editing of digital resources.

[0033] Figure 1 is a schematic diagram of an application scenario for online editing of digital resources shown according to an exemplary embodiment, as Figure 1 shown, this application scenario includes a front end and a back end communicatively connected to the front end (connected through a network in the figure).

[0034] In some embodiments, the front end can be used as a human-computer interaction end to implement various human-computer interaction functions. The back end can be used as a data processing end to provide various data supports for the human-computer interaction functions.

[0035] In some embodiments, the back end can be a server, and the front end can be an electronic device such as a mobile phone or a computer.

[0036] In some embodiments, the forms of the front-end services for digital resource editing can include: application programs, browsers, applets, etc., which are not limited herein.

[0037] In some embodiments, digital resources can include: various forms such as text, images, audio, video, etc., which are not limited herein.

[0038] In the embodiments of the present disclosure, the AI agent is also applied. Regarding the AI agent, it is an intelligent system that can perceive the environment, make autonomous decisions, and take actions to achieve specific goals. It integrates technologies such as large language models, reinforcement learning, and multi-modal interactions, and can independently complete tasks in complex scenarios, and is regarded as an advanced form of artificial intelligence technology.

[0039] The AI agent has the following characteristics: Autonomy: It can operate independently without manual intervention. Perception ability: It obtains external information through sensors or data interfaces, such as voice, images, or text. Decision-making ability: It analyzes the obtained information and makes decisions. Execution ability: It takes actual actions according to the decision results. Adaptive ability: It optimizes its behavior through learning to adapt to environmental changes. Interaction ability: It can interact naturally with users or other systems.

[0040] Therefore, by providing resource editing ideas for users through the AI agent, the intelligence of online editing of digital resources is relatively high.

[0041] Figure 2 is a flowchart of an online editing method for digital resources shown according to an exemplary embodiment. This online editing method can be applied to Figure 1 the application scenario shown. Some of the steps can be jointly implemented by the front end and the back end, or can be implemented only by the front end. This online editing method can include the following steps:

[0042] Step S21: Display a first resource editing interface on the electronic device. The first resource editing interface is a display interface for the resource to be edited.

[0043] Step S22: Obtain the user identification information, the resource information of the resource to be edited, and the hardware information of the electronic device.

[0044] Step S23: Determine the recommended resource content through the AI agent according to the resource information, the user identification information, and the hardware information.

[0045] Step S24: In response to detecting the usage requirement of the recommended resource content, display a second resource editing interface on the electronic device. The second resource editing interface is a display interface for the resource to be edited and the recommended resource content.

[0046] Step S25: In response to detecting the editing operation of the user on the second resource editing interface, display the edited resource according to the editing operation.

[0047] In step S21, the electronic device can be regarded as Figure 1 the front end in

[0048] In the embodiments of the present disclosure, the AI agent can be expressed as: Agent (intelligent agent) = LLM (large language model) + Planning (planning) + Memory (memory) + Tools (tools).

[0049] This formula shows that the AI agent not only depends on the language understanding ability, but also requires planning, memory, and tool invocation abilities to complete complex tasks.

[0050] Regarding the large language model, it can include the following key components:

[0051] Word embedding: Word embedding is a technique that maps words to a continuous vector space and is used to capture the semantic relationships between words. Common methods include Word2Vec and GloVe:

[0052] Word2Vec: CBOW (Continuous Bag of Words): Predict the center word given the context. Skip-Gram: Predict the context given the center word. Training objective: where T is the size of the training data, and w t is the word at time step t.

[0053] GloVe: Learn word embeddings through a matrix factorization task. Training objective: where X is the word vector matrix, Y is the context vector matrix, f ( u , v ) is the similarity of the word pair ( u , v ).

[0054] Self-Attention: Self-Attention is the core of the Transformer architecture, allowing the model to establish long-range dependencies between different time steps. The calculation formula is: where Q is the query vector, K is the key vector, V is the value vector, d k is the dimension of the key vector.

[0055] Transformer Architecture: Transformer is the core architecture of large language models, achieving efficient sequence modeling through self-attention mechanism and encoder-decoder structure. Main components:

[0056] Multi-Head Attention: Parallel self-attention mechanisms, allowing the model to simultaneously focus on multiple different contexts.

[0057] Positional Encoding: Used to represent the position information in the sequence. Since Transformer has no sequence structure, positional encoding is needed to capture the sequence structure.

[0058] Residual Connection: Retain the input before each layer to accelerate the training process.

[0059] Layer Normalization: Normalize the output of the model to reduce overfitting.

[0060] These technologies and formulas are the basis of large language models. However, actual large language models (such as GPT, LLaMA, etc.) will perform large-scale pre-training on this basis and improve performance through complex optimization and fine-tuning.

[0061] Therefore, in the embodiments of the present disclosure, by pre-training the accessed large model and integrating it in the form of an AI intelligent agent, technical support for the technical solutions of the embodiments of the present disclosure is provided.

[0062] In some embodiments, the first resource editing interface may be an interface displayed upon triggering by a user's operation. Under different triggering manners of the operation, the source of the resource to be edited may also be different.

[0063] Therefore, as an alternative implementation manner, step S21 includes: in response to detecting a user's selection operation on a target resource among multiple preset resources, displaying a first resource editing interface on the electronic device, and the resource to be edited is the target resource.

[0064] In some embodiments, taking an application as an example, the user can first register / login in the application through personal information, and then a resource selection interface can be displayed on the electronic device. The resource selection interface includes multiple preset resources, and the user can select a specified resource among the multiple resources. Further, a first resource editing interface can be displayed on the electronic device. In this scenario, the resource to be edited is the target resource.

[0065] As another alternative implementation manner, step S21 includes: in response to detecting a user's resource upload operation, displaying a first resource editing interface on the electronic device, and the resource to be edited is the resource uploaded by the user.

[0066] In some embodiments, taking an application as an example, the user can first register / login in the application through personal information, and then a resource selection interface can be displayed on the electronic device. The resource selection interface may include a resource upload control, and the user can trigger a resource upload operation by operating the resource upload control. Further, a first resource editing interface can be displayed on the electronic device. In this scenario, the resource to be edited is the resource uploaded by the user.

[0067] In addition to the above two implementation manners, in more digital resource online editing scenarios, there can be more triggering manners for the resource editing interface.

[0068] Exemplarily, in a social application, users can send digital resources to each other, such as documents. At this time, the user can click on the digital resource in the chat interface, and then the electronic device can display the digital resource. Correspondingly, an editing control can also be displayed in this interface. By operating the editing control, the user can trigger the electronic device to display the first resource editing interface. In this scenario, the resource to be edited is the resource sent by other users to the current user.

[0069] It can be understood that there can be multiple scenarios for online editing of digital resources, and the technical solutions of the embodiments of the present disclosure can be applied to all of them, and no further examples will be given here.

[0070] Figure 3 FIG. is an example diagram of a first resource editing interface shown according to an exemplary embodiment, as Figure 3 shown, on this first resource editing interface, the resource to be edited and at least one editing function option control corresponding to the resource to be edited can be displayed.

[0071] Among them, the editing function option control can correspond to the corresponding editing function. Taking text as an example, it can involve functions such as deletion, insertion, and modification. Taking video as an example, it can involve functions related to video frame editing. Taking audio as an example, it can involve functions related to audio frames, etc.

[0072] According to the different types of the resource to be edited, the resource to be edited and the editing function option control can adopt different display forms or arrangement methods on the first resource editing interface. Taking Figure 3 as an example, the resource to be edited is displayed on the left, and the editing function option control is displayed on the right.

[0073] In step S22, the user identification information, the resource information of the resource to be edited, and the hardware information of the electronic device are obtained.

[0074] In some embodiments, the user identification information can be used as the identification of the user, and it can be a kind of identity identification information, such as: the user's account number, password, and user name, etc. This user identification information can be directly obtained.

[0075] In some embodiments, the resource information of the resource to be edited can characterize the situation of the resource, and it can include: resource type, resource description, resource name, resource size, etc. Among them, the resource type, such as: text, picture, video, audio, etc.; the resource description can describe the content involved in the resource, such as: scenery, humanities, work-related, etc.; the resource name can be used as the identification information of the resource; the resource size can be described in units such as KB and MB, representing the data volume size of the resource.

[0076] In some embodiments, when obtaining the resource to be edited, the resource information can be determined or obtained.

[0077] In some embodiments, the hardware information of the electronic device can characterize the hardware performance of the electronic device, which may include performance parameters such as hardware type, hardware memory (running memory, etc.), and hardware battery capacity. This hardware information belongs to the inherent information of the electronic device and can be directly obtained.

[0078] Further, in step S23, the AI agent determines the recommended resource content based on the resource information, user identification information, and hardware information.

[0079] In some embodiments, after the electronic device starts the online editing function, the AI agent can be automatically enabled. Thus, the AI agent can actively pull the resource information, user identification information, and hardware information to determine the recommended resource content.

[0080] In some embodiments, regarding the AI agent technology, reference can be made to the mature technologies in the art, and no detailed introduction will be given in the embodiments of the present disclosure.

[0081] As an alternative implementation, step S23 includes: the AI agent determines the user evaluation information based on the user identification information, and the user evaluation information is used to characterize the user's resource editing ability; the AI agent determines the hardware evaluation information based on the hardware information, and the hardware evaluation information is used to characterize the resource content compatibility ability of the electronic device; the AI agent retrieves in the preset resource content library based on the resource information, user evaluation information, and hardware evaluation information to obtain the recommended resource content.

[0082] In this implementation, the AI agent can determine the user evaluation information based on the user identification information, and the user evaluation information can characterize the user's resource editing ability.

[0083] In some embodiments, the AI agent determines the user evaluation information based on the user identification information, including: the AI agent retrieves in the preset user database based on the user identification information, and the preset user database includes multiple registered user identification information and the historical resource editing information respectively corresponding to the multiple registered user identification information; if the AI agent retrieves the registered user identification information that is the same as the user identification information in the preset user database, the user evaluation information is determined according to the historical resource editing information corresponding to the registered user identification information; if the AI agent does not retrieve the registered user identification information that is the same as the user identification information in the preset user database, the reference user evaluation information is determined according to the historical resource editing information respectively corresponding to the multiple registered user identification information, and the user evaluation information is determined according to the reference user evaluation information and the preset user evaluation information.

[0084] In this embodiment, a user database is pre-configured, in which multiple registered user identification information and historical resource editing information corresponding to the multiple registered user identification information can be stored. That is, for an online editing application, the historical resource editing situations of users who have participated in online editing can be recorded.

[0085] Furthermore, when evaluating a user, these information can be referred to for evaluation.

[0086] In some embodiments, using an AI agent to implement information retrieval can improve the efficiency of information retrieval.

[0087] In some embodiments, the AI agent can compare the registered user identification information in the preset user database with the current user identification information. If the same user identification information is retrieved, the user evaluation information can be directly determined according to the historical resource editing information corresponding to the registered user identification information.

[0088] In some embodiments, the historical resource editing information can include: resource type, resource size, resource content description information, etc. According to these information, the complexity, difficulty, etc. of the historical resource editing information can be determined. According to the complexity and difficulty, the user evaluation information can be determined.

[0089] In some embodiments, the user evaluation information can be a resource editing ability score. The higher the score, the stronger the represented ability. Therefore, the relationship between the score, the complexity, the difficulty, etc. of the historical resource editing information can be pre-configured. Based on the pre-configured relationship and specific information, the resource editing ability score can be determined.

[0090] Exemplarily, the resource editing ability score is S, the complexity is A, and the difficulty is B. Then S = Q1×A + Q2×B, where Q1 and Q2 respectively represent the conversion weights of the complexity and difficulty to the resource editing ability score. The conversion weights can be determined by statistical analysis of big data, and the specific values are not limited here.

[0091] In some embodiments, in the case where the same registered user identification information as the user identification information is not retrieved in the preset user database, the historical resource editing information corresponding to multiple registered user identification information can be obtained. Based on these historical resource editing information, a reference user evaluation information is obtained. According to the reference user evaluation information and the preset user evaluation information, the user evaluation information is determined.

[0092] In some embodiments, multiple historical resource editing information corresponding to registered user identification information can be used to determine various information such as complexity and difficulty. Then, these various information such as complexity and difficulty are averaged to obtain average complexity and average difficulty information. Finally, the average complexity and average difficulty are converted into resource editing ability scores with reference to the foregoing embodiments, so as to obtain reference user evaluation information.

[0093] In some embodiments, the preset user evaluation information can be the lowest resource editing ability score with resource editing ability pre-configured. By way of example, assuming that the resource editing ability score is a value between 0 and 100, the preset user evaluation information can be a value between 30 and 50.

[0094] In some embodiments, when the number of registered user identification information is large, the reference user evaluation information has a higher priority. When the number of registered user identification information is small, the preset user evaluation information has a higher priority. Furthermore, the user evaluation information with a higher priority is used as the final user evaluation information. Alternatively, the reference user evaluation information and the preset user evaluation information are weighted and averaged to obtain the final user evaluation information.

[0095] In some embodiments, the AI agent determines hardware evaluation information based on hardware information, and the hardware evaluation information is used to characterize the resource content compatibility ability of the electronic device.

[0096] In some embodiments, the hardware evaluation information can be a compatibility ability score. The evaluation of hardware belongs to a relatively mature technology in this field and will not be introduced in detail here. By way of example, the larger the hardware running memory, the stronger the resource content compatibility ability, which allows editing more resource content and inserting richer resource content, etc., so the compatibility ability score is also higher.

[0097] Furthermore, the AI agent retrieves in a preset resource content library based on resource information, user evaluation information, and hardware evaluation information to obtain recommended resource content.

[0098] In some embodiments, the recommended resource content can be text, pictures, audio, video, etc., and its resource type can be different from that of the resource to be edited. By way of example, in a text resource, picture resource content can also be inserted.

[0099] As an alternative implementation, the preset resource content library includes various resource contents, and the resource information and resource content evaluation information respectively corresponding to different resource contents. Regarding the resource content evaluation information, it can characterize the secondary editing difficulty of the resource content.

[0100] In some embodiments, the difficulty of secondary editing of resource content represents the difficulty for users to use it for resource editing. Therefore, when recommending resource content to users, the difficulty of secondary editing needs to be considered.

[0101] For example, for video-based resource content, its secondary editing requires users to have video editing capabilities, so its secondary editing difficulty is relatively high. For text-based resource content, its secondary editing does not require users to have strong editing capabilities. For example, it can be directly copied into existing resources, so the secondary editing difficulty is relatively low.

[0102] Therefore, when setting up a resource content library, various resource contents can be searched from various digital resources in big data. These resource contents correspond to corresponding resource information. Then, the secondary editing difficulty of these various resource contents is evaluated to obtain resource content evaluation information.

[0103] In some embodiments, the evaluation of the secondary editing difficulty can also be achieved through an AI model. It can be pre-trained with a large amount of data so that the AI model has the ability to evaluate the secondary editing difficulty.

[0104] Furthermore, through the AI agent, according to the resource information, user evaluation information, and hardware evaluation information, a search is performed in the preset resource content library to obtain recommended resource content, which may include: through the AI agent, a search is performed in the preset resource content library according to the resource information to determine candidate resource content, and the resource information corresponding to the candidate resource content matches the resource information; through the AI agent, according to the resource content evaluation information, user evaluation information, and hardware evaluation information corresponding to the candidate resource content, the recommended resource content is determined from the candidate resource content, and the resource content evaluation information corresponding to the recommended resource content matches the user evaluation information and hardware evaluation information.

[0105] In this implementation manner, the retrieval ability of the AI agent also needs to be applied to perform a search from the preset resource content library.

[0106] In some embodiments, the resource information corresponding to the candidate resource content matching the resource information may be that the similarity between the resource information corresponding to the candidate resource content and the resource information is higher than the preset similarity.

[0107] In some embodiments, the resource content evaluation information corresponding to the recommended resource content matching the user evaluation information and hardware evaluation information may be that the resource content evaluation information, user evaluation information, and hardware evaluation information satisfy corresponding relationships.

[0108] Exemplarily, the secondary editing difficulty is denoted as M, the user's resource editing ability score is denoted as S, and the hardware compatibility ability score is denoted as N. Then M < f(S, N), where f(S + N) represents a function that converts S and N into the secondary editing difficulty, and this function can be determined by analyzing and statistically processing big data. For example, the higher the resource editing ability score, the higher the secondary editing difficulty; the higher the hardware compatibility ability score, the higher the secondary editing difficulty, etc.

[0109] Thus, through the intelligent retrieval function of the AI agent, the determination of the recommended resource content can be achieved.

[0110] In some embodiments, the AI agent can be an internet-connected agent. This method can further include: obtaining the payment information of the user for resource editing; determining, by the AI agent according to the payment information, whether the recommended resource content matches the payment information; in the case where the recommended resource content does not match the payment information, searching in the internet by the AI agent according to the recommended resource content to obtain the searched resource content, and expanding the recommended resource content according to the searched resource content to obtain the expanded recommended resource content, where the expansion of the recommended resource content includes at least one of the following: the expansion of the quantity of the recommended resource content, the expansion of the type of the recommended resource content, and the expansion of the quality of the recommended resource content.

[0111] In some embodiments, the payment information can be a recharge record, a membership application record, etc. Correspondingly, different payment information can correspond to different recommended resource contents.

[0112] In some embodiments, the process of determining whether the recommended resource content matches the payment information can include: obtaining the quality of the recommended resource content corresponding to different preset payment information, comparing the current quality of the recommended resource content with the preset quality of the recommended resource content corresponding to the current payment information. If the current quality is higher or basically the same, it matches; otherwise, it does not match.

[0113] In some embodiments, the quality of the recommended resource content can be determined by the content richness, content depth, etc. of the recommended resource content, and specific reference can be made to the mature technologies in this field.

[0114] In some embodiments, in the case where the recommended resource content does not match the payment information, the internet search function can be enabled to search in the internet to obtain the searched resource content. Further, the recommended resource content is expanded using the searched resource content to obtain the expanded recommended resource content, where the expansion of the recommended resource content includes at least one of the following: the expansion of the quantity of the recommended resource content, the expansion of the type of the recommended resource content, and the expansion of the quality of the recommended resource content.

[0115] In some embodiments, the expansion of the quantity of recommended resource content may be adding searched resource content to the recommended resource content; the expansion of the type of recommended resource content may be adding the searched resource content corresponding to the resource type not involved therein to the recommended resource content; the expansion of the quality of recommended resource content may be inserting the high-quality resource content in the searched resource content into the existing low-quality recommended resource content. Or, there may be other expansion methods, which are not limited herein.

[0116] After determining the recommended resource content, in step S24, in response to detecting a usage requirement for the recommended resource content, a second resource editing interface is displayed on the electronic device.

[0117] It can be understood that although the recommended resource content is determined, the user may not necessarily have a requirement. Therefore, corresponding display can be performed when a usage requirement is detected, which can avoid affecting user editing.

[0118] As an alternative implementation, the first resource editing interface may include an AI agent control and an editing function option control. Thus, step S24 includes: in response to detecting a trigger operation by the user on the AI agent control, displaying a second resource editing interface on the electronic device; or, in response to not detecting a trigger operation by the user on the editing function option control within a first preset duration, displaying a preset reminder message in the first resource editing interface, where the preset reminder message is used to indicate that a resource editing assistance function will be enabled after a second preset duration; in response to detecting an operation by the user on the preset reminder message, and / or not detecting an operation by the user on the preset reminder message within the second preset duration, displaying a second resource editing interface on the electronic device.

[0119] In this implementation, if the user performs a trigger operation on the AI agent control, such as clicking or long-pressing, etc., the second resource editing interface can be directly displayed.

[0120] Also, if the user does not perform editing for a long time, it indicates that the user may have a recommendation requirement for resource content. At this time, a preset reminder message can be displayed first. For example, the resource editing assistance function will be enabled after XX seconds.

[0121] In some embodiments, the first preset duration may be 2 to 5 minutes, and the second preset duration may be a value within 1 minute.

[0122] In some embodiments, if the user clicks on the preset reminder message, or the user never triggers the preset reminder message, both can be regarded as default enabling of the resource editing assistance function, so that the second resource editing interface can be displayed.

[0123] In some embodiments, the second resource editing interface may display the resource to be edited and the content of the recommended resources, where the content of the recommended resources may be displayed in the form of a list. The user may select the content of the recommended resources that meets the requirements and further select the corresponding processing operation, such as inserting it into the current resource content, etc.

[0124] In some embodiments, the second resource editing interface also includes resource editing function option controls, which can be used to implement different resource editing functions.

[0125] In some embodiments, the second resource editing interface includes a storage control, which can implement the storage of the edited resources; and a sharing control, which can implement the sharing of the edited resources.

[0126] Figure 4 is an example diagram of a second resource editing interface shown according to an exemplary embodiment, as Figure 4 shown, the second resource editing interface may display the resource to be edited, the content of the recommended resources, the storage control, the sharing control, and the resource editing function option controls, etc.

[0127] It can be understood that Figure 4 the display elements shown in the interface are only taken as an example. In different scenarios, more display elements can be configured according to the specific interaction scenarios, and the layout of these display elements can be changed, etc.

[0128] Regarding the storage control, its application process may include: in response to detecting a triggering operation by the user on the storage control, through the AI agent, determining the storage information according to the content of the resource to be edited, the content of the resource to be stored, and the content of the recommended resources, where the storage information is used to characterize the storage method and storage path of the resource to be stored, and the storage method includes at least one of direct storage, encrypted storage, and compressed storage; displaying the storage information; in response to detecting a confirmation operation by the user on the target storage information of the storage information, storing the resource to be stored according to the target storage information.

[0129] In this implementation, the AI agent can determine the storage method and storage path according to the content of the resource to be edited, the content of the resource to be stored, and the content of the recommended resources, and display the storage method and storage path to the user. If the user determines the corresponding storage information, the storage can be performed according to the corresponding storage information.

[0130] In some embodiments, if the content of the resource to be edited, the content of the resource to be stored, and the content of the recommended resources involve content with encryptability (such as having sensitive fields), the storage information may include encrypted storage; if not, the storage information may include direct storage. If the content size of the resource to be stored is large, the storage information may include compressed storage.

[0131] In some embodiments, the storage paths may include: cloud storage, local storage, network disk storage, etc. These storage paths can all be included in the stored information for the user to select.

[0132] In some embodiments, the application process of the sharing control may include: in response to detecting a triggering operation by the user on the sharing control, through an AI agent, determining sharing information based on the content of the resource to be edited, the content of the resource to be shared, and the content of the recommended resources. The sharing information is used to characterize the sharing method, sharing validity period, content to be shared, and secondary sharing permission of the resource to be shared. Among them, the sharing method includes at least one of direct sharing, sharing after encryption, and sharing after compression; displaying the sharing information; in response to detecting a confirmation operation by the user on the target sharing information of the sharing information, sharing the resource to be shared according to the target sharing information.

[0133] In this implementation manner, when the user has a sharing requirement, the AI agent can also determine the corresponding sharing information for them, and then the user can make a choice independently.

[0134] In some embodiments, if the content of the resource to be edited, the content of the resource to be shared, and the content of the recommended resources involve content with encryptability (such as having sensitive fields), then the sharing information may include sharing after encryption. If the content size of the resource to be shared is large, the sharing information may include sharing after compression. If the content size of the resource to be shared is small, the sharing information may include direct sharing.

[0135] In some embodiments, the sharing validity period may depend on the quality of the content of the resource to be edited, the content of the resource to be shared, and the content of the recommended resources. The higher the quality, the longer the sharing validity period. The secondary sharing permission may depend on the quality of the content of the resource to be edited, the content of the resource to be shared, and the content of the recommended resources. With higher quality, there is no secondary sharing permission. With lower quality, there is secondary sharing permission.

[0136] In some embodiments, if appropriate sharing information cannot be determined based on the content of the resource to be edited, the content of the resource to be shared, and the content of the recommended resources, then various optional sharing information can be displayed to the user, and the user can select the specified sharing information.

[0137] Furthermore, according to the sharing information and other operations related to sharing, such as the sharing object selected by the user, etc., the sharing of the resource to be shared can be achieved.

[0138] Further, when the user performs relevant resource editing operations, these operations can be responded to, and the displayed resource content can be changed accordingly so that the user can view the latest resource editing effect.

[0139] Figure 5It is a block diagram of an online editing system 500 for digital resources shown according to an exemplary embodiment. As Figure 5 shown, the online editing system 500 for digital resources includes:

[0140] A display module 501, configured to display a first resource editing interface on an electronic device, where the first resource editing interface is a display interface of a resource to be edited.

[0141] An acquisition module 502, configured to acquire user identification information, resource information of the resource to be edited, and hardware information of the electronic device.

[0142] A determination module 503, configured to determine recommended resource content through an AI agent according to the resource information, the user identification information, and the hardware information.

[0143] The display module 501 is further configured to, in response to detecting a usage requirement for the recommended resource content, display a second resource editing interface on the electronic device, where the second resource editing interface is a display interface of the resource to be edited and the recommended resource content. In response to detecting an editing operation of the user on the second resource editing interface, display the edited resource according to the editing operation.

[0144] Regarding the device in the above embodiment, the specific manners in which each module performs operations have been described in detail in the embodiment related to the method, and will not be elaborated here.

[0145] Figure 6 It is a block diagram of an electronic device 600 shown according to an exemplary embodiment. As Figure 6 shown, the electronic device 600 may include: a processor 601, a memory 602. The electronic device 600 may further include one or more of a multimedia component 603, an input / output (I / O) interface 604, and a communication component 605.

[0146] Among them, the processor 601 is used to control the overall operation of the electronic device 600 to complete all or part of the steps in the above-mentioned online editing method of digital resources. The memory 602 is used to store various types of data to support the operation of the electronic device 600. These data may include, for example, instructions for any application or method operating on the electronic device 600, as well as application-related data, such as contact data, sent and received messages, pictures, audio, video, and so on. The memory 602 can be implemented by any type of volatile or non-volatile storage device or a combination thereof, such as static random access memory (SRAM), electrically erasable programmable read-only memory (EEPROM), erasable programmable read-only memory (EPROM), programmable read-only memory (PROM), read-only memory (ROM), magnetic memory, flash memory, a magnetic disk, or an optical disc. The multimedia component 603 may include a screen and an audio component. Among them, the screen may be a touch screen, and the audio component is used to output and / or input audio signals. For example, the audio component may include a microphone, and the microphone is used to receive external audio signals. The received audio signals may be further stored in the memory 602 or sent through the communication component 605. The audio component further includes at least one speaker for outputting audio signals. The I / O interface 604 provides an interface between the processor 601 and other interface modules. The above-mentioned other interface modules may be a keyboard, a mouse, buttons, etc. These buttons may be virtual buttons or physical buttons. The communication component 605 is used for wired or wireless communication between the electronic device 600 and other devices. Wireless communication, such as Wi-Fi, Bluetooth, near field communication (NFC), 2G, 3G, or 4G, or a combination of one or more of them. Therefore, the corresponding communication component 605 may include: a Wi-Fi module, a Bluetooth module, and an NFC module.

[0147] In an exemplary embodiment, the electronic device 600 can be implemented by one or more application specific integrated circuits (ASICs), digital signal processors (DSPs), digital signal processing devices (DSPDs), programmable logic devices (PLDs), field programmable gate arrays (FPGAs), controllers, microcontrollers, microprocessors or other electronic components, and is used to execute the above-mentioned online editing method of digital resources.

[0148] In another exemplary embodiment, a computer-readable storage medium including program instructions is further provided. When the program instructions are executed by a processor, the steps of the above-mentioned online editing method of digital resources are implemented. For example, the computer-readable storage medium can be the above-mentioned memory 602 including program instructions, and the above-mentioned program instructions can be executed by the processor 601 of the electronic device 600 to complete the above-mentioned online editing method of digital resources.

[0149] In another exemplary embodiment, a computer program product is further provided. The computer program product includes a computer program that can be executed by a processor. When the computer program is executed by the processor, the steps of the above-mentioned online editing method of digital resources are implemented.

[0150] The preferred embodiments of the present disclosure have been described in detail above with reference to the accompanying drawings. However, the present disclosure is not limited to the specific details in the above embodiments. Within the scope of the technical concept of the present disclosure, various simple variations can be made to the technical solutions of the present disclosure, and these simple variations all belong to the protection scope of the present disclosure.

[0151] In addition, it should be noted that, among the various specific technical features described in the above specific embodiments, without conflict, they can be combined in any appropriate manner. To avoid unnecessary repetition, the present disclosure will not separately describe various possible combination methods.

[0152] In addition, any combination can be made between various different embodiments of the present disclosure, as long as it does not violate the idea of the present disclosure, it should also be regarded as the content disclosed by the present disclosure.

Claims

1. An online editing method for digital resources, characterized in that, Including: Displaying a first resource editing interface on an electronic device, where the first resource editing interface is a display interface of a resource to be edited; Obtaining user identification information, resource information of the resource to be edited, and hardware information of the electronic device; Determining recommended resource content by an AI agent according to the resource information, the user identification information, and the hardware information; In response to detecting a usage requirement for the recommended resource content, displaying a second resource editing interface on the electronic device, where the second resource editing interface is a display interface of the resource to be edited and the recommended resource content; In response to detecting an editing operation of the user on the second resource editing interface, displaying the edited resource according to the editing operation; The determining the recommended resource content by the AI agent according to the resource information, the user identification information, and the hardware information includes: Determining user evaluation information by the AI agent according to the user identification information, where the user evaluation information is used to characterize the user's resource editing ability; Determining hardware evaluation information by the AI agent according to the hardware information, where the hardware evaluation information is used to characterize the resource content compatibility ability of the electronic device; Retrieving in a preset resource content library by the AI agent according to the resource information, the user evaluation information, and the hardware evaluation information to obtain the recommended resource content; The preset resource content library includes various resource contents, and the resource information and resource content evaluation information respectively corresponding to different resource contents, where the resource content evaluation information is used to characterize the secondary editing difficulty of the resource content. The retrieving in the preset resource content library by the AI agent according to the resource information, the user evaluation information, and the hardware evaluation information to obtain the recommended resource content includes: Retrieving in the preset resource content library by the AI agent according to the resource information to determine candidate resource contents, where the resource information corresponding to the candidate resource contents matches the resource information; Determining the recommended resource content from the candidate resource contents by the AI agent according to the resource content evaluation information, the user evaluation information, and the hardware evaluation information corresponding to the candidate resource contents, where the resource content evaluation information corresponding to the recommended resource content matches the user evaluation information and the hardware evaluation information.

2. The online editing method according to claim 1, wherein The displaying the first resource editing interface on the electronic device includes: In response to detecting a selection operation of the user on a target resource among multiple preset resources, displaying the first resource editing interface on the electronic device, where the resource to be edited is the target resource; or, In response to detecting a resource uploading operation of the user, displaying the first resource editing interface on the electronic device, where the resource to be edited is the resource uploaded by the user.

3. The online editing method according to claim 1, wherein The determining the user evaluation information by the AI agent according to the user identification information includes: Through the AI intelligent agent, retrieve in a preset user database according to the user identification information, where the preset user database includes multiple registered user identification information and historical resource editing information respectively corresponding to the multiple registered user identification information; If, through the AI intelligent agent, a registered user identification information identical to the user identification information is retrieved in the preset user database, determine user evaluation information according to the historical resource editing information corresponding to the registered user identification information; If, through the AI intelligent agent, a registered user identification information identical to the user identification information is not retrieved in the preset user database, determine reference user evaluation information according to the historical resource editing information respectively corresponding to the multiple registered user identification information, and determine user evaluation information according to the reference user evaluation information and preset user evaluation information.

4. The online editing method according to any one of claims 1 to 3, characterized in that, The AI intelligent agent is an internet-connected intelligent agent, and the online editing method further includes: Obtain the payment information of the user for resource editing; Judge whether the recommended resource content matches the payment information through the AI intelligent agent according to the payment information; In the case where the recommended resource content does not match the payment information, search in the Internet according to the recommended resource content through the AI intelligent agent to obtain search resource content, and expand the recommended resource content according to the search resource content to obtain the expanded recommended resource content, where the expansion of the recommended resource content includes at least one of the expansion of the quantity of the recommended resource content, the expansion of the type of the recommended resource content, and the expansion of the quality of the recommended resource content.

5. The online editing method according to any one of claims 1 to 3, characterized in that The first resource editing interface includes an AI intelligent agent control and an editing function option control. Responding to detecting the usage requirement of the recommended resource content, display a second resource editing interface on the electronic device, including: Responding to detecting a triggering operation of the user on the AI intelligent agent control, display a second resource editing interface on the electronic device; or, Responding to not detecting a triggering operation of the user on the editing function option control within a first preset duration, display a preset reminder message in the first resource editing interface, where the preset reminder message is used to indicate to turn on the resource editing assistance function after a second preset duration; responding to detecting an operation of the user on the preset reminder message, and / or not detecting an operation of the user on the preset reminder message within the second preset duration, display a second resource editing interface on the electronic device.

6. The online editing method according to any one of claims 1 to 3, characterized in that The second resource editing interface includes a storage control, and the online editing method further includes: Responding to detecting a triggering operation of the user on the storage control, through the AI intelligent agent, determine storage information according to the content of the resource to be edited, the content of the resource to be stored, and the recommended resource content, where the storage information is used to represent the storage method and storage path of the resource to be stored, and the storage method includes at least one of direct storage, encrypted storage, and compressed storage; Display the storage information; In response to detecting the user's confirmation operation on the target storage information of the storage information, store the resource to be stored according to the target storage information.

7. The online editing method according to any one of claims 1 to 3, characterized in that The second resource editing interface includes a sharing control, and the online editing method further includes: In response to detecting the user's triggering operation on the sharing control, through the AI agent, determine sharing information according to the content of the resource to be edited, the content of the resource to be shared, and the content of the recommended resource, where the sharing information is used to characterize the sharing method, sharing validity period, content to be shared, and secondary sharing permission of the resource to be shared, and the sharing method includes at least one of direct sharing, encrypted sharing, and compressed sharing; Display the sharing information; In response to detecting the user's confirmation operation on the target sharing information of the sharing information, share the resource to be shared according to the target sharing information.

8. An online editing system for digital resources, characterized in that, including: A display module, configured to display a first resource editing interface on an electronic device, where the first resource editing interface is a display interface of the resource to be edited; An acquisition module, configured to acquire user identification information, resource information of the resource to be edited, and hardware information of the electronic device; A determination module, configured to determine recommended resource content through the AI agent according to the resource information, the user identification information, and the hardware information; The display module is further configured to, in response to detecting a usage requirement for the recommended resource content, display a second resource editing interface on the electronic device, where the second resource editing interface is a display interface of the resource to be edited and the recommended resource content; In response to detecting the user's editing operation on the second resource editing interface, display the edited resource according to the editing operation; The determination module is further configured to: determine user evaluation information through the AI agent according to the user identification information, where the user evaluation information is used to characterize the user's resource editing ability; Determine hardware evaluation information through the AI agent according to the hardware information, where the hardware evaluation information is used to characterize the resource content compatibility ability of the electronic device; Retrieve in a preset resource content library through the AI agent according to the resource information, the user evaluation information, and the hardware evaluation information to obtain the recommended resource content; The preset resource content library includes various resource contents, and different resource contents respectively correspond to resource information and resource content evaluation information, where the resource content evaluation information is used to characterize the secondary editing difficulty of the resource content, and the determination module is further configured to: Retrieve in the preset resource content library through the AI agent according to the resource information to determine candidate resource contents, where the resource information corresponding to the candidate resource contents matches the resource information; Determine the recommended resource content from the candidate resource contents through the AI agent according to the resource content evaluation information corresponding to the candidate resource contents, the user evaluation information, and the hardware evaluation information, where the resource content evaluation information corresponding to the recommended resource content matches the user evaluation information and the hardware evaluation information.

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