Digital resource online editing method and system

Abstract

The invention relates to a digital resource online editing method and system, and relates to the technical field of computers. In the online editing scene of the digital resources, the recommended resource content is determined through the AI agent according to the resource information of the to-be-edited resources, the user identification information and the hardware information of the electronic equipment, and the recommended resource content and the to-be-edited resources are further presented to the user together. The recommended resource content can provide resource editing creativity for the user, and the user can use the recommended resource content according to requirements so as to perform online editing operation of the resources. Therefore, according to the technical scheme, a resource editing creativity can be provided for the user, the intelligence of online editing of the digital resources is improved, and then the online editing experience of the user on the digital resources is improved.

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 text, images, audio, video and other forms, which are accessed and used through digital devices such as computers and networks. It is the sum of information resources published, accessed and used in digital form formed by the 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 edit, collaborate and manage various digital resources in real time.

[0004] At present, in the online editing scenario of digital resources, although it can support editing of multiple functions, it cannot provide users with editing creativity, has poor intelligence, and thus has a 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 creativity, improve the intelligence of online editing of digital resources, and thus improve the user's online editing experience of digital resources.

[0006] In order to achieve the above-mentioned objectives, in a first aspect, the present disclosure provides an online editing method for digital resources, comprising: displaying a first resource editing interface on an electronic device, the first resource editing interface being a display interface of a resource to be edited; acquiring user identification information, resource information of the resource to be edited, and hardware information of the electronic device; determining recommended resource content through an AI agent based on the resource information, the user identification information, and the hardware information; in response to detecting a demand for use of the recommended resource content, displaying a second resource editing interface on the electronic device, the second resource editing interface being a display interface of the resource to be edited and the recommended resource content; in response to detecting an editing operation performed by the user on the second resource editing interface, displaying the edited resource according to the editing operation.

[0007] Optionally, 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 from multiple preset resources, displaying the first resource editing interface on the electronic device, the resource to be edited being 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, the resource to be edited being a resource uploaded by the user.

[0008] Optionally, the determining of recommended resource content by the AI ​​agent based on the resource information, the user identification information and the hardware information includes: determining user evaluation information by the AI ​​agent based on the user identification information, the user evaluation information being used to characterize the resource editing capability of the user; determining hardware evaluation information by the AI ​​agent based on the hardware information, the hardware evaluation information being used to characterize the resource content compatibility capability of the electronic device; and obtaining the recommended resource content by searching in a preset resource content library by the AI ​​agent based on the resource information, the user evaluation information and the hardware evaluation information.

[0009] Optionally, determining the user evaluation information according to the user identification information by the AI ​​agent includes: searching, by the AI ​​agent, in a preset user database according to the user identification information, the preset user database including multiple registered user identification information and historical resource editing information corresponding to the multiple registered user identification information; if the registered user identification information identical to the user identification information is retrieved from the preset user database by the AI ​​agent, determining the user evaluation information according to the historical resource editing information corresponding to the registered user identification information; if the registered user identification information identical to the user identification information is not retrieved from the preset user database by the AI ​​agent, determining reference user evaluation information according to the historical resource editing information 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 a variety of resource contents, and different resource contents respectively correspond to resource information and resource content evaluation information, and the resource content evaluation information is used to characterize the difficulty of secondary editing of the resource content. The AI ​​agent searches in the preset resource content library according to the resource information, the user evaluation information and the hardware evaluation information to obtain the recommended resource content, including: searching in the preset resource content library according to the resource information by the AI ​​agent to determine candidate resource content, and the resource information corresponding to the candidate resource content matches the resource information; determining the recommended resource content from the candidate resource content by the AI ​​agent according to the resource content evaluation information corresponding to the candidate resource content, the user evaluation information and the hardware evaluation information, and the resource content evaluation information corresponding to the recommended resource content matches the user evaluation information and the hardware evaluation information.

[0011] Optionally, the AI ​​agent is a networked agent, and the online editing method further includes: obtaining payment information of the user for resource editing; judging by the AI ​​agent whether the recommended resource content matches the payment information based on the payment information; when the recommended resource content does not match the payment information, searching the Internet based on the recommended resource content by the AI ​​agent to obtain search resource content, and expanding the recommended resource content based on the search resource content to obtain expanded recommended resource content, wherein the expansion of the recommended resource content includes at least one of: expansion of the quantity of recommended resource content, expansion of the type of recommended resource content, and expansion of the quality of recommended resource content.

[0012] Optionally, the first resource editing interface includes an AI agent control and an editing function option control, and the response to detecting the need to use the recommended resource content, displaying the second resource editing interface on the electronic device includes: in response to detecting a user triggering operation on the AI ​​agent control, displaying the second resource editing interface on the electronic device; or, in response to not detecting a user triggering operation on the editing function option control within a first preset time period, displaying a preset reminder information in the first resource editing interface, the preset reminder information being used to indicate that the resource editing auxiliary function is turned on after a second preset time period; in response to detecting a user operation on the preset reminder information, and / or not detecting a user operation on the preset reminder information within the second preset time period, displaying the second resource editing interface on the electronic device.

[0013] Optionally, the second resource editing interface includes a storage control, and the online editing method further includes: in response to detecting a trigger operation of the user on the storage control, determining storage information through the AI ​​agent according to the content of the resource to be edited, the content of the resource to be stored and the content of the recommended resource, wherein the storage information is used to characterize the storage method and storage path of the resource to be stored, wherein 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 of the user on the target storage information of the storage information, storing the resource to be stored according to the target storage information.

[0014] Optionally, the second resource editing interface includes a sharing control, and the online editing method further includes: in response to detecting a trigger operation of the sharing control by the user, determining sharing information through the AI ​​agent 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, the sharing information being used to characterize the sharing method, sharing validity period, content to be shared and secondary sharing permissions of the resource to be shared, wherein the sharing method includes: at least one of direct sharing, encrypted sharing and compressed sharing; displaying the sharing information; in response to detecting a confirmation operation of 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, comprising: a display module, used to display a first resource editing interface on an electronic device, the first resource editing interface being a display interface of a resource to be edited; an acquisition module, used to acquire user identification information, resource information of the resource to be edited, and hardware information of the electronic device; a determination module, used to determine recommended resource content through an AI agent based on the resource information, the user identification information, and the hardware information; the display module is also used to display a second resource editing interface on the electronic device in response to detecting a demand for use of the recommended resource content, the second resource editing interface being a display interface of the resource to be edited and the recommended resource content; in response to detecting an editing operation performed by the user on the second resource editing interface, displaying the edited resource according to the editing operation.

[0016] Through the above technical solution, in the online editing scenario of digital resources, the AI ​​agent determines the recommended resource content based on 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. 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 resource. Therefore, the technical solution can provide users with resource editing ideas, improve the intelligence of online editing of digital resources, and thus 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 following detailed description. BRIEF DESCRIPTION OF THE DRAWINGS

[0018] The accompanying drawings are used to provide a further understanding of the present disclosure and constitute a part of the specification. Together with the following specific embodiments, they are used to explain the present disclosure but do not constitute a limitation of the present disclosure. In the accompanying drawings: Figure 1The figure is a schematic diagram of an application scenario of online editing of digital resources according to an exemplary embodiment.

[0019] Figure 2 The figure is a flow chart of a method for online editing of digital resources according to an exemplary embodiment.

[0020] Figure 3 The figure is an example diagram of a first resource editing interface according to an exemplary embodiment.

[0021] Figure 4 The figure is an example diagram showing a second resource editing interface according to an exemplary embodiment.

[0022] Figure 5 It is a block diagram of an online editing system for digital resources according to an exemplary embodiment.

[0023] Figure 6 It is a block diagram of an electronic device according to an exemplary embodiment. DETAILED DESCRIPTION

[0024] The specific implementation of the present disclosure is described in detail below in conjunction with the accompanying drawings. It should be understood that the specific implementation described herein is only used to illustrate and explain the present disclosure, and is not used to limit the present disclosure.

[0025] Digital resources refer to information resources stored, processed and disseminated in digital form, including text, images, audio, video and other forms, which are accessed and used through digital devices such as computers and networks. It is the sum of information resources published, accessed and used in digital form formed by the integration of computer technology, communication technology and multimedia technology.

[0026] Online editing of digital resources is one of the important functions of modern digital resource management, which allows users to edit, collaborate and manage various digital resources in real time.

[0027] At present, in the online editing scenario of digital resources, although it can support editing of multiple functions, it cannot provide users with editing creativity, has poor intelligence, and thus has a poor user experience.

[0028] For example, in some online document editing scenarios, users can edit online documents, and multiple editing functions can be provided to users, such as copying, quoting, pasting, etc. However, in such editing scenarios, users are not provided with intelligent editing ideas, such as what content can be filled in the document, etc., which makes the online editing of resources less intelligent and the user experience is also poor.

[0029] For some online editing scenarios where creativity is more important, it especially affects the user experience.

[0030] Based on this, the embodiment of the present disclosure provides a technical solution. In the online editing scenario of digital resources, an AI agent is used to determine the recommended resource content based on the resource information of the resource to be edited, user identification information and hardware information of the electronic device, and further present the recommended resource content and the resource to be edited to the user. 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.

[0031] Therefore, this technical solution can provide users with resource editing creativity, improve the intelligence of online editing of digital resources, and thus enhance users' online editing experience of digital resources.

[0032] Figure 1 is a schematic diagram of an application scenario of online editing of digital resources according to an exemplary embodiment. Figure 1 As shown, the application scenario includes a front end and a back end that is connected to the front end in communication (connected via a network in the figure).

[0033] 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.

[0034] In some embodiments, the back end may be a server, and the front end may be an electronic device such as a mobile phone or a computer.

[0035] In some embodiments, the front-end service for digital resource editing may include: applications, browsers, applets, etc., which are not limited here.

[0036] In some embodiments, digital resources may include text, images, audio, video and other forms, which are not limited here.

[0037] In the embodiments of the present disclosure, AI agents are also applied. AI agents are intelligent systems that can perceive the environment, make autonomous decisions, and take actions to achieve specific goals. They integrate technologies such as large language models, reinforcement learning, and multimodal interaction, and can independently complete tasks in complex scenarios. They are considered to be an advanced form of artificial intelligence technology.

[0038] AI agents have the following characteristics: Autonomy: Ability to operate independently without human intervention. Perception: Acquisition of external information such as voice, images or text through sensors or data interfaces. Decision-making: Analyze and make decisions based on the acquired information. Execution: Take actual actions based on the decision results. Adaptive ability: Optimize its behavior through learning and adapt to environmental changes. Interactivity: Ability to interact naturally with users or other systems.

[0039] Therefore, by providing users with resource editing ideas through AI agents, the online editing of digital resources is made more intelligent.

[0040] Figure 2 is a flowchart of an online editing method for digital resources according to an exemplary embodiment. The online editing method can be applied to Figure 1 In the application scenario shown, some steps may be implemented by both the front-end and the back-end, or only by the front-end. The online editing method may include the following steps: Step S21: displaying a first resource editing interface on the electronic device, where the first resource editing interface is a display interface of the resource to be edited.

[0041] Step S22, obtaining user identification information, resource information of the resource to be edited, and hardware information of the electronic device.

[0042] Step S23, determining the recommended resource content based on resource information, user identification information and hardware information through the AI ​​agent.

[0043] Step S24, in response to detecting the use demand of the recommended resource content, displaying a second resource editing interface on the electronic device, the second resource editing interface being a display interface of the resource to be edited and the recommended resource content.

[0044] Step S25, 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.

[0045] In step S21, the electronic device can be regarded as Figure 1 Therefore, a first resource editing interface can be displayed on the electronic device, and the interface is used to display the resource to be edited.

[0046] In the disclosed embodiment, the AI ​​agent can be expressed as: Agent = LLM (Large Language Model) + Planning + Memory + Tools.

[0047] This formula shows that AI agents not only rely on language understanding capabilities, but also require planning, memory, and tool-calling capabilities to complete complex tasks.

[0048] Regarding large language models, the following key components can be included: Word embedding: Word embedding is a technique for mapping words to a continuous vector space to capture the semantic relationship between words. Common methods include Word2Vec and GloVe: Word2Vec: CBOW (Continuous Bag of Words): Predict the central word given the context. Skip-Gram: Predict the context given the central word. Training objectives: . Where T is the size of the training data, w t is the word at time step t.

[0049] GloVe: Learning word embeddings through matrix decomposition tasks, training objectives: ,in, X is the word vector matrix, Y is the context vector matrix, f ( u , v ) is a word pair ( u , v ) similarity.

[0050] Self-Attention: The self-attention mechanism is the core of the Transformer architecture, allowing the model to establish long-distance dependencies between different time steps. The calculation formula is: ,in, Q is the query vector, K is the key vector, V is a vector of values, d k is the dimension of the key vector.

[0051] Transformer architecture: Transformer is the core architecture of large language models, which realizes efficient sequence modeling through self-attention mechanism and encoder-decoder structure. Main components: Multi-Head Attention: A parallel self-attention mechanism that allows the model to focus on multiple different contexts at the same time.

[0052] Positional Encoding: It is used to represent the position information in the sequence. Since Transformer has no sequence structure, positional encoding is needed to capture the sequence structure.

[0053] Residual Connection: Retain the previous input of each layer to speed up the training process.

[0054] Layer Normalization: Normalize the output of the model to reduce overfitting.

[0055] These techniques and formulas are the basis of large language models, but 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.

[0056] Therefore, in the embodiment of the present disclosure, the accessed large model is pre-trained and integrated into the form of an AI agent to provide technical support for the technical solution of the embodiment of the present disclosure.

[0057] In some embodiments, the first resource editing interface may be an interface displayed under the triggering of a user's operation. Under different operation triggering modes, the source of the resource to be edited may also be different.

[0058] Therefore, as an optional implementation, step S21 includes: in response to detecting a user's selection operation on a target resource among a plurality of preset resources, displaying a first resource editing interface on the electronic device, wherein the resource to be edited is the target resource.

[0059] In some embodiments, taking an application as an example, a user may first register / log in the application using personal information, and then a resource selection interface may be displayed on the electronic device. The resource selection interface includes multiple preset resources, and the user may select a specified resource from the multiple resources. Then, a first resource editing interface may be displayed on the electronic device. In this scenario, the resource to be edited is the target resource.

[0060] As another optional implementation, step S21 includes: in response to detecting a resource uploading operation by a user, displaying a first resource editing interface on the electronic device, where the resource to be edited is a resource uploaded by the user.

[0061] In some embodiments, taking an application as an example, a user may first register / log in the application using personal information, and then a resource selection interface may be displayed on the electronic device. The resource selection interface may include a resource upload control, and the user may trigger a resource upload operation by operating the resource upload control. Then, a first resource editing interface may be displayed on the electronic device. In this scenario, the resource to be edited is the resource uploaded by the user.

[0062] In addition to the above two implementations, in more digital resource online editing scenarios, there may be more ways to trigger the resource editing interface.

[0063] For example, in a social application, users can send digital resources, such as documents, to each other. 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, the interface can also display an editing control. The user can trigger the electronic device to display the first resource editing interface by operating the editing control. In this scenario, the resource to be edited is a resource sent to the current user by other users.

[0064] It can be understood that there are many 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, so no examples are given here one by one.

[0065] Figure 3 is an example diagram of a first resource editing interface according to an exemplary embodiment. Figure 3 As shown, on the 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.

[0066] Among them, the editing function option control can correspond to the corresponding editing functions. 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.

[0067] Depending on the type of resource to be edited, the resource to be edited and the editing function option control may be displayed in different forms or arranged in different ways on the first resource editing interface. Figure 3 For example, the resource to be edited is displayed on the left, and the editing function option control is displayed on the right.

[0068] In step S22, user identification information, resource information of the resource to be edited, and hardware information of the electronic device are obtained.

[0069] In some embodiments, the user identification information may be used as the identification of the user, which may be a kind of identity identification information, such as the user's account number, password, and user name, etc. The user identification information may be directly obtained.

[0070] In some embodiments, the resource information of the resource to be edited may represent the situation of the resource, which may include: resource type, resource description, resource name, resource size, etc. Among them, the resource type, for example: text, picture, video, audio, etc.; the resource description, may describe the content involved in the resource, for example: scenery, humanities, work-related, etc.; the resource name, may be used as identification information of the resource; the resource size, may be described in units such as KB, MB, etc., representing the data volume of the resource.

[0071] In some embodiments, when obtaining the resource to be edited, the resource information may be determined or obtained.

[0072] In some embodiments, the hardware information of an electronic device can characterize the hardware performance of the electronic device, which may include: hardware type, hardware memory (running memory, etc.), hardware battery capacity and other performance parameters. The hardware information is inherent information of the electronic device and can be directly obtained.

[0073] Furthermore, in step S23, the AI ​​agent determines the recommended resource content based on the resource information, user identification information and hardware information.

[0074] In some embodiments, the AI ​​agent can be automatically enabled after the electronic device starts the online editing function. Thus, the AI ​​agent can actively pull resource information, user identification information and hardware information to determine the recommended resource content.

[0075] In some embodiments, regarding AI intelligent agent technology, reference can be made to mature technologies in the field and will not be introduced in detail in the present disclosed embodiments.

[0076] As an optional implementation, step S23 includes: determining user evaluation information based on user identification information through an AI agent, where the user evaluation information is used to characterize the user's resource editing ability; determining hardware evaluation information based on hardware information through an AI agent, where the hardware evaluation information is used to characterize the resource content compatibility of the electronic device; and searching in a preset resource content library through an AI agent based on resource information, user evaluation information, and hardware evaluation information to obtain recommended resource content.

[0077] In this implementation, the AI ​​agent can determine user evaluation information based on user identification information, and the user evaluation information can represent the user's resource editing ability.

[0078] In some embodiments, the AI ​​agent determines user evaluation information based on the user identification information, including: searching a preset user database based on the user identification information through the AI ​​agent, the preset user database including multiple registered user identification information and historical resource editing information corresponding to the multiple registered user identification information; if the registered user identification information identical to the user identification information is retrieved from the preset user database through the AI ​​agent, the user evaluation information is determined based on the historical resource editing information corresponding to the registered user identification information; if the registered user identification information identical to the user identification information is not retrieved from the preset user database through the AI ​​agent, reference user evaluation information is determined based on the historical resource editing information corresponding to the multiple registered user identification information, and the user evaluation information is determined based on the reference user evaluation information and the preset user evaluation information.

[0079] In this embodiment, a user database is pre-configured, and the user database can store multiple registered user identification information and historical resource editing information corresponding to the multiple registered user identification information. That is, for an online editing application, the historical resource editing of users who have participated in the online editing can be recorded.

[0080] Furthermore, when evaluating users, this information can be used as a reference.

[0081] In some embodiments, using AI agents to implement information retrieval can improve the efficiency of information retrieval.

[0082] In some embodiments, the AI ​​agent may compare the registered user identification information in a preset user database with the current user identification information. If consistent user identification information is retrieved, the user evaluation information may be determined directly based on the historical resource editing information corresponding to the registered user identification information.

[0083] In some embodiments, historical resource editing information may include: resource type, resource size, resource content description information, etc. Based on this information, the complexity and difficulty of the historical resource editing information can be determined, and based on the complexity and difficulty, user evaluation information can be determined.

[0084] In some embodiments, the user evaluation information may be a resource editing capability score, where the higher the score, the stronger the representation capability. Therefore, the relationship between the score, the complexity and difficulty of the historical resource editing information, etc. may be preconfigured, and the resource editing capability score may be determined based on the preconfigured relationship and specific information.

[0085] For example, if 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 represent the conversion weights of complexity difficulty and resource editing ability score, respectively. The conversion weights can be determined by statistical analysis of big data, and the specific values ​​are not limited here.

[0086] In some embodiments, when no registered user identification information identical to the user identification information is retrieved in a preset user database, historical resource editing information corresponding to multiple registered user identification information can be obtained, and based on these historical resource editing information, a reference user evaluation information is obtained, and the user evaluation information is determined based on the reference user evaluation information and the preset user evaluation information.

[0087] In some embodiments, various complexity, difficulty and other information can be determined based on the historical resource editing information corresponding to multiple registered user identification information. Then, these various complexity, difficulty and other information are averaged to obtain information such as average complexity and average difficulty. Finally, the average complexity and average difficulty are converted into a resource editing ability score with reference to the aforementioned embodiment, thereby obtaining reference user evaluation information.

[0088] In some embodiments, the preset user evaluation information may be a pre-configured minimum resource editing capability score for having resource editing capability. For example, assuming that the resource editing capability score is a score between 0 and 100, the preset user evaluation information may be a score between 30 and 50.

[0089] In some embodiments, when the number of registered user identification information is large, the reference user evaluation information has a higher priority, and when the number of registered user identification information is small, the preset user evaluation information has a higher priority. Then, 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 averaged to obtain the final user evaluation information.

[0090] In some embodiments, hardware evaluation information is determined by an AI agent based on hardware information, and the hardware evaluation information is used to characterize resource content compatibility of the electronic device.

[0091] In some embodiments, the hardware evaluation information may be a compatibility score. The evaluation of hardware is a relatively mature technology in the art and will not be described in detail here. For example, the larger the hardware running memory, the stronger the resource content compatibility, which allows more resource content to be edited and richer resource content to be inserted, and thus the compatibility score is also higher.

[0092] Furthermore, the AI ​​agent searches a preset resource content library based on resource information, user evaluation information, and hardware evaluation information to obtain recommended resource content.

[0093] In some embodiments, the recommended resource content may be text, picture, audio, video, etc., which may be different from the resource type of the resource to be edited. For example, in a text resource, picture resource content, etc. may also be inserted.

[0094] As an optional implementation, the preset resource content library includes multiple resource contents, and different resource contents correspond to resource information and resource content evaluation information. The resource content evaluation information can represent the difficulty of secondary editing of the resource content.

[0095] In some embodiments, the secondary editing difficulty of resource content represents the difficulty for users to use it for resource editing. Therefore, when recommending resource content to users, the secondary editing difficulty needs to be considered.

[0096] For example, for video resources, secondary editing requires users to have video editing capabilities, so secondary editing is more difficult. For text resources, secondary editing does not require users to have strong editing capabilities, such as being able to directly copy to existing resources, so secondary editing is less difficult.

[0097] Therefore, when setting up a resource content library, you can first search from various digital resources in big data to obtain a variety of resource contents that have corresponding resource information, and then evaluate the difficulty of secondary editing of these various resource contents to obtain resource content evaluation information.

[0098] In some embodiments, the evaluation of the difficulty of secondary editing can also be achieved through an AI model, which can be pre-trained with a large amount of data so that the AI ​​model has the ability to evaluate the difficulty of secondary editing.

[0099] Furthermore, the AI ​​agent searches in a preset resource content library according to the resource information, user evaluation information and hardware evaluation information to obtain recommended resource content, which may include: searching in a preset resource content library according to the resource information by the AI ​​agent to determine candidate resource content, and matching the resource information corresponding to the candidate resource content with the resource information; determining recommended resource content from the candidate resource content by the AI ​​agent according to the resource content evaluation information, user evaluation information and hardware evaluation information corresponding to the candidate resource content, and matching the resource content evaluation information corresponding to the recommended resource content with the user evaluation information and the hardware evaluation information.

[0100] In this implementation, it is also necessary to apply the retrieval capability of the AI ​​agent to search from a preset resource content library.

[0101] In some embodiments, the resource information corresponding to the candidate resource content matches the resource information, which may be that the similarity between the resource information corresponding to the candidate resource content and the resource information is higher than a preset similarity.

[0102] In some embodiments, the resource content evaluation information corresponding to the recommended resource content matches the user evaluation information and the hardware evaluation information, which may be that the resource content evaluation information satisfies a corresponding relationship with the user evaluation information and the hardware evaluation information.

[0103] For example, the secondary editing difficulty is represented by M, the user's resource editing ability score is represented by S, and the hardware compatibility score is represented by N, then M<f(S,N), where f(S+N) represents a function that converts S and N into the secondary editing difficulty, and the function can be determined by analyzing and statistically analyzing big data. For example, the higher the resource editing ability score, the higher the secondary editing difficulty, the higher the hardware compatibility score, the higher the secondary editing difficulty, and so on.

[0104] Therefore, through the intelligent retrieval function of the AI ​​agent, the content of recommended resources can be determined.

[0105] In some embodiments, the AI ​​agent may be a networked agent, and the method may further include: obtaining payment information of a user for editing a resource; determining, by the AI ​​agent, whether the recommended resource content matches the payment information based on the payment information; in the case where the recommended resource content does not match the payment information, searching the Internet based on the recommended resource content by the AI ​​agent to obtain the search resource content, and expanding the recommended resource content based on the search resource content to obtain expanded recommended resource content, wherein the expansion of the recommended resource content includes: at least one of an expansion of the quantity of the recommended resource content, an expansion of the type of the recommended resource content, and an expansion of the quality of the recommended resource content.

[0106] In some embodiments, the payment information may be a recharge record, a membership registration record, etc. Accordingly, different payment information may correspond to different recommended resource contents.

[0107] In some embodiments, the judgment process of whether the recommended resource content matches the payment information may include: obtaining different pre-set payment information and the corresponding recommended resource content quality, comparing the current recommended resource content quality with the preset recommended resource content quality corresponding to the current payment information, if the current quality is higher or basically the same, then it matches, otherwise it does not match.

[0108] In some embodiments, the quality of the recommended resource content may be determined by the content richness, content depth, etc. of the recommended resource content, and specific details may refer to mature technologies in the art.

[0109] In some embodiments, when the recommended resource content does not match the payment information, an online search function may be enabled to search the Internet to obtain the search resource content. Further, the recommended resource content is expanded using the search resource content to obtain expanded recommended resource content, wherein the expansion of the recommended resource content includes at least one of: 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.

[0110] In some embodiments, the expansion of the quantity of recommended resource content may be to add the search resource content to the recommended resource content; the expansion of the types of recommended resource content may be to add the search 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 to insert the high-quality resource content in the search resource content into the existing low-quality recommended resource content. Alternatively, other expansion methods may be used, which are not limited here.

[0111] After the recommended resource content is determined, in step S24, in response to detecting a demand for using the recommended resource content, a second resource editing interface is displayed on the electronic device.

[0112] It is understandable that although the recommended resource content is determined, the user may not necessarily have a need for it. Therefore, when the use need is detected, the corresponding display can be performed to avoid affecting the user's editing.

[0113] As an optional implementation, the first resource editing interface may include an AI agent control and an editing function option control, so that step S24 includes: in response to detecting a user triggering operation on the AI ​​agent control, displaying a second resource editing interface on the electronic device; or, in response to not detecting a user triggering operation on the editing function option control within a first preset time period, displaying a preset reminder message in the first resource editing interface, the preset reminder message being used to indicate that the resource editing auxiliary function is to be turned on after a second preset time period; in response to detecting a user operation on the preset reminder message, and / or not detecting a user operation on the preset reminder message within the second preset time period, displaying a second resource editing interface on the electronic device.

[0114] In this embodiment, if the user performs a trigger operation on the AI ​​agent control, such as clicking, long pressing, etc., the second resource editing interface can be directly displayed.

[0115] Also, if the user has not edited for a long time, it means that the user may have a recommendation demand for resource content, and at this time, a preset reminder message can be displayed first. For example, the resource editing auxiliary function will be enabled after XX seconds.

[0116] In some embodiments, the first preset time length may be 2 to 5 minutes, and the second preset time length may be a value within 1 minute.

[0117] In some embodiments, if the user clicks on the preset reminder information, or the user has not triggered the preset reminder information, it can be regarded as the resource editing auxiliary function being enabled by default, so that the second resource editing interface can be displayed.

[0118] In some embodiments, the second resource editing interface may display the resource to be edited and the recommended resource content, wherein the recommended resource content may be displayed in the form of a list. The user may select the recommended resource content required and further select a corresponding processing operation, such as inserting the current resource content.

[0119] In some embodiments, the second resource editing interface also includes a resource editing function option control, which can be used to implement different resource editing functions.

[0120] In some embodiments, the second resource editing interface includes a storage control to enable storage of the edited resources; and includes a sharing control to enable sharing of the edited resources.

[0121] Figure 4 is an example diagram of a second resource editing interface according to an exemplary embodiment. Figure 4 As shown, the second resource editing interface can display resources to be edited, recommended resource content, storage controls, sharing controls, and resource editing function option controls.

[0122] Understandably, Figure 4 The display elements shown in the illustrated interface are merely examples, and in different scenarios, more display elements may be configured, and the layout of these display elements may be changed, etc., according to specific interaction scenarios.

[0123] Regarding storage controls, their application process may include: in response to detecting a user's triggering operation on the storage control, through an AI agent, determining storage information based on the content of the resources to be edited, the content of the resources to be stored, and the content of the recommended resources, the storage information is used to characterize the storage method and storage path of the resources to be stored, wherein the storage method includes: at least one of direct storage, encrypted storage, and compressed storage; displaying the storage information; in response to detecting a user's confirmation operation on the target storage information of the storage information, storing the resources to be stored according to the target storage information.

[0124] In this implementation, the AI ​​agent can determine the storage method and storage path based on the content of the resources to be edited, the content of the resources 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, it can be stored according to the corresponding storage information.

[0125] 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 resource involve content that can be encrypted (for example, with sensitive fields), the storage information may include encrypted storage; if not, the storage information may include direct storage. If the content of the resource to be stored is large in size, the storage information may include compressed storage.

[0126] In some embodiments, the storage path may include: cloud storage, local storage, network disk storage, etc. These storage paths can be included in the storage information and selected by the user.

[0127] In some embodiments, the application process of the sharing control may include: in response to detecting a user's triggering operation 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 resource, the sharing information is used to characterize the sharing method, sharing validity period, content to be shared, and secondary sharing permissions of the resource to be shared, wherein the sharing method includes: at least one of direct sharing, encrypted sharing, and compressed sharing; displaying the sharing information; in response to detecting a user's confirmation operation on the target sharing information of the sharing information, sharing the resource to be shared according to the target sharing information.

[0128] In this implementation, when a user has a sharing need, the AI ​​agent can also determine the corresponding sharing information for the user, and then the user can make the choice independently.

[0129] 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 resource involve content that can be encrypted (for example, with sensitive fields), the sharing information may include sharing after encryption. If the content of the resource to be shared is large in size, the sharing information may include sharing after compression; if the content of the resource to be shared is small in size, the sharing information may include direct sharing.

[0130] 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 resource. The higher the quality, the longer the sharing validity period. The secondary sharing authority 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 resource. If the quality is high, there is no secondary sharing authority, and if the quality is low, there is secondary sharing authority.

[0131] 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 resource, various optional sharing information may be displayed to the user, and the user may select the specified sharing information.

[0132] Furthermore, the resource to be shared can be shared according to the sharing information and other operations related to sharing, such as the sharing object selected by the user.

[0133] Furthermore, when the user performs related 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 effects.

[0134] Figure 5is a block diagram of an online editing system 500 for digital resources according to an exemplary embodiment. Figure 5 As shown, the online editing system 500 of the digital resource includes: The display module 501 is used to display a first resource editing interface on the electronic device, where the first resource editing interface is a display interface of the resource to be edited.

[0135] The acquisition module 502 is used to acquire user identification information, resource information of the resource to be edited, and hardware information of the electronic device.

[0136] The determination module 503 is used to determine the recommended resource content according to the resource information, the user identification information and the hardware information through the AI ​​agent.

[0137] The display module 501 is further configured to display a second resource editing interface on the electronic device in response to detecting a use requirement of the recommended resource content, wherein 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, the edited resource is displayed according to the editing operation.

[0138] Regarding the device in the above embodiment, the specific manner in which each module performs operations has been described in detail in the embodiment of the method, and will not be elaborated here.

[0139] Figure 6 FIG. 6 is a block diagram of an electronic device 600 according to an exemplary embodiment. Figure 6 As shown, the electronic device 600 may include: a processor 601 , a memory 602 . The electronic device 600 may also include one or more of a multimedia component 603 , an input / output (I / O) interface 604 , and a communication component 605 .

[0140] 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 online editing method of the digital resource. The memory 602 is used to store various types of data to support the operation of the electronic device 600. For example, these data may include instructions for any application or method used to operate on the electronic device 600, and application-related data, such as contact data, messages sent and received, pictures, audio, video, etc. 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 (Static Random Access Memory, referred to as SRAM), electrically erasable programmable read-only memory (Electrically Erasable Programmable Read-Only Memory, referred to as EEPROM), erasable programmable read-only memory (Erasable Programmable Read-Only Memory, referred to as EPROM), programmable read-only memory (Programmable Read-Only Memory, referred to as PROM), read-only memory (Read-Only Memory, referred to as ROM), magnetic memory, flash memory, magnetic disk or optical disk. The multimedia component 603 may include a screen and an audio component. The screen may be, for example, 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 for receiving external audio signals. The received audio signal may be further stored in the memory 602 or sent through the communication component 605. The audio component also 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, and 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, so the corresponding communication component 605 may include: Wi-Fi module, Bluetooth module, NFC module.

[0141] In an exemplary embodiment, the electronic device 600 can be implemented by one or more application specific integrated circuits (ASIC), digital signal processors (DSP), digital signal processing devices (DSPD), programmable logic devices (PLD), field programmable gate arrays (FPGA), controllers, microcontrollers, microprocessors or other electronic components to execute the above-mentioned online editing method of digital resources.

[0142] In another exemplary embodiment, a computer-readable storage medium including program instructions is also provided, and 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.

[0143] In another exemplary embodiment, a computer program product is further provided. The computer program product includes a computer program executable by a processor. When the computer program is executed by the processor, the steps of the online editing method of digital resources are implemented.

[0144] The preferred embodiments of the present disclosure are described in detail above in conjunction with the accompanying drawings; however, the present disclosure is not limited to the specific details in the above embodiments. Within the technical concept of the present disclosure, a variety of simple modifications can be made to the technical solution of the present disclosure, and these simple modifications all fall within the protection scope of the present disclosure.

[0145] It should also be noted that the various specific technical features described in the above specific embodiments can be combined in any suitable manner without contradiction. In order to avoid unnecessary repetition, the present disclosure will not further describe various possible combinations.

[0146] In addition, various embodiments of the present disclosure may be arbitrarily combined, and as long as they do not violate the concept of the present disclosure, they should also be regarded as the contents disclosed by the present disclosure.

Claims

1. A method for online editing of digital resources, characterized in that: include: Displaying a first resource editing interface on the electronic device, where the first resource editing interface is a display interface of the resource to be edited; Acquire user identification information, resource information of the resource to be edited, and hardware information of the electronic device; Determine, by an AI agent, recommended resource content according to the resource information, the user identification information and the hardware information; In response to detecting a use demand for the recommended resource content, displaying a second resource editing interface on the electronic device, the second resource editing interface being a display interface of the resource to be edited and the recommended resource content; In response to detecting an editing operation performed by the user on the second resource editing interface, displaying the edited resource according to the editing operation.

2. The online editing method of digital resources according to claim 1, characterized in that: The displaying of the first resource editing interface on the electronic device includes: In response to detecting the user's selection operation on a target resource among a plurality of preset resources, displaying the first resource editing interface on the electronic device, wherein the resource to be edited is the target resource; or, In response to detecting the resource uploading operation of the user, the first resource editing interface is displayed on the electronic device, and the resource to be edited is the resource uploaded by the user.

3. The online editing method of digital resources according to claim 1, characterized in that: The step of determining the recommended resource content according to the resource information, the user identification information and the hardware information by the AI ​​agent includes: Determining user evaluation information by the AI ​​agent according to the user identification information, wherein the user evaluation information is used to characterize the resource editing ability of the user; Determining hardware evaluation information by the AI ​​agent according to the hardware information, wherein the hardware evaluation information is used to characterize resource content compatibility of the electronic device; The AI ​​agent searches a preset resource content library according to the resource information, the user evaluation information and the hardware evaluation information to obtain the recommended resource content.

4. The online editing method of digital resources according to claim 3, characterized in that: The step of determining the user evaluation information according to the user identification information by the AI ​​agent includes: By means of the AI ​​agent, searching in a preset user database according to the user identification information, the preset user database includes a plurality of registered user identification information and historical resource editing information respectively corresponding to the plurality of registered user identification information; If the registered user identification information identical to the user identification information is retrieved in the preset user database through the AI ​​agent, the user evaluation information is determined according to the historical resource editing information corresponding to the registered user identification information; If no registered user identification information identical to the user identification information is retrieved in the preset user database through the AI ​​agent, reference user evaluation information is determined based on the historical resource editing information corresponding to the multiple registered user identification information, and user evaluation information is determined based on the reference user evaluation information and the preset user evaluation information.

5. The online editing method of digital resources according to claim 3, characterized in that: The preset resource content library includes a variety of resource contents, and different resource contents correspond to resource information and resource content evaluation information respectively, and the resource content evaluation information is used to characterize the difficulty of secondary editing of resource contents. The AI ​​agent searches in the preset resource content library according to the resource information, the user evaluation information and the hardware evaluation information to obtain the recommended resource content, including: By means of the AI ​​agent, searching the preset resource content library according to the resource information to determine candidate resource content, wherein the resource information corresponding to the candidate resource content matches the resource information; Through the AI ​​agent, the recommended resource content is determined from the candidate resource content based on the resource content evaluation information corresponding to the candidate resource content, the user evaluation information and the hardware evaluation information, and the resource content evaluation information corresponding to the recommended resource content matches the user evaluation information and the hardware evaluation information.

6. The online editing method of digital resources according to any one of claims 1 to 5, characterized in that: The AI ​​agent is a networked agent, and the online editing method further includes: Obtain payment information of the user for resource editing; Determining, by the AI ​​agent, whether the content of the recommended resource matches the payment information according to the payment information; In the case that the recommended resource content does not match the payment information, the AI ​​agent searches the Internet according to the recommended resource content to obtain the search resource content, and expands the recommended resource content according to the search resource content to obtain expanded recommended resource content, wherein the expansion of the recommended resource content includes: at least one of an expansion of the quantity of recommended resource content, an expansion of the type of recommended resource content, and an expansion of the quality of recommended resource content.

7. The online editing method of digital resources according to any one of claims 1 to 5, characterized in that: The first resource editing interface includes an AI agent control and an editing function option control, and the second resource editing interface is displayed on the electronic device in response to detecting the use demand of the recommended resource content, including: In response to detecting a triggering operation of the AI ​​agent control by a user, displaying a second resource editing interface on the electronic device; or, In response to not detecting a triggering operation of the editing function option control by the user within a first preset time period, a preset reminder information is displayed in the first resource editing interface, and the preset reminder information is used to indicate that the resource editing auxiliary function is turned on after a second preset time period; in response to detecting an operation of the user on the preset reminder information, and / or not detecting an operation of the user on the preset reminder information within the second preset time period, a second resource editing interface is displayed on the electronic device.

8. The online editing method of digital resources according to any one of claims 1 to 5, characterized in that: The second resource editing interface includes a storage control, and the online editing method further includes: In response to detecting a triggering operation of the storage control by the user, the AI ​​agent determines 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 resource, wherein the storage information is used to characterize the storage mode and storage path of the resource to be stored, wherein the storage mode includes: at least one of direct storage, encrypted storage, and compressed storage; Displaying the storage information; In response to detecting a confirmation operation of the user on the target storage information of the storage information, the resource to be stored is stored according to the target storage information.

9. The online editing method of digital resources according to any one of claims 1 to 5, 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, the AI ​​agent determines 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, wherein the sharing information is used to characterize the sharing method, sharing validity period, content to be shared, and secondary sharing authority of the resource to be shared, wherein the sharing method includes: at least one of direct sharing, encrypted sharing, and compressed sharing; Displaying the shared information; In response to detecting a confirmation operation of the user on target sharing information of the sharing information, the resource to be shared is shared according to the target sharing information.

10. An online editing system for digital resources, characterized in that: include: A display module, used to display a first resource editing interface on the electronic device, wherein the first resource editing interface is a display interface of a resource to be edited; An acquisition module, used 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 the recommended resource content according to the resource information, the user identification information and the hardware information through an AI agent; The display module is further configured to display a second resource editing interface on the electronic device in response to detecting a use requirement of the recommended resource content, wherein 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 performed by the user on the second resource editing interface, displaying the edited resource according to the editing operation.

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