Information display method and device, electronic equipment, storage medium and program product

Abstract

The invention relates to an information display method and device, electronic equipment, a storage medium and a program product. The method comprises the steps of displaying a material analysis page corresponding to a target material; and displaying a first analysis result on the material analysis page, the first analysis result representing first material optimization information of semantic indication of a target comment, and the target comment being a comment corresponding to the target material. The first material optimization information directly mined based on the real feedback (target comment) of the audience of the target material reflects the real demand of the audience, and a creator of the target material can adjust and improve the material in a targeted manner based on the real demand of the audience, so that the material optimization result can be matched with the real demand of the audience, and the user experience is improved. And the material optimization efficiency and the propagation effect are improved, and the time and energy of a creator are saved. Meanwhile, as accurate insight is provided for the needs of audiences, the trial and error of creators can be reduced, and the creation cost is reduced.

Description

Technical Field

[0001] This disclosure relates to the field of computer technology, and in particular to an information display method, apparatus, electronic device, storage medium, and program product. Background Technology

[0002] In the field of content creation and optimization, whether it's short video production, advertising material design, or graphic content editing, the commonly used optimization methods often fail to address the actual needs of users. This results in optimized content that still doesn't match the true needs of the target audience, leading to low optimization efficiency, poor dissemination effects, and a waste of creators' time and energy. Furthermore, due to a lack of precise insight into audience needs, creators often need to make numerous modifications and undergo trial and error, increasing creation costs and potentially affecting the final value of the content by missing the optimal dissemination opportunity. Summary of the Invention

[0003] This disclosure provides an information display method, apparatus, electronic device, storage medium, and program product to solve at least one of the aforementioned technical problems. The technical solution of this disclosure is as follows: According to a first aspect of the present disclosure, an information display method is provided, comprising: Displays the material analysis page corresponding to the target material; On the material analysis page, a first analysis result is displayed. The first analysis result represents the first material optimization information that characterizes the semantic indication of the target comment. The target comment is the comment corresponding to the target material.

[0004] In one exemplary implementation, the first analysis result includes at least one semantic analysis result and at least one first material optimization suggestion information, wherein the semantic analysis result characterizes the strengths, weaknesses, or improvement directions of the target material as indicated by the semantics of the target comment; the first material optimization suggestion information includes at least one of the following: The optimization operation includes: the time point at which the optimization operation is performed on the target material; the position at which the optimization operation is performed on the target material; the optimization direction of the optimization operation; the reference material related to the optimization operation; and the associated material used in the optimization operation.

[0005] In one exemplary embodiment, the method further includes: On the material analysis page, duration suggestion information is displayed. The duration suggestion information includes a reference duration, which is the duration information of industry reference material corresponding to the target material. The industry reference material belongs to the same industry as the target material, and the interaction popularity of the industry reference material meets the preset interaction popularity requirements.

[0006] In one exemplary embodiment, the method further includes: The timeline corresponding to the target material is displayed on the material analysis page. On the timeline, an identifier corresponding to each of the first material optimization suggestion information is displayed. The display position of the identifier on the timeline is determined based on the time point corresponding to the material optimization operation. When any of the aforementioned identifiers is triggered, the display effect of the first material optimization suggestion information corresponding to the identifier is changed.

[0007] In one exemplary embodiment, the method further includes: On the material analysis page, operation controls are displayed for each of the first material optimization suggestion information. The operation controls are used to adopt the corresponding first material optimization suggestion information. The material analysis page displays a control for generating an analysis report; When the analysis report generation control is triggered, a material analysis report is displayed, which includes the first material optimization suggestion information that has been adopted.

[0008] In one exemplary embodiment, the method further includes: On the material analysis page, reference materials corresponding to the first material optimization suggestion information are displayed. These reference materials are from industry reference materials, which belong to the same industry as the target material, and the interaction popularity of the industry reference materials meets the preset interaction popularity requirements.

[0009] In one exemplary embodiment, the method further includes: The timeline corresponding to the target material is displayed on the material analysis page. On the material analysis page, at least one curve is displayed based on the timeline, which is used to indicate the change pattern of the corresponding interactive operation over time.

[0010] In one exemplary embodiment, the at least one curve includes a loss curve, and the method further includes: At the target time position of the churn curve, the corresponding churn analysis information is displayed, which indicates the reason for the churn occurring at the target time position.

[0011] In one exemplary embodiment, the method further includes: The churn analysis information displays optimization controls; When the optimization control is triggered, the storyboard sequence to be optimized and the associated storyboard sequence corresponding to the target time position are displayed. The associated storyboard sequence is a storyboard sequence obtained in response to the reason for the loss at the target time position. Display the storyboard replacement control; When the storyboard replacement control is triggered, the storyboard sequence to be optimized in the target material is replaced with the associated storyboard sequence.

[0012] In one exemplary embodiment, the method further includes: On the material analysis page, the second analysis result corresponding to the target material is displayed. The second analysis result shows the comparison result between the target material and the industry reference material in at least one target dimension. The industry reference material and the target material belong to the same industry, and the interaction popularity of the industry reference material meets the preset interaction popularity requirements. The target dimension refers to the dimension for semantic analysis of the industry reference material.

[0013] In one exemplary embodiment, the method further includes: On the material analysis page, second material optimization information is displayed, which matches the second analysis result.

[0014] In one exemplary embodiment, the second material optimization information includes at least one second material optimization suggestion, each of the second material optimization suggestion pieces of information including an optimization time point, and the method further includes: The timeline corresponding to the target material is displayed on the material analysis page. On the material analysis page, at the position corresponding to the optimization time point in the timeline, a corresponding display element is displayed. The display element is used to indicate the second material optimization information associated with the corresponding position.

[0015] In one exemplary embodiment, the method further includes: When any of the display elements is triggered, corresponding script change information is displayed at the associated location of the display element. The script change information includes script information before the change and script information after the change. The script change information is obtained based on the second material optimization information corresponding to the display element.

[0016] According to a second aspect of the present disclosure, an information display device is provided, comprising: The page display module is configured to execute the material analysis page corresponding to the target material for display; The analysis results display module is configured to execute on the material analysis page to display a first analysis result, wherein the first analysis result represents first material optimization information representing the semantic indication of the target comment, and the target comment is the comment corresponding to the target material.

[0017] In one exemplary implementation, the first analysis result includes at least one semantic analysis result and at least one first material optimization suggestion information, wherein the semantic analysis result characterizes the strengths, weaknesses, or improvement directions of the target material as indicated by the semantics of the target comment; the first material optimization suggestion information includes at least one of the following: The optimization operation includes: the time point at which the optimization operation is performed on the target material; the position at which the optimization operation is performed on the target material; the optimization direction of the optimization operation; the reference material related to the optimization operation; and the associated material used in the optimization operation.

[0018] In one exemplary implementation, the analysis results display module is configured to perform: On the material analysis page, duration suggestion information is displayed. The duration suggestion information includes a reference duration, which is the duration information of industry reference material corresponding to the target material. The industry reference material belongs to the same industry as the target material, and the interaction popularity of the industry reference material meets the preset interaction popularity requirements.

[0019] In one exemplary implementation, the analysis results display module is configured to perform: The timeline corresponding to the target material is displayed on the material analysis page. On the timeline, an identifier corresponding to each of the first material optimization suggestion information is displayed. The display position of the identifier on the timeline is determined based on the time point corresponding to the material optimization operation. When any of the aforementioned identifiers is triggered, the display effect of the first material optimization suggestion information corresponding to the identifier is changed.

[0020] In one exemplary implementation, the analysis results display module is configured to perform: On the material analysis page, operation controls are displayed for each of the first material optimization suggestion information. The operation controls are used to adopt the corresponding first material optimization suggestion information. The material analysis page displays a control for generating an analysis report; When the analysis report generation control is triggered, a material analysis report is displayed, which includes the first material optimization suggestion information that has been adopted.

[0021] In one exemplary implementation, the analysis results display module is configured to perform: On the material analysis page, reference materials corresponding to the first material optimization suggestion information are displayed. These reference materials are from industry reference materials, which belong to the same industry as the target material, and the interaction popularity of the industry reference materials meets the preset interaction popularity requirements.

[0022] In one exemplary implementation, the analysis results display module is configured to perform: The timeline corresponding to the target material is displayed on the material analysis page. On the material analysis page, at least one curve is displayed based on the timeline, which is used to indicate the change pattern of the corresponding interactive operation over time.

[0023] In one exemplary implementation, the at least one curve includes a loss curve, and the analysis results display module is configured to perform: At the target time position of the churn curve, the corresponding churn analysis information is displayed, which indicates the reason for the churn occurring at the target time position.

[0024] In one exemplary implementation, the analysis results display module is configured to perform: The churn analysis information displays optimization controls; When the optimization control is triggered, the storyboard sequence to be optimized and the associated storyboard sequence corresponding to the target time position are displayed. The associated storyboard sequence is a storyboard sequence obtained in response to the reason for the loss at the target time position. Display the storyboard replacement control; When the storyboard replacement control is triggered, the storyboard sequence to be optimized in the target material is replaced with the associated storyboard sequence.

[0025] In one exemplary implementation, the analysis results display module is configured to perform: On the material analysis page, the second analysis result corresponding to the target material is displayed. The second analysis result shows the comparison result between the target material and the industry reference material in at least one target dimension. The industry reference material and the target material belong to the same industry, and the interaction popularity of the industry reference material meets the preset interaction popularity requirements. The target dimension refers to the dimension for semantic analysis of the industry reference material.

[0026] In one exemplary implementation, the analysis results display module is configured to perform: On the material analysis page, second material optimization information is displayed, which matches the second analysis result.

[0027] In one exemplary implementation, the second material optimization information includes at least one second material optimization suggestion, each of the second material optimization suggestion pieces includes an optimization time point, and the analysis result display module is configured to execute: The timeline corresponding to the target material is displayed on the material analysis page. On the material analysis page, at the position corresponding to the optimization time point in the timeline, a corresponding display element is displayed. The display element is used to indicate the second material optimization information associated with the corresponding position.

[0028] In one exemplary implementation, the analysis results display module is configured to perform: When any of the display elements is triggered, corresponding script change information is displayed at the associated location of the display element. The script change information includes script information before the change and script information after the change. The script change information is obtained based on the second material optimization information corresponding to the display element.

[0029] According to a third aspect of the present disclosure, an electronic device is provided, comprising: a processor; and a memory for storing processor-executable instructions; wherein the processor is configured to execute the instructions to implement the information display method described above.

[0030] According to a fourth aspect of the present disclosure, a computer-readable storage medium is provided that, when instructions in the computer-readable storage medium are executed by a processor of an electronic device, enables the electronic device to perform the information display method as described above.

[0031] According to a fifth aspect of the present disclosure, a computer program product is provided, the computer program product including a computer program stored in a readable storage medium, wherein at least one processor of a computer device reads from the readable storage medium and executes the computer program, causing the device to perform the information display method described above.

[0032] The technical solutions provided by the embodiments of this disclosure bring at least the following beneficial effects: The information display method, apparatus, electronic device, storage medium, and program product disclosed herein are applied to an application that displays a material analysis page corresponding to a target material. On the material analysis page, a first analysis result is displayed, representing first material optimization information that semantically indicates a target comment, where the target comment is the comment corresponding to the target material. By mining the semantics of the target comment corresponding to the target material, the application can obtain and display the first material optimization information. The first material optimization information directly mined by the application based on the audience's real feedback (target comments) of the target material reflects the audience's real needs. Creators of the target material can adjust and improve the material in a targeted manner based on these real needs, ensuring that the material optimization results match the audience's real needs, improving material optimization efficiency and dissemination effect, and saving creators' time and effort. Simultaneously, by providing precise insights into audience needs, it reduces the creator's trial-and-error process, thereby lowering creation costs.

[0033] It should be understood that the above general description and the following detailed description are exemplary and explanatory only, and are not intended to limit this disclosure. Attached Figure Description

[0034] The accompanying drawings, which are incorporated in and form part of this specification, illustrate embodiments consistent with this disclosure and, together with the description, serve to explain the principles of this disclosure, and are not intended to unduly limit this disclosure.

[0035] Some of the accompanying drawings in this disclosure are in color. Because this disclosure involves the representation of color, to ensure clarity of expression, while retaining the color drawings, corresponding grayscale drawings are also provided for review purposes.

[0036] Figure 1 This is a schematic diagram of an implementation environment according to an exemplary embodiment.

[0037] Figure 2 This is a flowchart illustrating an information display method according to an exemplary embodiment.

[0038] Figure 3 This is a schematic diagram of a material analysis page according to an exemplary embodiment. Figure 1 .

[0039] Figure 4 This is a schematic diagram of a material analysis page according to an exemplary embodiment. Figure 2 .

[0040] Figure 5 This is a schematic diagram of a material analysis page according to an exemplary embodiment. Figure 3 .

[0041] Figure 6 This is a schematic diagram of a material analysis page according to an exemplary embodiment. Figure 4 .

[0042] Figure 7 This is a block diagram of an information display device according to an exemplary embodiment.

[0043] Figure 8 This is a block diagram illustrating an electronic device for displaying information according to an exemplary embodiment.

[0044] Figure 9 This is another block diagram illustrating an electronic device for displaying information according to an exemplary embodiment. Detailed Implementation

[0045] To enable those skilled in the art to better understand the technical solutions of this disclosure, the technical solutions in the embodiments of this disclosure will be clearly and completely described below with reference to the accompanying drawings.

[0046] It should be noted that the terms "first," "second," etc., used in the specification, claims, and accompanying drawings of this disclosure are used to distinguish similar objects and are not necessarily used to describe a specific order or sequence. It should be understood that such data can be interchanged where appropriate so that the embodiments of this disclosure described herein can be implemented in orders other than those illustrated or described herein. The embodiments described in the following exemplary embodiments do not represent all embodiments consistent with this disclosure. Rather, they are merely examples of apparatuses and methods consistent with some aspects of this disclosure as detailed in the appended claims.

[0047] It should be noted that the user information (including but not limited to user device information, user personal information, etc.) and data (including but not limited to data used for display, data used for analysis, etc.) involved in this disclosure are all information and data authorized by the user or fully authorized by all parties.

[0048] This disclosure proposes that, in the field of material creation and optimization, whether it is short video production, advertising material design, or graphic content editing, the commonly used optimization methods have the following obvious limitations: The optimization is based on a single metric: the optimization of materials relies solely on basic data indicators such as play count, click-through rate, and completion rate, without fully exploring the real needs, feedback, and content expectations contained in user comments. This results in a lack of targeted optimization and difficulty in accurately matching user preferences.

[0049] Blindly controlling the duration: Adjusting the duration of materials relies on the creator's experience or subjective judgment, lacking objectivity. This often results in problems such as users being lost due to excessively long durations or incomplete content expression due to excessively short durations.

[0050] Inefficient content optimization: Lack of high-quality case studies makes it difficult to quickly produce optimized content that meets requirements.

[0051] The optimization results are scattered: the optimization suggestions are mostly fragmented viewpoints, lacking a systematic report presentation, which is not conducive to creators organizing their thoughts and team collaboration in decision-making.

[0052] In summary, the technology proposed in this disclosure fails to deeply integrate user comments, a "high-value feedback data," with material optimization, resulting in a "supply-demand mismatch" problem in material optimization—creators struggle to accurately capture user concerns, and the optimized materials still fail to resonate with the audience, ultimately affecting the content dissemination effect and conversion efficiency.

[0053] From the perspective of technological development trends, the application of artificial intelligence technology in the field of content creation has extended from basic data statistics to deep semantic understanding. User comments, as unstructured data that carries the "true intentions of users," are becoming increasingly valuable. However, the industry currently lacks a technical solution that integrates comment semantic analysis, industry data benchmarking, content generation suggestions, and report output. This results in the inability to effectively transform the value of comment data into precise actionable action for material optimization, creating a technical contradiction between "high-value data being idle" and "urgent optimization needs."

[0054] In view of this, the present disclosure provides a new information display method, which aims to provide innovative design from the following aspects: 1. Comment Semantic Mining: By using artificial intelligence to traverse comments related to the content, semantic mining is performed on these comments to summarize information for content optimization.

[0055] 2. Precise Duration Matching: Compare the duration of the content with that of high-quality, highly interactive content in the same industry, and provide optimization suggestions in the duration dimension.

[0056] 3. Dynamic content generation: Based on the material optimization information, locate the material optimization position and the specific content that needs to be optimized, and provide reference materials based on high-quality and highly interactive materials in the same industry to help users quickly and specifically optimize their materials.

[0057] 4. Flexible decision-making and report output: Users can choose whether to adopt optimization suggestions and generate a systematic material optimization report based on the adoption results.

[0058] Please see Figure 1 The illustration shows an implementation environment provided by an embodiment of the present disclosure. The implementation environment may include at least one information display terminal 110 and an information acquisition server 120, wherein the information display terminal 110 and the information acquisition server 120 can communicate with each other via a network.

[0059] Specifically, the information display terminal 110 interacts with the user through interaction with the information acquisition server 120. Specifically, the information display terminal 110 can display a material analysis page corresponding to the target material; on the material analysis page, a first analysis result is displayed, the first analysis result representing first material optimization information representing the semantic indication of the target comment, where the target comment is the comment corresponding to the target material.

[0060] The information display terminal 110 can communicate with the information acquisition server 120 based on a browser / server (B / S) mode or a client / server (C / S) mode. The information display terminal 110 may include physical devices such as smartphones, tablets, laptops, digital assistants, smart wearable devices, in-vehicle terminals, and servers, and may also include software running on the physical device, such as applications. The operating system running on the information display terminal 110 in this embodiment may include, but is not limited to, Android, iOS, Linux, and Windows.

[0061] The information acquisition server 120 and the information display terminal 110 can establish and display a communication connection through wired or wireless means. The information acquisition server 120 may include an independently operating server, a distributed server, or a server cluster composed of multiple servers, wherein the server may be a cloud server.

[0062] Please refer to Figure 2 The diagram illustrates a flowchart of an information display method in an exemplary embodiment of this disclosure. The execution subject of this method can be the aforementioned information display terminal. Please refer to [link / reference] for details. Figure 2 The method may include: S210. Display the material analysis page corresponding to the target material.

[0063] This disclosure can be applied to applications for creating, analyzing, publishing, and interacting with source materials. Target material refers to any material within the application. This disclosure does not limit the type of target material; for example, it can be at least one of text, images, graphic-text combination, video, and audio.

[0064] This disclosure does not limit the timing of S210 execution. For example, when a creator explicitly selects a piece of material they are creating in the application and triggers the "analysis" command, such as clicking the "analyze material" button, the application will execute S210 immediately after completing the analysis of the target material and display the generated material analysis page to the user. Alternatively, during the user's material creation process, the application can analyze the target material being created in real time or semi-automatically and display the material analysis page when certain conditions are met, such as when the user pauses editing for more than a preset time or switches to a specific "analysis view" mode.

[0065] S220. On the material analysis page, a first analysis result is displayed. The first analysis result represents the first material optimization information that characterizes the semantic indication of the target comment. The target comment is the comment corresponding to the target material.

[0066] The first analytical result of this disclosure is based on semantic analysis of the target comments. For example, the application can use an artificial intelligence model to perform semantic parsing and semantic mining on all or part of the comments targeting the target material, thereby obtaining first material optimization information. The purpose of this design is to effectively transform the value of comment data into precise actionable material optimization, resolving the technical contradiction between "high-value data being idle" and "urgent optimization needs."

[0067] This disclosure does not limit the semantic parsing and semantic mining operations performed by the artificial intelligence model, and this does not constitute a technical obstacle. For example, the artificial intelligence model can first perform text preprocessing on the target comment, including removing irrelevant symbols, performing word segmentation and part-of-speech tagging, etc., and then use a word vector model to convert the text into a computer-recognizable vector form. Then, it can perform deep mining on the vector data to extract the sentiment, key opinions, and specific suggestions from the comment. For instance, if the target material is a food preparation video, and some comments mention that "the steps are explained too quickly, and beginners can't keep up," the artificial intelligence model can identify the key dimension of "step explanation speed" and the negative sentiment expressed by "too fast" through semantic parsing, and transform it into specific first-material optimization information such as "suggest slowing down the step explanation speed and increasing the time spent on key steps," so that the creator can clearly understand the targeted improvement directions that can be obtained from the comments.

[0068] The information display method disclosed herein is applied to an application that displays a material analysis page corresponding to a target material. On this material analysis page, a first analysis result is displayed, representing first material optimization information that semantically indicates a target comment, where the target comment is the comment corresponding to the target material. By mining the semantics of the target comment corresponding to the target material, the application can obtain and display the first material optimization information. The first material optimization information directly mined by the application based on the audience's real feedback (target comments) of the target material reflects the audience's real needs. Creators of the target material can then adjust and improve the material in a targeted manner based on these real needs, ensuring that the material optimization results match the audience's real needs, improving material optimization efficiency and dissemination effectiveness, and saving creators' time and effort. Simultaneously, by providing precise insights into audience needs, it reduces the creator's trial-and-error process, thereby lowering creation costs. This disclosure does not limit the specific content of the first analysis result. In an exemplary embodiment, the first analysis result includes at least one semantic analysis result and at least one first material optimization suggestion information. The semantic analysis result characterizes the advantages, disadvantages, or improvement directions of the target material as indicated by the semantics of the target comment. The first material optimization suggestion information includes at least one of the following: material optimization operation, the time point corresponding to the material optimization operation in the target material, the position corresponding to the material optimization operation in the target material, the optimization direction corresponding to the material optimization operation, the reference material related to the material optimization operation, and the associated material used in the material optimization operation.

[0069] The semantic analysis results disclosed herein can be used to clearly reveal at least one of the following three aspects of information about the target material that are semantically implied in the target comment: The strengths of the target material, which are the aspects mentioned in the target comments that make the material well-made and popular; The weaknesses of the target material, namely the shortcomings and deficiencies that need to be improved pointed out in the target comments; The direction for improvement usually refers to suggestions, directly or indirectly, made in the target comments regarding which aspects of the material should be adjusted or improved.

[0070] For example, suppose the target material is a short video introducing a "smart home system." If a viewer comments, "The beginning of the video clearly introduces the product functions, making it easy to understand at a glance. However, the demonstration in the middle is too fast, making it difficult to see the steps. I hope it can be slowed down or explained step by step," then the semantic analysis result for this comment might be: "Strengths: The product function introduction at the beginning of the video is clear; Weaknesses: The demonstration in the middle is too fast, making it difficult for viewers to see the steps; Improvement directions: Slow down the demonstration speed or use a step-by-step explanation method." The strengths, weaknesses, and improvement directions here are the core viewpoints extracted from the semantics of the target comment.

[0071] The first material optimization suggestions disclosed herein are more specific and actionable. Based on the semantic analysis results, they provide further practical guidance on how to optimize the material. It may include at least one of the following: Material optimization operations: Clearly specify the specific modifications to be performed. For example, in response to the semantic analysis result of "the demonstration operation is too fast", the corresponding material optimization operations might be "slow down the playback speed of the demonstration operation video clip" or "edit the demonstration operation video clip into segments, adding pauses and explanations between steps".

[0072] The timing point at which the optimization operation should be performed on the target material: If the material is sequential, such as video, audio, or animated graphics, then it is necessary to specify the specific time point in the material at which the optimization operation should be performed. Continuing with the smart home video example above, assuming the operation demonstration starts at the 30th second of the video, then the suggested time point might be "at the 30th second of the video".

[0073] The location corresponding to the material optimization operation within the target material: If the material is static or spatially distributed, such as an image or graphic layout, then the specific spatial location of the optimization operation needs to be specified. For example, if the target material is a promotional poster, and a comment points out that "the product image is too small and not eye-catching," then the corresponding location for the optimization operation might be "the product image in the upper center of the poster," and the suggested operation might be "enlarge the size of the product image in that area."

[0074] The optimization directions corresponding to the material optimization operations are somewhat related to the "improvement directions" in the semantic analysis results, but focus more on the goals of the operation itself. For example, the optimization direction corresponding to the operation of "slowing down the playback speed of the demonstration operation video clip" is "improving the clarity and understandability of the operation demonstration".

[0075] Reference materials related to the optimization operation: To help creators better understand how to perform the optimization operation, relevant reference cases or templates can be provided. For example, for the optimization operation of "explaining the operation step by step", a "video clip demonstrating the operation steps of an excellent product" can be provided as reference material, and creators can learn from its rhythm, expression style, etc.

[0076] The associated materials used in the material optimization operation refer to other auxiliary materials that may be needed when performing the optimization operation. For example, if the optimization suggestion is "add text explanation subtitles to the operation demonstration steps", then the "associated materials" may include recommended subtitle fonts, font sizes, color schemes, or a preset subtitle template file.

[0077] In summary, this disclosure refines the initial analysis results into semantic analysis results and specific optimization suggestions, making the information mined from the semantics of target comments highly intuitive and actionable. By showcasing the details of the initial analysis results, creators can "identify problems" (strengths, weaknesses, and directions for improvement), while the initial material optimization suggestions further point to "how to solve the problems" (specific actions, timing / location, direction, references, and related materials). This makes the entire material optimization process smoother and more efficient. Furthermore, because the optimization suggestions are precise down to actions, timing, and location, creators can accurately pinpoint where the material needs modification, avoiding blind modifications and improving optimization effectiveness. These optimization suggestions come directly from the audience's real comments (target comments), so material optimization based on these suggestions can more accurately align with the audience's preferences and needs, making the optimized material more likely to gain audience recognition and favor, thereby increasing the material's reach and influence.

[0078] Please refer to Figure 3 It illustrates a material analysis page in an exemplary embodiment of this disclosure. Figure 1 The "Comment Insights" tab on the material analysis page displays the first analysis result 310. This first analysis result 310 includes "AI Comment Intent Type," the content of which belongs to the semantic analysis result 311 within the first analysis result 310. Furthermore, this "AI Comment Intent Type" also includes a "View Full Text" control 312, used to display the full text of its corresponding semantic analysis result 311. The "Comment Insights" tab also displays a comment list 320, which includes information such as the user's nickname, posting time, hidden status, number of likes, comment level, and comment content for each target comment related to the target material. Users can search for target comments in the comment list 320.

[0079] In one exemplary embodiment, the method further includes: displaying a timeline corresponding to the target material on the material analysis page; and displaying at least one curve on the material analysis page based on the timeline, the curve being used to indicate the changing pattern of the corresponding interactive operation over time.

[0080] The timeline in this disclosure can be presented linearly on the material analysis page, with the horizontal axis representing the time dimension. Taking short video materials as an example, it is usually accurate to the second. The starting point of the timeline can be from 0 seconds to the end time of the short video material. This disclosure does not limit the interactive operation, which can include various interactive behavior data performed by users on the target material, such as likes, comments, shares, favorites, and churn. Each curve can correspond to a type of interactive operation. For example, the blue curve represents the change in likes over time, and the red curve represents the trend of comment changes. Different colors or line types of curves allow users to intuitively distinguish the dynamic patterns of different interactive operations. Please refer to [reference needed]. Figure 3 It includes a first curve showing how churn rate changes over time, and a second curve showing how many comments change over time.

[0081] This disclosure, through its design, enables creators to more clearly grasp the user engagement levels of target content at different points in time. For example, it allows for quick identification of which segments of a short video generated concentrated likes or comments, and which segments saw a significant drop in engagement, thus accurately pinpointing highlights or potential areas for optimization within the content. Furthermore, by combining specific time scales on the timeline, creators can correlate fluctuations in interaction data with the rhythm and plot changes of the content itself, conducting in-depth analysis of the relationship between user behavior and content presentation. This provides data-driven decision-making support for subsequent content creation and optimization, effectively enhancing the relevance and appeal of content production.

[0082] Please refer to Figure 4 It illustrates a material analysis page in an exemplary embodiment of this disclosure. Figure 2 The "AI Material Suggestion Distribution" section on the material analysis page displays multiple AI material suggestions, all of which belong to the first material optimization suggestion information 410 in the aforementioned first analysis results.

[0083] In one exemplary embodiment, the method further includes: displaying duration suggestion information on the material analysis page, the duration suggestion information including a reference duration, the reference duration being the duration information of an industry reference material corresponding to the target material, the industry reference material belonging to the same industry as the target material, and the interaction popularity of the industry reference material meeting a preset interaction popularity requirement.

[0084] The suggested duration information is a reference guide for creators regarding the duration of target content, based on industry data. The core content is the suggested duration, designed to help creators match the duration patterns of highly interactive content within the industry. The suggested duration refers to the duration information of industry reference materials corresponding to the target material. Industry reference materials are a collection of high-quality materials belonging to the same industry as the target material and whose interaction popularity reaches a preset standard. This disclosure does not limit interaction popularity or preset interaction popularity requirements. For example, interaction popularity can be measured by a single indicator or a weighted combination of multiple indicators such as likes, comments, shares, favorites, play completion rate, viewing time, number of shares, and follower conversion rate. The preset interaction popularity requirement can be flexibly set according to different industries, platform characteristics, or content types. For example, for newly launched content platforms, the preset interaction popularity requirement may be set to 1.2 times the average interaction popularity of similar materials on the platform to encourage the production of high-quality content; for mature content platforms, the preset interaction popularity requirement may be specified as a single material having more than 10,000 likes and more than 500 comments.

[0085] For example, suppose an educational content creator uploads a 15-minute "Python Basic Syntax" tutorial video (target material). When displaying suggested duration information on the material analysis page, it first filters out industry reference materials (possibly including 100 similar high-quality videos) within the "Programming Instruction" subcategory of the education industry that meet preset interaction popularity requirements (e.g., completion rate ≥ 55%, number of favorites ≥ 2000) and calculates the average or mode of these materials' durations, resulting in a suggested duration of "8-10 minutes". At this point, the suggested duration information will display: "Based on the analysis of highly interactive programming instruction materials in the education industry, the suggested duration is 8-10 minutes (current material duration is 15 minutes)."

[0086] This design reveals audience preferences for content length across different industries. By showcasing reference lengths, creators can quickly pinpoint a reasonable length range without repeated testing, providing them with direction for time-based optimization.

[0087] Please refer to Figure 4 The "Overall Duration Suggestions" section on the content analysis page displays suggested duration information (420). This "Overall Duration Suggestions" includes not only a reference duration but also the duration of the target content, allowing creators to optimize their target content through duration comparison. Please refer to... Figure 4 , and Figure 3 Similarly, it also includes the first curve showing the churn rate changing over time, and the second curve showing the number of comments changing over time. Therefore, creators in Figure 4 When viewing the overall duration suggestions and AI-suggested material distribution, you can also refer to the first and second curves.

[0088] In some implementations, the content optimization suggestions are determined based on the semantic analysis results and the time-based suggestions. That is, in addition to obtaining content optimization information through semantic analysis results, time-based suggestions can be referenced to further improve the quality of the content optimization information, so that the final optimized target content not only enhances its appeal to users in terms of content but also aligns with user preferences in terms of timing.

[0089] In one exemplary embodiment, the method further includes: displaying a timeline corresponding to the target material on the material analysis page; displaying an identifier corresponding to each first material optimization suggestion on the timeline, wherein the display position of the identifier on the timeline is determined based on the time point corresponding to the material optimization operation; and changing the display effect of the first material optimization suggestion corresponding to the identifier when any of the identifiers is triggered.

[0090] For example, when the first curve shows a significant increase in churn rate within a certain time period, while the second curve shows abnormal fluctuations in comment volume during that period, a prominent indicator, such as a red exclamation mark, can be generated at the corresponding position on the timeline to alert the creator that the segment may have issues such as insufficient content appeal or a sluggish pacing. These indicators are closely linked to specific content optimization operations. For instance, when a creator clicks on the red exclamation mark, the first content optimization suggestion associated with the available optimization operation at that location can be displayed. Different types of content optimization operations correspond to different display styles of indicators; for example, a suggestion to "add fun elements" might use a yellow star icon, while a suggestion to "adjust background music" might use a blue musical note icon. The benefits of this design are as follows: Through intuitive visual markers on the timeline, creators can quickly locate specific time points in the target material that require optimization, avoiding the tedious process of searching for problems frame by frame in lengthy videos or audio, thus greatly improving analysis efficiency. The linked display of markers and optimization operations allows creators to obtain corresponding improvement directions as soon as they see the markers, forming a closed loop of "identifying problems - obtaining solutions," reducing the creator's thinking costs and operational path. Different display styles of markers help creators quickly distinguish and categorize various optimization suggestions. For example, urgent and important modification suggestions are marked in red, while routine improvement suggestions are marked in yellow, allowing creators to adjust the material in an orderly manner according to priority, further improving the targeting and effectiveness of material optimization.

[0091] Please continue to refer to this. Figure 4 , Figure 4The symbols “1”, “2”, and “3” correspond to the first, second, and third optimization suggestions for the first material, respectively. If the creator clicks on symbol “1”, the first optimization suggestion for the first material can be changed from the original background color 1 to background color 2, thereby triggering a linked display.

[0092] In some implementations, the method further includes: displaying an operation control corresponding to each of the first material optimization suggestion information on the material analysis page, the operation control being used to adopt the corresponding first material optimization suggestion information; displaying an analysis report generation control on the material analysis page; and displaying a material analysis report when the analysis report generation control is triggered, the material analysis including the adopted first material optimization suggestion information.

[0093] For each primary creative optimization suggestion, a corresponding action control can be configured. This control allows creators to explicitly adopt the suggestion. Additionally, an analysis report generation control will be displayed on the page. After a creator adopts an approved primary creative optimization suggestion based on their needs, triggering (e.g., clicking) this analysis report generation control will automatically summarize the information and display a "Creative Analysis Report." This report contains all primary creative optimization suggestions adopted by the creator and may also include summaries, statistics, or further guidance based on these adopted suggestions.

[0094] For example, suppose a creator is analyzing a 10-minute instructional video clip. The timeline on the clip analysis page displays multiple optimization suggestions for the first clip, such as: 1. Suggestion 1 (marked "1"): "00:01:20-00:01:35 The speaking speed here is too fast. It is recommended to adjust the speaking speed to XXX." The corresponding operation control is the "Accept this suggestion" button.

[0095] 2. Recommendation 2 (marked "2"): "Slight shaking occurs in the image from 00:03:10 to 00:03:20. It is recommended to implement image stabilization." The corresponding control is the "Accept this recommendation" button.

[0096] 3. Recommendation 3 (marked "3"): "00:05:00 It is recommended to add the subtitle 'XXX knowledge point'." The corresponding operation control is the "Accept this suggestion" button.

[0097] After carefully reading the suggestions, the creator deemed suggestions 1 and 3 valuable and clicked the "Accept this suggestion" button next to each. These two suggestions will likely be marked as "Accepted." The creator, however, felt suggestion 2 would have little impact and did not click its button.

[0098] When the creator clicks the "Generate Analysis Report" button (i.e., the analysis report generation control) at the bottom of the page, a "Teaching Video Material Analysis Report" is generated and displayed. Under the "Adopted Optimization Suggestions" section, the following is clearly listed: Marker "1": "00:01:20-00:01:35 The speaking speed here is too fast. It is recommended to adjust the speaking speed to XXX." (Adopted) Marker "3": "00:05:00 Suggestion to add subtitle 'XXX knowledge point'." (Adopted) The report may also include information such as "two recommendations were adopted".

[0099] The control settings make creators' adoption of optimization suggestions explicit and recordable. This avoids creators simply memorizing or manually recording which suggestions were adopted, reducing the possibility of forgetting or confusion. Through the adoption process, creators can focus only on the adopted parts, improving revision efficiency. The introduction of the analysis report generation control allows scattered adopted suggestions to be automatically summarized into structured analysis reports. The material analysis report includes adopted suggestions, allowing creators or relevant personnel to quantitatively analyze the quantity, type, and distribution of adopted suggestions. For example, "This video adopted X suggestions regarding audio and Y suggestions regarding visuals," forming a closed loop of "receiving suggestions - adopting suggestions - generating reports," reducing the workload of manual sorting and summarizing. The generated report is based on the creator's actual adoption status, thus possessing high personalization and relevance, truly reflecting the creator's specific thinking on material optimization.

[0100] Please continue to refer to this. Figure 4 , Figure 4 The labels “1”, “2”, and “3” correspond to the first, second, and third optimization suggestions for the first material, respectively. Next to each optimization suggestion, there is a corresponding adoption control 430. Creators can adopt the corresponding optimization suggestion by clicking the adoption control 430. Then, at the bottom of the page, there is an analysis report generation control 440. Clicking the analysis report generation control 440 will generate a material analysis report.

[0101] In some implementations, the method further includes: displaying reference materials corresponding to the first material optimization suggestion information on the material analysis page, wherein the reference materials are from industry reference materials, the industry reference materials belong to the same industry as the target material, and the interaction popularity of the industry reference materials meets the preset interaction popularity requirements.

[0102] When presenting creators with initial material optimization suggestions on the material analysis page, you can also display related reference materials. Please continue to refer to these materials. Figure 4 , Figure 4 Next to each optimization suggestion for the first creative material is a list of 450 reference materials. These reference materials are not randomly selected, but rather drawn from high-quality materials within the industry. The criteria for judging high-quality industry materials are that they are from the same industry and meet preset interaction and popularity requirements, such as high likes, high comments, high shares, or high completion rates. This ensures that the reference materials themselves have a certain degree of market recognition and user appeal. In this way, when creators see optimization suggestions, they can intuitively refer to cases that have been successfully validated in the market within the same industry, thereby better completing the optimization.

[0103] This disclosure further uses the optimization of short video materials for the promotion of "foundation" in the beauty industry as an example to explain in detail the specific implementation process of this disclosure: Step 1: Comment Collection and Analysis The creator uploaded a short promotional video for a foundation (original length 45 seconds) to be optimized, and 1200 user comments on the video were automatically collected. Natural language processing analysis revealed that: 35% of the comments mentioned "wanting to see the makeup effect on different skin types" (positive demand), 28% of the comments reported "unclear explanation of coverage" (information gaps), and 12% of the comments felt the "product display at the beginning was redundant" (content reduction requirement). The first analysis results can include three optimization suggestions for the primary source material, each pointing to one of three core points: "supplementing the makeup effect on multiple skin types," "refining the coverage explanation," and "removing redundant content at the beginning."

[0104] Step 2: Duration Matching and Target Determination Data from high-click-through-rate creatives in the beauty industry shows that the optimal video length for this type of product promotion is 60-90 seconds, with an average length of 75 seconds. Considering the need to add two core elements—"effects on multiple skin types" and "coverage demonstration"—the target length is calculated to be 70 seconds. This requires adding 25 seconds of content to the original 45 seconds, while also removing the first 5 seconds of redundant product display footage.

[0105] Step 3: Content Optimization and Case Matching Using an AI model based on the video's narrative logic (introduction - product's core selling points - effect demonstration - purchase guidance), the following optimization suggestions were provided for the first video clip: Add 20 seconds of content at 15 seconds (after the product's core ingredients) to showcase the makeup effect and coverage comparison for dry, oily, and combination skin, accompanied by the statement "dry skin won't feel dry, oily skin will have 8 hours of wear"; add 5 seconds of content at 35 seconds to demonstrate the coverage power through real-world testing of "covering acne scars / redness"; and remove the rotating product display from the first 0-5 seconds. Additionally, three highly viewed videos on "multi-skin type foundation reviews" (each with over 500,000 views) were found, generating a list of reference materials for creators to consider in terms of shooting style and wording.

[0106] Step 4: User Interaction and Solution Confirmation Creators can view the optimization suggestions for the first source material above, check the "Accept" box, and receive real-time updates to the optimization plan.

[0107] Step 5: Optimize report generation Based on the confirmed plan, a relevant report will be generated, which will include a summary of the original video's problems, core conclusions of the comment analysis, target duration and adjustment basis, specific optimization content and location, 3 reference case links and expected results (expected click-through rate increase of 30%+). Creators can use the report to complete video shooting and editing optimization.

[0108] In one exemplary embodiment, the at least one curve includes a churn curve, and the method further includes: displaying corresponding churn analysis information at a target time position on the churn curve, the churn analysis information indicating the reason for the churn occurring at the target time position.

[0109] On the churn curve, when a specific "target time point" is located—usually a specific point in time or time period where significant churn occurs (such as a sudden increase in churn volume or a sharp rise in churn rate)—corresponding churn analysis information can be displayed at that location. The core function of this "churn analysis information" is to clearly indicate or explain why churn occurred at that "target time point," that is, to analyze and present the specific reasons that led to the churn. Through this design, creators no longer need to manually search for or analyze reasons elsewhere; they can quickly and directly understand the driving factors behind the churn phenomenon, greatly improving optimization efficiency.

[0110] Please refer to Figure 5 This is a schematic diagram of a material analysis page according to an exemplary embodiment of this disclosure. Figure 3 .exist Figure 5 In (a), the content analysis page displays "AI analysis of churn reasons," which is churn analysis information obtained automatically by AI artificial intelligence. In addition, this page can also display a lot of consumption and conversion data related to the target content, so that creators can understand various information related to the target content.

[0111] In an exemplary embodiment, the method further includes: displaying an optimization control in the churn analysis information; when the optimization control is triggered, displaying the storyboard sequence to be optimized corresponding to the target time position and the associated storyboard sequence corresponding to the target time position, wherein the associated storyboard sequence is a storyboard sequence obtained for the reason of churn at the target time position; displaying a storyboard replacement control; when the storyboard replacement control is triggered, replacing the storyboard sequence to be optimized in the target material with the associated storyboard sequence.

[0112] For example, suppose a creator is analyzing footage from a short cooking tutorial video. The video experiences a significant drop-off at the 45-second mark. AI analysis determines the cause is "overly lengthy and monotonous demonstrations of ingredient preparation steps." At this point, an "Optimize this segment" control will be displayed in the drop-off analysis information. When the creator clicks this control, the system automatically navigates to the target time point of 45 seconds, displaying the corresponding storyboard sequence to be optimized—a 10-second combination of "close-ups of chopping vegetables + a single fixed shot" from the original video. It also displays a related storyboard sequence—a combination of "rapidly edited multi-angle chopping scenes + close-ups of the chef's hand movements + close-ups of changes in ingredient states," generated by the AI ​​based on the drop-off cause. Key information such as segment duration and shot type is labeled below both sequences. Simultaneously, a "Replace Storyboard Sequence" control is displayed. After comparing the effects of the two storyboard sequences, clicking this control will automatically replace the original video's 45-55 second segment with the new related storyboard sequence, resulting in optimized video footage.

[0113] This design eliminates the need for creators to repeatedly switch between analysis reports and video editing tools. They can directly trigger precise optimizations at the storyboard level through controls, significantly reducing operational complexity. Furthermore, the strong correlation between the associated storyboard sequence and the reasons for churn ensures the accuracy of the optimization direction, avoiding blind trial and error. Through the comparison and display of storyboard sequences, creators can further filter or adjust the associated storyboards recommended by AI based on their own creative style, improving efficiency while taking into account the personalized needs of content creation.

[0114] Click Figure 5 (a) The "One-Click Optimization" button in "AI Analysis of Churn Reasons" can be seen in the following example. Figure 5(b) The material analysis page displays the storyboard sequence 510 to be optimized, AI-optimized content 520, related storyboard sequence 530, and storyboard replacement control 540. AI-optimized content 520 explains what aspects of the related storyboard sequence 530 have been optimized compared to the storyboard sequence 510, and why, to help creators clearly understand the optimization logic and basis of the related storyboard sequence 530. For example, when the reason for churn is "monotonous visuals leading to user distraction," AI-optimized content 520 will specifically explain: "The related storyboard sequence 530 replaces the single fixed shot (10 seconds) in the original sequence with rapid switching between three different angles (a top-down shot of the cutting board, a 45-degree angle shot of the chef's hand holding the knife, and a close-up of the moment the ingredients are sliced) (each shot lasting 0.8-1.2 seconds), increasing the amount of information and dynamism in the visuals, thereby enhancing user viewing interest." In this disclosure, both AI-optimized content 520 and related storyboard sequence 530 can be automatically generated by artificial intelligence models; this process is not limited and does not constitute an obstacle to implementation. In some implementations, the associated storyboard sequence 530 is determined based on the churn analysis information, the duration information of the industry reference material, and the industry reference material itself. The industry reference material and the target material belong to the same industry, and the interaction popularity of the industry reference material meets the preset interaction popularity requirements.

[0115] Next, this disclosure will use the example from the previous text to explain in detail the specific implementation process of this disclosure: Step 1: Churn Peak Time Series Analysis The playback behavior data of the short video promoting the foundation was retrieved (covering 12,000 complete plays and 35,000 mid-play exits). The time-series churn analysis model automatically located the following: the first churn peak was at 10 seconds of the original video (the beginning of the product ingredient introduction), with a churn rate of 42%; the second churn peak was at 25 seconds (the single dry skin makeup demonstration segment), with a churn rate of 38%.

[0116] Step 2: Extracting storyboards and determining causes of loss Pulling out the storyboards corresponding to these two peaks—the 10-second segment is a pure text ingredient list segment, and the 25-second segment is a static shot showing only dry skin applying makeup; combined with the previous comment analysis conclusion (35% of users need multi-skin type effects), the reasons for churn were determined to be "boring storyboard content" and "narrow skin type coverage".

[0117] Step 3: Simultaneously generate long replacement materials AI matches high-click content from the beauty industry's content library and generates replacement content of the same duration as the original storyboard: At 10 seconds, the scene is changed to 3 seconds: the pure text is replaced with "dynamic animation + real voice narration" to demonstrate the working principle of "makeup-holding factors + skin-nourishing essence", accompanied by the words "makeup-holding and skin-nourishing at the same time, dry skin will not have powder cake". At 25 seconds, a 5-second scene is replaced: dynamic makeup application footage of oily and combination skin is added, simultaneously demonstrating the real-world test results of "oily skin makeup lasting 8 hours without fading" and "combination skin T-zone without patchiness".

[0118] Step 4: Replace interaction with one click Show a preview clip of the replacement material (related to the storyboard sequence), labeled with "Original Storyboard Loss Rate" and "Estimated Retention Rate After Replacement (Increase of 20%+)"; after the user confirms the requirements, click the "One-Click Replacement" button (storyboard replacement control) to complete the replacement.

[0119] In one exemplary embodiment, the method further includes: displaying a second analysis result corresponding to the target material on the material analysis page. The second analysis result shows the comparison result between the target material and the industry reference material in at least one target dimension. The industry reference material and the target material belong to the same industry, and the interaction popularity of the industry reference material meets a preset interaction popularity requirement. The target dimension refers to the dimension for semantic analysis of the industry reference material.

[0120] The second analysis result involves a multi-dimensional comparison of the target materials with industry reference materials, presenting the results. Industry reference materials are high-quality samples of materials within the industry that have been market-tested and have high user attention and engagement. The target dimensions are key evaluation indicators extracted through semantic analysis of these popular industry reference materials. These dimensions reflect the core elements of the industry's materials in terms of content creation and user attraction. For example, potential target dimensions for the beauty industry might include "product efficacy demonstration method," "skin type coverage," "visual presentation format," and "compelling appeal." Please refer to [the provided text]. Figure 6 This is a schematic diagram of a material analysis page according to an exemplary embodiment of this disclosure. Figure 4 . Figure 6 The result shown in the "Comparative Analysis of Viral Videos" is the second analysis result 610.

[0121] By showcasing a detailed comparison between target content and industry benchmark content across key target dimensions on the content analysis page, users can clearly see the gaps and advantages of the target content compared to industry best practices in each core element. This provides users with a clear direction for optimization based on the secondary analysis results. Users are no longer judging the quality of content based on subjective experience, but can accurately pinpoint the shortcomings of the target content in core elements based on objective industry data and key dimension comparisons, avoiding blind optimization. Since industry benchmark content itself is a high-quality sample with high engagement, the target dimensions derived from its semantic analysis represent content characteristics that are widely accepted and liked by users in the current industry. Users can adjust their content based on the comparison results of these dimensions, allowing them to more quickly approach industry best practices, reduce trial-and-error costs, and increase the interactive potential of the optimized content. By intuitively displaying the differences between the target content and industry benchmarks in each key dimension, users can have a relatively clear expectation of the effects of content optimization, which helps them make more reasonable optimization decisions.

[0122] In one exemplary embodiment, the method further includes: displaying second material optimization information on the material analysis page, the second material optimization information matching the second analysis result. Please refer to... Figure 6 The AI ​​video optimization suggestion 620 refers to the optimization information for this second source material. This optimization information can include the purpose of modification, the original content, and modification suggestions. By displaying optimization information for second source materials that matches the results of the second analysis on the source material analysis page, such as the purpose of modification, the original content, and modification suggestions, creators can improve their understanding and efficiency in optimizing source materials.

[0123] In one exemplary embodiment, the second material optimization information includes at least one second material optimization suggestion information, each of the second material optimization suggestion information including an optimization time point, and the method further includes: displaying a timeline corresponding to the target material on the material analysis page; and displaying a corresponding display element at the position corresponding to the optimization time point on the timeline on the material analysis page, the display element being used to indicate that the corresponding position is associated with the second material optimization information.

[0124] The second-level material optimization suggestion information includes an optimization time point, which precisely indicates the specific moment or time period within the target material (e.g., a video clip) that requires optimization. The timeline on the material analysis page resembles a visual progress bar, intuitively reflecting the overall duration of the material and the sequence of its various parts. Then, at the specific location corresponding to the optimization time point on this timeline, a corresponding display element is shown. This display element can be diverse, such as a special icon (e.g., a small flag, exclamation mark, pencil icon), a different colored marker, a flashing highlighted area, or a label with prompt text. The core function of this display element is to indicate the connection between the corresponding location and the second-level material optimization information. In other words, when a user sees this display element on the timeline, they immediately understand that there is a relevant optimization suggestion at that specific point in time. Users can typically view this specific second-level material optimization information, such as the purpose of modification, the original content, and the modification suggestion, through interactive methods like clicking or hovering. By optimizing the combination of time points and display elements on the timeline, abstract optimization suggestions are directly anchored to specific time positions in the footage. This avoids users aimlessly searching for segments that need optimization within long clips, ensuring that users can accurately pinpoint the problem and make precise modifications, greatly improving the targeted nature of optimization work. Creators no longer need to manually locate text suggestions within the footage; instead, they can quickly jump to the relevant time points for viewing and editing directly through the display elements on the timeline. This "what you see is what you get" approach reduces user steps and cognitive burden, saves time, and significantly improves the efficiency and overall experience of optimizing footage. Furthermore, the timeline provides a global perspective on the footage, while the display elements guide users to focus on local optimization points. This combination allows users to understand the overall distribution of optimizations in the footage while easily focusing on specific optimization details, helping them balance overall effects and local improvements during modifications.

[0125] In one exemplary embodiment, the method further includes: when any of the display elements is triggered, displaying corresponding script change information at the associated position of the display element, the script change information including script information before the change and script information after the change, the script change information being obtained based on the second material optimization information corresponding to the display element.

[0126] When a user triggers any display element on the timeline (which corresponds to a specific time point requiring optimization and related secondary material optimization information), the corresponding script change information is automatically displayed in a location associated with that element (e.g., the area near the element, a specific information panel below the timeline, or a pop-up floating window). This script change information clearly presents two key parts: "script information before the change" and "script information after the change." The "script information before the change" refers to the script content or related weaknesses of the target material at that time point before optimization adjustments; the "script information after the change" is based on the related secondary material optimization information, showing the script content or related improvement directions after overcoming the weaknesses. In this way, users can intuitively see the specific details of the script changes from its original state to its optimized state, improving the transparency and understandability of script modifications.

[0127] Please refer to Figure 6 There are multiple optimization time points in the timeline, and these optimization time points all display the relevant display element 630. In addition, after the display element is triggered, the script change information 640 associated with the display element 630 is also displayed.

[0128] Next, this disclosure will use the example from the previous text to explain in detail the specific implementation process of this disclosure: Step 1: Deconstruct and analyze the formulas of best-selling products in the same industry We retrieved high-click content from the beauty industry over the past 30 days (covering 500+ viral videos) and used AI to analyze the core formula for viral hits: "pain point scenarios + visualized efficacy + multi-skin type verification." At the same time, we identified the gaps in the current videos: the lack of "pain point pre-revelation" and "dynamic efficacy demonstration" segments.

[0129] Step 2: Script Comparison and Generation AI generates storyboards before and after modification based on the formula for creating viral content: Script before modification (at 10 seconds): A plain text list of "makeup-holding factor ingredients"; Modified script (at 10 seconds): Replace with a screen showing the pain point of "oily skin causing makeup to come off and become patchy" + dynamic animation demonstrating the principle of "makeup-holding factors filling pores", accompanied by the statement "oily skin in summer? Makeup-holding factors lock in the foundation and prevent it from becoming patchy".

[0130] Step 3: Modify the timeline markers Mark all modification points (optimization points) (such as at 10 seconds and 25 seconds) with colored dots (display elements) at the corresponding positions on the timeline below, and associate each dot with the modification point of the corresponding storyboard.

[0131] Step 4: Quickly expand and collapse the interaction Users can click on a marker on the timeline to expand the specific modification suggestions for that location with one click (including script comparison, explanation of best-selling formula matching, i.e., script change information); clicking again will collapse the content, helping users quickly locate and view the modification details.

[0132] Figure 7 This is a block diagram illustrating an information display device according to an exemplary embodiment. (Refer to...) Figure 7 The device includes: Page display module 710 is configured to execute the material analysis page corresponding to the target material; The analysis result display module 720 is configured to execute on the material analysis page to display a first analysis result, wherein the first analysis result represents first material optimization information representing the semantic indication of the target comment, and the target comment is the comment corresponding to the target material.

[0133] In one exemplary implementation, the first analysis result includes at least one semantic analysis result and at least one first material optimization suggestion information, wherein the semantic analysis result characterizes the strengths, weaknesses, or improvement directions of the target material as indicated by the semantics of the target comment; the first material optimization suggestion information includes at least one of the following: The optimization operation includes: the time point at which the optimization operation is performed on the target material; the position at which the optimization operation is performed on the target material; the optimization direction of the optimization operation; the reference material related to the optimization operation; and the associated material used in the optimization operation.

[0134] In one exemplary implementation, the analysis result display module 720 is configured to perform: On the material analysis page, duration suggestion information is displayed. The duration suggestion information includes a reference duration, which is the duration information of industry reference material corresponding to the target material. The industry reference material belongs to the same industry as the target material, and the interaction popularity of the industry reference material meets the preset interaction popularity requirements.

[0135] In one exemplary implementation, the analysis result display module 720 is configured to perform: The timeline corresponding to the target material is displayed on the material analysis page. On the timeline, an identifier corresponding to each of the first material optimization suggestion information is displayed. The display position of the identifier on the timeline is determined based on the time point corresponding to the material optimization operation. When any of the aforementioned identifiers is triggered, the display effect of the first material optimization suggestion information corresponding to the identifier is changed.

[0136] In one exemplary implementation, the analysis result display module 720 is configured to perform: On the material analysis page, operation controls are displayed for each of the first material optimization suggestion information. The operation controls are used to adopt the corresponding first material optimization suggestion information. The material analysis page displays a control for generating an analysis report; When the analysis report generation control is triggered, a material analysis report is displayed, which includes the first material optimization suggestion information that has been adopted.

[0137] In one exemplary implementation, the analysis result display module 720 is configured to perform: On the material analysis page, reference materials corresponding to the first material optimization suggestion information are displayed. These reference materials are from industry reference materials, which belong to the same industry as the target material, and the interaction popularity of the industry reference materials meets the preset interaction popularity requirements.

[0138] In one exemplary implementation, the analysis result display module 720 is configured to perform: The timeline corresponding to the target material is displayed on the material analysis page. On the material analysis page, at least one curve is displayed based on the timeline, which is used to indicate the change pattern of the corresponding interactive operation over time.

[0139] In one exemplary implementation, the at least one curve includes a loss curve, and the analysis results display module 720 is configured to perform: At the target time position of the churn curve, the corresponding churn analysis information is displayed, which indicates the reason for the churn occurring at the target time position.

[0140] In one exemplary implementation, the analysis result display module 720 is configured to perform: The churn analysis information displays optimization controls; When the optimization control is triggered, the storyboard sequence to be optimized and the associated storyboard sequence corresponding to the target time position are displayed. The associated storyboard sequence is a storyboard sequence obtained in response to the reason for the loss at the target time position. Display the storyboard replacement control; When the storyboard replacement control is triggered, the storyboard sequence to be optimized in the target material is replaced with the associated storyboard sequence.

[0141] In one exemplary implementation, the analysis result display module 720 is configured to perform: On the material analysis page, the second analysis result corresponding to the target material is displayed. The second analysis result shows the comparison result between the target material and the industry reference material in at least one target dimension. The industry reference material and the target material belong to the same industry, and the interaction popularity of the industry reference material meets the preset interaction popularity requirements. The target dimension refers to the dimension for semantic analysis of the industry reference material.

[0142] In one exemplary implementation, the analysis result display module 720 is configured to perform: On the material analysis page, second material optimization information is displayed, which matches the second analysis result.

[0143] In one exemplary embodiment, the second material optimization information includes at least one second material optimization suggestion, each of the second material optimization suggestion pieces includes an optimization time point, and the analysis result display module 720 is configured to execute: The timeline corresponding to the target material is displayed on the material analysis page. On the material analysis page, at the position corresponding to the optimization time point in the timeline, a corresponding display element is displayed. The display element is used to indicate the second material optimization information associated with the corresponding position.

[0144] In one exemplary implementation, the analysis result display module 720 is configured to perform: When any of the display elements is triggered, corresponding script change information is displayed at the associated location of the display element. The script change information includes script information before the change and script information after the change. The script change information is obtained based on the second material optimization information corresponding to the display element.

[0145] Regarding the apparatus in the above embodiments, the specific manner in which each module performs its operation has been described in detail in the embodiments related to the method, and will not be elaborated upon here.

[0146] In an exemplary embodiment, a computer-readable storage medium including instructions is also provided. Optionally, the computer-readable storage medium may be a ROM, random access memory (RAM), CD-ROM, magnetic tape, floppy disk, and optical data storage device, etc. When the instructions in the computer-readable storage medium are executed by a processor of an electronic device, the electronic device is able to perform any of the methods described above.

[0147] In an exemplary embodiment, a computer program product is also provided, the computer program product including a computer program stored in a readable storage medium, wherein at least one processor of a computer device reads from the readable storage medium and executes the computer program, causing the device to perform any of the methods described above.

[0148] Figure 8 This is a block diagram illustrating an electronic device for displaying information according to an exemplary embodiment. The electronic device may be a terminal, and its internal structure diagram may be as follows: Figure 8 As shown, the device may include an RF (Radio Frequency) circuit 810, a memory 820 including one or more computer-readable storage media, an input unit 830, a display unit 840, a sensor 850, an audio circuit 860, a WiFi (Wireless Fidelity) module 870, a processor 880 including one or more processing cores, and a power supply 890, among other components. Those skilled in the art will understand that... Figure 8 The terminal structure shown does not constitute a limitation on the terminal and may include more or fewer components than shown, or combine certain components, or have different component arrangements. Wherein: The RF circuit 810 can be used for receiving and transmitting signals during information transmission or calls. Specifically, it receives downlink information from the base station and hands it over to one or more processors 880 for processing; additionally, it transmits uplink data to the base station. Typically, the RF circuit 810 includes, but is not limited to, an antenna, at least one amplifier, a tuner, one or more oscillators, a Subscriber Identity Module (SIM) card, a transceiver, a coupler, an LNA (Low Noise Amplifier), a duplexer, etc. Furthermore, the RF circuit 810 can also communicate wirelessly with networks and other terminals. Wireless communication can use any communication standard or protocol, including but not limited to GSM (Global System for Mobile communication), GPRS (General Packet Radio Service), CDMA (Code Division Multiple Access), WCDMA (Wideband Code Division Multiple Access), LTE (Long Term Evolution), email, SMS (Short Messaging Service), etc.

[0149] The memory 820 can be used to store software programs and modules. The processor 880 executes various functional applications and data processing by running the software programs and modules stored in the memory 820. The memory 820 may mainly include a program storage area and a data storage area. The program storage area may store the operating system, application programs required for the functions, etc.; the data storage area may store data created according to the use of the terminal, etc. In addition, the memory 820 may include high-speed random access memory, and may also include non-volatile memory, such as at least one disk storage device, flash memory device, or other volatile solid-state storage device. Accordingly, the memory 820 may also include a memory controller to provide access to the memory 820 for the processor 880 and the input unit 830.

[0150] The input unit 830 can be used to receive input digital or character information, and to generate keyboard, mouse, joystick, optical, or trackball signal inputs related to user settings and function control. Specifically, the input unit 830 may include a touch-sensitive surface 831 and other input devices 832. The touch-sensitive surface 831, also known as a touch display screen or touchpad, can collect touch operations performed by the user on or near it (such as operations performed by the user using a finger, stylus, or any suitable object or accessory on or near the touch-sensitive surface 831), and drive the corresponding connected devices according to a pre-set program. Optionally, the touch-sensitive surface 831 may include two parts: a touch detection device and a touch controller. The touch detection device detects the user's touch position and the signal generated by the touch operation, and transmits the signal to the touch controller; the touch controller receives touch information from the touch detection device, converts it into touch point coordinates, and sends it to the processor 880, and can also receive and execute commands sent by the processor 880. In addition, the touch-sensitive surface 831 can be implemented using various types such as resistive, capacitive, infrared, and surface acoustic wave. In addition to the touch-sensitive surface 831, the input unit 830 may also include other input devices 832. Specifically, other input devices 832 may include, but are not limited to, one or more of the following: physical keyboard, function keys (such as volume control buttons, power buttons, etc.), trackball, mouse, joystick, etc. The display unit 840 can be used to display information input by the user or information provided to the user, as well as various graphical user interfaces of the terminal. These graphical user interfaces can be composed of graphics, text, icons, video, and any combination thereof. The display unit 840 may include a display panel 841, which may optionally be configured as an LCD (Liquid Crystal Display), OLED (Organic Light-Emitting Diode), or similar display panel 841. Further, a touch-sensitive surface 831 may cover the display panel 841. When the touch-sensitive surface 831 detects a touch operation on or near it, it transmits the information to the processor 880 to determine the type of touch event. Subsequently, the processor 880 provides corresponding visual output on the display panel 841 according to the type of touch event. The touch-sensitive surface 831 and the display panel 841 can be two independent components to implement input and output functions. However, in some embodiments, the touch-sensitive surface 831 and the display panel 841 can be integrated to achieve input and output functions.

[0151] The terminal may also include at least one sensor 850, such as a light sensor, a motion sensor, and other sensors. Specifically, the light sensor may include an ambient light sensor and a proximity sensor. The ambient light sensor can adjust the brightness of the display panel 841 according to the ambient light level, and the proximity sensor can turn off the display panel 841 and / or the backlight when the terminal is moved to the ear. As a type of motion sensor, a gravity acceleration sensor can detect the magnitude of acceleration in various directions (generally three axes). When stationary, it can detect the magnitude and direction of gravity and can be used for applications that identify the terminal's posture (such as landscape / portrait switching, related games, magnetometer posture calibration), vibration recognition-related functions (such as pedometer, tapping), etc. Other sensors that may be configured on the terminal, such as gyroscopes, barometers, hygrometers, thermometers, and infrared sensors, will not be described in detail here.

[0152] Audio circuitry 860, speaker 861, and microphone 862 provide an audio interface between the user and the terminal. Audio circuitry 860 converts received audio data into electrical signals, which are then transmitted to speaker 861, where they are converted into sound signals for output. Conversely, microphone 862 collects sound signals, converts them into electrical signals, which are then received by audio circuitry 860, converted back into audio data, processed by processor 880, and transmitted via RF circuitry 810 to, for example, another terminal, or output to memory 820 for further processing. Audio circuitry 860 may also include an earphone jack to facilitate communication between a peripheral headset and the terminal.

[0153] WiFi is a short-range wireless transmission technology. This terminal, through the WiFi module 870, can help users send and receive emails, browse web pages, and access streaming media, providing users with wireless broadband internet access. Although Figure 8 WiFi module 870 is shown, but it is understood that it is not a necessary component of the terminal and can be omitted as needed without changing the nature of the invention.

[0154] The processor 880 is the control center of the terminal, connecting various parts of the terminal through various interfaces and lines. It executes software programs and / or modules stored in the memory 820, and calls data stored in the memory 820 to perform various functions and process data, thereby enabling overall monitoring of the terminal. Optionally, the processor 880 may include one or more processing cores; preferably, the processor 880 may integrate an application processor and a modem processor, wherein the application processor mainly handles the operating system, user interaction area, and applications, while the modem processor mainly handles wireless communication. It is understood that the modem processor may not be integrated into the processor 880.

[0155] The terminal also includes a power supply 890 (such as a battery) to power various components. Preferably, the power supply can be logically connected to the processor 880 through a power management system, thereby enabling functions such as charging, discharging, and power consumption management through the power management system. The power supply 890 may also include one or more DC or AC power supplies, a recharging system, a power fault detection circuit, a power converter or inverter, a power status indicator, and other arbitrary components.

[0156] Although not shown, the terminal may also include a camera, Bluetooth module, etc., which will not be described in detail here. Specifically, in this embodiment, the display unit of the terminal is a touch screen display, and the terminal also includes a memory and one or more programs, wherein one or more programs are stored in the memory and configured to be executed by one or more processors of the instructions in the method embodiment of the present invention.

[0157] Please refer to Figure 9 This illustration shows another block diagram of an electronic device for displaying information, provided in another exemplary embodiment of this disclosure. The computer device may be a server for performing the information display method described above. Specifically: Computer device 900 includes a Central Processing Unit (CPU) 901, a system memory 904 including Random Access Memory (RAM) 902 and Read Only Memory (ROM) 903, and a system bus 905 connecting the system memory 904 and the CPU 901. Computer device 900 also includes a basic input / output system (I / O system) 906 that facilitates information transfer between various devices within the computer, and a mass storage device 907 for storing the operating system 913, application programs 914, and other program modules 911.

[0158] The basic input / output system 906 includes a display 908 for displaying information and an input device 909 for user input, such as a mouse or keyboard. Both the display 908 and the input device 909 are connected to the central processing unit 901 via an input / output controller 190 connected to the system bus 905. The basic input / output system 906 may also include the input / output controller 190 for receiving and processing input from multiple other devices such as a keyboard, mouse, or electronic stylus. Similarly, the input / output controller 190 also provides output to a display screen, printer, or other types of output devices.

[0159] Mass storage device 907 is connected to central processing unit 901 via a mass storage controller (not shown) connected to system bus 905. Mass storage device 907 and its associated computer-readable media provide non-volatile storage for computer device 900. That is, mass storage device 907 may include computer-readable media (not shown) such as hard disk or CD-ROM (CompactDisc Read-Only Memory) drive.

[0160] Without loss of generality, computer-readable media can include computer storage media and communication media. Computer storage media includes volatile and non-volatile, removable and non-removable media implemented using any method or technology for storing information such as computer-readable instructions, data structures, program modules, or other data. Computer storage media includes RAM, ROM, EPROM (Erasable Programmable Read Only Memory), EEPROM (Electrically Erasable Programmable Read Only Memory), flash memory or other solid-state storage technologies, CD-ROM, DVD (Digital Video Disc) or other optical storage, magnetic tape cassettes, magnetic tape, disk storage, or other magnetic storage devices. Of course, those skilled in the art will recognize that computer storage media are not limited to the above-mentioned types. The system memory 904 and mass storage device 907 described above can be collectively referred to as memory.

[0161] According to various embodiments of this disclosure, the computer device 900 can also be connected to a remote computer on a network, such as the Internet. That is, the computer device 900 can be connected to a network 912 via a network interface unit 911 connected to a system bus 905, or the network interface unit 911 can be used to connect to other types of networks or remote computer systems (not shown).

[0162] The aforementioned memory also includes a computer program stored in the memory and configured to be executed by one or more processors to implement the aforementioned information display method.

[0163] In an exemplary embodiment, a computer-readable storage medium is also provided, which stores at least one instruction, at least one program, code set, or instruction set, wherein the at least one instruction, at least one program, code set, or instruction set is executed by a processor to implement the information display method described above.

[0164] Optionally, the computer-readable storage medium may include: ROM (Read Only Memory), RAM (Random Access Memory), SSD (Solid State Drives), or optical disc, etc. The random access memory may include ReRAM (Resistance Random Access Memory) and DRAM (Dynamic Random Access Memory).

[0165] In an exemplary embodiment, a computer-readable storage medium including program code is also provided, such as a memory including program code, which can be executed by a processor to complete the above-described information display method. Optionally, the computer-readable storage medium may be read-only memory (ROM), random access memory (RAM), compact-disc read-only memory (CD-ROM), magnetic tape, floppy disk, and optical data storage device, etc.

[0166] In an exemplary embodiment, a computer program product is also provided, including a computer program that, when executed by a processor, implements the information display method described above.

[0167] Other embodiments of this disclosure will readily occur to those skilled in the art upon consideration of the specification and practice of the invention disclosed herein. This disclosure is intended to cover any variations, uses, or adaptations of this disclosure that follow the general principles of this disclosure and include common knowledge or customary techniques in the art not disclosed herein. The specification and examples are to be considered exemplary only, and the true scope and spirit of this disclosure are indicated by the following claims.

[0168] It should be understood that this disclosure is not limited to the precise structures described above and shown in the accompanying drawings, and various modifications and changes can be made without departing from its scope. The scope of this disclosure is limited only by the appended claims.

Claims

1. An information display method, characterized in that, The method includes: Displays the material analysis page corresponding to the target material; On the material analysis page, a first analysis result is displayed. The first analysis result represents the first material optimization information that characterizes the semantic indication of the target comment. The target comment is the comment corresponding to the target material.

2. The method according to claim 1, characterized in that, The first analysis result includes at least one semantic analysis result and at least one first material optimization suggestion information. The semantic analysis result characterizes the strengths, weaknesses, or improvement directions of the target material as indicated by the semantics of the target comment. The first material optimization suggestion information includes at least one of the following: The optimization operation includes: the time point at which the optimization operation is performed on the target material; the position at which the optimization operation is performed on the target material; the optimization direction of the optimization operation; the reference material related to the optimization operation; and the associated material used in the optimization operation.

3. The method according to claim 1, characterized in that, The method further includes: On the material analysis page, duration suggestion information is displayed. The duration suggestion information includes a reference duration, which is the duration information of industry reference material corresponding to the target material. The industry reference material belongs to the same industry as the target material, and the interaction popularity of the industry reference material meets the preset interaction popularity requirements.

4. The method according to claim 2, characterized in that, The method further includes: The timeline corresponding to the target material is displayed on the material analysis page. On the timeline, an identifier corresponding to each of the first material optimization suggestion information is displayed. The display position of the identifier on the timeline is determined based on the time point corresponding to the material optimization operation. When any of the aforementioned identifiers is triggered, the display effect of the first material optimization suggestion information corresponding to the identifier is changed.

5. The method according to claim 2 or 4, characterized in that, The method further includes: On the material analysis page, operation controls are displayed for each of the first material optimization suggestion information. The operation controls are used to adopt the corresponding first material optimization suggestion information. The material analysis page displays a control for generating an analysis report; When the analysis report generation control is triggered, a material analysis report is displayed, which includes the first material optimization suggestion information that has been adopted.

6. The method according to claim 2 or 4, characterized in that, The method further includes: On the material analysis page, reference materials corresponding to the first material optimization suggestion information are displayed. These reference materials are from industry reference materials, which belong to the same industry as the target material, and the interaction popularity of the industry reference materials meets the preset interaction popularity requirements.

7. The method according to claim 1, characterized in that, The method further includes: The timeline corresponding to the target material is displayed on the material analysis page. On the material analysis page, at least one curve is displayed based on the timeline, which is used to indicate the change pattern of the corresponding interactive operation over time.

8. The method according to claim 7, characterized in that, The at least one curve includes a loss curve, and the method further includes: At the target time position of the churn curve, the corresponding churn analysis information is displayed, which indicates the reason for the churn occurring at the target time position.

9. The method according to claim 8, characterized in that, The method further includes: The churn analysis information displays optimization controls; When the optimization control is triggered, the storyboard sequence to be optimized and the associated storyboard sequence corresponding to the target time position are displayed. The associated storyboard sequence is a storyboard sequence obtained in response to the reason for the loss at the target time position. Display the storyboard replacement control; When the storyboard replacement control is triggered, the storyboard sequence to be optimized in the target material is replaced with the associated storyboard sequence.

10. The method according to claim 1, characterized in that, The method further includes: On the material analysis page, the second analysis result corresponding to the target material is displayed. The second analysis result shows the comparison result between the target material and the industry reference material in at least one target dimension. The industry reference material and the target material belong to the same industry, and the interaction popularity of the industry reference material meets the preset interaction popularity requirements. The target dimension refers to the dimension for semantic analysis of the industry reference material.

11. The method according to claim 10, characterized in that, The method further includes: On the material analysis page, second material optimization information is displayed, which matches the second analysis result.

12. The method according to claim 11, characterized in that, The second material optimization information includes at least one second material optimization suggestion, each second material optimization suggestion includes an optimization time point, and the method further includes: The timeline corresponding to the target material is displayed on the material analysis page. On the material analysis page, at the position corresponding to the optimization time point in the timeline, a corresponding display element is displayed. The display element is used to indicate the second material optimization information associated with the corresponding position.

13. The method according to claim 12, characterized in that, The method further includes: When any of the display elements is triggered, corresponding script change information is displayed at the associated location of the display element. The script change information includes script information before the change and script information after the change. The script change information is obtained based on the second material optimization information corresponding to the display element.

14. An information display device, characterized in that, The device includes: The page display module is configured to execute the material analysis page corresponding to the target material for display; The analysis results display module is configured to execute on the material analysis page to display a first analysis result, wherein the first analysis result represents first material optimization information representing the semantic indication of the target comment, and the target comment is the comment corresponding to the target material.

15. An electronic device, characterized in that, include: processor; Memory used to store the processor's executable instructions; The processor is configured to execute the instructions to implement the information display method as described in any one of claims 1 to 13.

16. A computer-readable storage medium, characterized in that, When the instructions in the computer-readable storage medium are executed by the processor of the electronic device, the electronic device is able to perform the information display method as described in any one of claims 1 to 13.

17. A computer program product, characterized in that, The computer program product includes a computer program stored in a readable storage medium, wherein at least one processor of a computer device reads from the readable storage medium and executes the computer program, causing the device to perform the information display method as described in any one of claims 1 to 13.

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