Display device, server and display method of media data

Abstract

The embodiment of the application provides a display device, a server and a display method of media data, in response to a play action instruction input by a user, log data can be generated, the log data includes a start playing time, a duration, a media code and a user identifier of the media data; the time interval between the end time and the start playing time of the media data corresponding to the media code is calculated; the target sub-stage to which the log data belongs in the memory curve is queried according to the time interval; the integral value corresponding to the log data of the review is calculated according to the duration at the time of the review and the calculation weight corresponding to the target sub-stage, and the integral value is accumulated into an integral table, and an interface including the integral table and the integral value is displayed on the display. Through the calculation and statistics of the integral value of the log data reviewed by the user, the statistical content of the user review in the live course review process is enriched, and the problem that the display content of the statistical situation of the user review in the live course review process is too little is solved.

Description

Technical Field

[0001] Some embodiments of this application relate to the field of display device technology, and in particular to a display device, server, and method for displaying media data. Background Technology

[0002] Due to the internet's advantages of being intuitive, highly interactive, and geographically unrestricted, online live streaming is becoming increasingly common. For example, media assets such as course data can be displayed on screen devices during online live streams. After an online live course ends, users often need to repeatedly review the recorded video to reinforce the course content and deepen their understanding.

[0003] To display users' review progress, it's necessary to statistically analyze data on users' viewing of media replays. This statistical data would then help determine users' learning habits. However, currently, during live stream replays, only basic statistics on user viewing activity can be displayed, resulting in insufficient content and a degraded user experience. Summary of the Invention

[0004] Some embodiments of this application provide a display device, server, and media data display method to solve the problem of insufficient display content of user replay statistics during live course replay.

[0005] In a first aspect, some embodiments of this application provide a server, including:

[0006] The memory is configured to store program instructions;

[0007] The processor executes program instructions, and the processor is configured to:

[0008] Receive log data sent by the display device; the log data includes the start time, duration, media asset encoding, and user identifier of the media asset data;

[0009] Calculate the time interval between the end time and the start time of the media asset data corresponding to the media asset code;

[0010] The system queries the target sub-stage to which the log data belongs in the memory curve based on the time interval, calculates the integral value based on the duration and the calculation weight corresponding to the target sub-stage, and accumulates the integral value in the integral table; wherein, the memory curve is a curve established based on the media asset code and user identifier; the memory curve is divided into multiple sub-stages according to time, and each sub-stage has a calculation weight;

[0011] The integral value is fed back to the display device.

[0012] Secondly, some embodiments of this application provide a display device, including:

[0013] The monitor is configured to display the playback interface;

[0014] The communicator is configured to establish a communication connection with the server.

[0015] The controller is configured as follows:

[0016] In response to the user's input playback action command, log data is generated, which includes the start time of media asset playback, duration, media asset encoding, and user identifier.

[0017] Log data is sent to the server so that the server can calculate the time interval between the end time and the start time of the media asset data corresponding to the media asset code; and query the target sub-stage to which the log data belongs in the memory curve according to the time interval, and calculate the integral value according to the duration and the calculation weight corresponding to the target sub-stage, and accumulate the integral value into the integral table; wherein, the memory curve is a curve established according to the media asset code and the user identifier; the memory curve is divided into multiple sub-stages according to time, and each sub-stage has a calculation weight;

[0018] It receives the score values ​​from the server and controls the display to show the interface including the score table and score values.

[0019] Thirdly, some embodiments of this application provide a display device, including:

[0020] The monitor is configured to display the playback interface;

[0021] The controller is configured as follows:

[0022] In response to the user's input playback action command, log data is generated, which includes the start time of media asset playback, duration, media asset encoding, and user identifier.

[0023] Calculate the time interval between the end time and the start time of the media asset data corresponding to the media asset code;

[0024] The log data is queried according to the time interval to determine the target sub-stage to which it belongs in the memory curve. The memory curve is a curve established based on media asset encoding and user identifier. The memory curve is divided into multiple sub-stages according to time, and each sub-stage has a calculation weight.

[0025] The integral value is calculated based on the duration and the calculation weight corresponding to the target sub-stage, and the integral value is accumulated in the integral table.

[0026] The control display shows an interface including an integrator table and integral values.

[0027] Fourthly, some embodiments of this application provide a method for displaying media asset data, applied to a display device of the third aspect, wherein the display device includes a display and a controller; the method for displaying media asset data includes:

[0028] In response to the user's input playback action command, log data is generated, which includes the start time of media asset playback, duration, media asset encoding, and user identifier.

[0029] Calculate the time interval between the end time and the start time of the media asset data corresponding to the media asset code;

[0030] The log data is queried according to the time interval to determine the target sub-stage to which it belongs in the memory curve. The memory curve is a curve established based on media asset encoding and user identifier. The memory curve is divided into multiple sub-stages according to time, and each sub-stage has a calculation weight.

[0031] The integral value is calculated based on the duration and the calculation weight corresponding to the target sub-stage, and the integral value is accumulated in the integral table.

[0032] The control display shows an interface including an integrator table and integral values.

[0033] As can be seen from the above technical solutions, some embodiments of this application provide a display device, a server, and a method for displaying media asset data. In response to a user-inputted playback command, the display device generates log data, which includes the start playback time, duration, media asset code, and user identifier of the media asset data. The method calculates the time interval between the end time and start playback time of the media asset data corresponding to the media asset code; queries the target sub-stage to which the log data belongs in the memory curve based on the time interval; calculates the integral value corresponding to the replayed log data based on the duration of the replay and the calculation weight corresponding to the target sub-stage; accumulates the integral value in an integral table; and controls the display to show an interface including the integral table and the integral value. This application, by calculating and statistically analyzing the integral value of the log data replayed by the user, enriches the statistical content of user replay during the live course replay process and solves the problem of insufficient statistical content displayed during the live course replay process. Attached Figure Description

[0034] To more clearly illustrate the technical solutions in some embodiments of this application or in the prior art, the drawings used in the embodiments will be briefly introduced below. Obviously, the drawings described below are only some embodiments of this application. For those skilled in the art, other drawings can be obtained based on these drawings without creative effort.

[0035] Figure 1This is a schematic diagram illustrating an operational scenario between a display device and a control device provided in some embodiments of this application;

[0036] Figure 2 Provided for some embodiments of this application Figure 1 The hardware configuration block diagram of the display device is shown in the image.

[0037] Figure 3 Provided for some embodiments of this application Figure 1 Hardware configuration block diagram of the central control device;

[0038] Figure 4 Provided for some embodiments of this application Figure 1 A schematic diagram of the software configuration in the display device;

[0039] Figure 5 This application provides schematic flowcharts of media asset data display methods for some embodiments;

[0040] Figure 6 Interactive timing diagrams of media asset data display methods provided in some embodiments of this application;

[0041] Figure 7 This is a schematic diagram of the log data reporting process provided in some embodiments of this application;

[0042] Figure 8 This application provides flowcharts illustrating the statistical log data based on identifiers in some embodiments.

[0043] Figure 9 This application provides timing diagrams for log data flow in some embodiments.

[0044] Figure 10 A flowchart illustrating the process of dividing a memory curve into a preset number of sub-stages, provided for some embodiments of this application;

[0045] Figure 11 This application provides schematic diagrams of integral calculation processes for some embodiments.

[0046] Figure 12 This is a schematic diagram illustrating the user's review status as provided in some embodiments of this application;

[0047] Figure 13 Illustrated diagrams illustrating the integrals provided for some embodiments of this application;

[0048] Figure 14 The diagram illustrates the display device and execution flow provided in some embodiments of this application. Detailed Implementation

[0049] To make the objectives, technical solutions, and advantages of some embodiments of this application clearer, the technical solutions of some embodiments of this application will be clearly and completely described below with reference to specific embodiments and corresponding drawings. Obviously, the described embodiments are only some embodiments of this application, and not all embodiments.

[0050] It should be noted that the brief descriptions of terms in some embodiments of this application are only for the convenience of understanding the implementation methods described below, and are not intended to limit the implementation methods of some embodiments of this application. Unless otherwise stated, these terms should be understood in their ordinary and common meaning.

[0051] In some embodiments of this application, the terms "first," "second," "third," etc., in the specification, claims, and accompanying drawings are used to distinguish similar or related objects or entities, and do not necessarily imply a specific order or sequence, unless otherwise specified. It should be understood that such terms can be used interchangeably where appropriate.

[0052] The terms “comprising” and “having”, and any variations thereof, are intended to cover but not exclude inclusion, for example, a product or device that includes a range of components is not necessarily limited to all of the components that are clearly listed, but may include other components that are not clearly listed or that are inherent to such product or device.

[0053] The term "module" refers to any known or subsequently developed hardware, software, firmware, artificial intelligence, fuzzy logic, or combination of hardware and / or software code that is capable of performing the functions associated with that element.

[0054] Figure 1 This is a schematic diagram illustrating an operational scenario between a display device and a control device provided in some embodiments of this application. For example... Figure 1 As shown, the user can operate the display device 200 through the mobile terminal 300 and the control device 100.

[0055] In some embodiments, the mobile terminal 300 may install software applications with the display device 200 to establish a connection and communication via a network communication protocol, thereby achieving one-to-one control operation and data communication. Alternatively, audio and video content displayed on the mobile terminal 300 can be transmitted to the display device 200 to achieve synchronous display.

[0056] like Figure 1 The diagram also shows that the display device 200 communicates with the server 400 via various communication methods. This allows the display device 200 to communicate via a local area network (LAN), a wireless local area network (WLAN), and other networks.

[0057] In addition to providing broadcast television reception functions, the display device 200 can also be equipped with intelligent network television functions that provide computer support, including but not limited to network television, smart television, Internet Protocol television (IPTV), etc.

[0058] Figure 2 Provided for some embodiments of this application Figure 1 Hardware configuration block diagram of display device 200.

[0059] In some embodiments, the display device 200 includes at least one of a tuner 210, a communicator 220, a detector 230, an external device interface 240, a controller 250, a display 260, an audio output interface 270, a memory, a power supply, and a user interface.

[0060] In some embodiments, the detector 230 is used to collect signals from the external environment or to interact with the outside world.

[0061] In some embodiments, the display 260 includes a display screen component for presenting an image, a driving component for driving image display, a component for receiving image signals output from a controller, and a user control UI interface, etc.

[0062] In some embodiments, the communicator 220 is a component for communicating with external devices or the server 400 according to various communication protocol types.

[0063] In some embodiments, the controller 250 controls the operation of the display device and responds to user operations through various software control programs stored in memory. The controller 250 controls the overall operation of the display device 200.

[0064] In some embodiments, a user can input user commands through a graphical user interface (GUI) displayed on a display 260, and the user input interface receives user input commands through the graphical user interface (GUI).

[0065] In some embodiments, user interface 280 is an interface that can be used to receive control input.

[0066] Figure 3 Provided for some embodiments of this application Figure 1 Hardware configuration block diagram of the central control device. (Example) Figure 3 As shown, the control device 100 includes a controller 110, a communication interface 130, a user input / output interface, a memory, and a power supply.

[0067] The control device 100 is configured to control the display device 200, and to receive user input operation commands and convert the operation commands into commands that the display device 200 can recognize and respond to, thus acting as an intermediary for interaction between the user and the display device 200.

[0068] In some embodiments, the control device 100 may be an intelligent device. For example, the control device 100 may be equipped with various applications for controlling the display device 200 according to user needs.

[0069] In some embodiments, such as Figure 1 As shown, the mobile terminal 300 or other smart electronic devices can perform similar functions to the control device 100 after installing the application of the control display device 200.

[0070] The controller 110 includes a processor 112, RAM 113, ROM 114, a communication interface 130, and a communication bus. The controller 110 is used to control the operation of the control device 100, as well as the communication and cooperation between internal components and the external and internal data processing functions.

[0071] Under the control of the controller 110, the communication interface 130 enables communication of control signals and data signals with the display device 200. The communication interface 130 may include at least one of other near-field communication modules such as WiFi chip 131, Bluetooth module 132, and NFC module 133.

[0072] User input / output interface 140, wherein the input interface includes at least one of other input interfaces such as microphone 141, touchpad 142, sensor 143, button 144, etc.

[0073] In some embodiments, the control device 100 includes at least one of a communication interface 130 and an input / output interface 140. The control device 100 is configured with the communication interface 130, such as a WiFi, Bluetooth, or NFC module, which can encode user input commands via WiFi, Bluetooth, or NFC protocols and send them to the display device 200.

[0074] The memory 190 is used to store various operating programs, data, and applications for driving and controlling the control device 100 under the control of the controller. The memory 190 can also store various control signal instructions input by the user.

[0075] The power supply 180 is used to provide operating power support for the various components of the control device 100 under the control of the controller.

[0076] Figure 4 Provided for some embodiments of this application Figure 1The diagram shows the software configuration in the display device. In some embodiments, the system is divided into four layers, from top to bottom: the Applications layer (referred to as the "Application Layer"), the Application Framework layer (referred to as the "Framework Layer"), the Android runtime and the System Library layer (referred to as the "System Runtime Library Layer"), and the kernel layer.

[0077] In some embodiments, at least one application runs in the application layer. These applications may be Windows programs that come with the operating system, system settings programs, clock programs, camera applications, etc., or they may be applications developed by third-party developers.

[0078] The framework layer provides application programming interfaces (APIs) and programming frameworks for applications in the application layer. The application framework layer includes predefined functions. It acts as a central processing unit, determining the actions taken by applications within the application layer.

[0079] like Figure 4 As shown, in some embodiments of this application, the application framework layer includes managers, content providers, and a view system.

[0080] In some embodiments, the Activity Manager is used to: manage the lifecycle of individual applications and the usual navigation back functionality.

[0081] In some embodiments, the window manager is used to manage all window programs.

[0082] In some embodiments, the system runtime library layer provides support for the upper layer, namely the framework layer. When the framework layer is accessed, the Android operating system runs the C / C++ libraries contained in the system runtime library layer to implement the functions that the framework layer needs to perform.

[0083] In some embodiments, the kernel layer is a layer between hardware and software. For example... Figure 4 As shown, the kernel layer includes at least one of the following drivers: audio driver, display driver, Bluetooth driver, camera driver, WIFI driver, USB driver, HDMI driver, sensor driver (such as fingerprint sensor, temperature sensor, touch sensor, pressure sensor, etc.).

[0084] In some embodiments, the kernel layer also includes a power driver module for power management.

[0085] In some embodiments, Figure 4 The software programs and / or modules corresponding to the software architecture in the document are stored in [the relevant database]. Figure 2 or Figure 3 In the first or second memory shown.

[0086] Based on the display device 200 in the above embodiments, the content of media asset data playback can be presented on the display device 200. For example, online live media asset data, such as course data, can be presented on the display device. After the live broadcast ends, users can also review the live course content through a specific interface. The display device 200 can generate and display a statistics interface based on the user's viewing behavior. The statistics interface can display relevant data content during the live broadcast review process, including the number of reviews and the review duration.

[0087] Currently, live stream replays can only provide basic statistics on user viewing activity, displaying very limited information. For example, they can only track basic information such as viewing time and duration, making the content too simplistic and unable to effectively support user learning. Furthermore, based on forgetting curves like the Ebbinghaus forgetting curve, the rate of forgetting learned knowledge, such as live course content, follows a certain pattern. Forgetting does not follow a linear downward trend; instead, the rate of forgetting is faster in the initial stages, slowing down or even ceasing after a certain period.

[0088] To solidify learned knowledge and ensure its firm storage in the brain, it's necessary to review it repeatedly for a period after learning new material, especially during periods of rapid forgetting. This reinforces memory and counteracts the effects of the accelerated forgetting phase of the forgetting curve, allowing the knowledge to be retained until the curve flattens out. Therefore, it's necessary to statistically analyze users' media review data. By analyzing this data, we can determine if users' learning habits align with the forgetting curve and guide them towards it. However, since the statistical interface only contains basic information, it lacks the functionality to guide users' learning habits towards the forgetting curve.

[0089] To address the issue of insufficient statistical content displayed during live course replays, some embodiments of this application provide a method for displaying media asset data. This method can be applied to a display device 200, which includes a display 260 and a controller 250. To facilitate understanding of the technical solutions in some embodiments of this application, the steps are described in detail below with reference to specific embodiments and accompanying drawings. Figure 5 This is a schematic flowchart illustrating a media asset data display method provided in some embodiments of this application, such as... Figure 5 As shown, in some embodiments, a method for displaying media asset data may include the following steps:

[0090] Step S100: In response to the playback action command input by the user, the display device 200 generates log data, which includes the start time of media asset playback, duration, media asset encoding, and user identifier.

[0091] In order to enable functions such as playback, replay, and statistics of media asset data, in some embodiments, multiple service modules can be configured in the display device 200. Figure 6 Interaction timing diagrams of media asset data display methods provided in some embodiments of this application, such as... Figure 6 As shown, the display device 200 can be configured with business modules such as a playback unit, a business system, a cache, a database, and a log system. The playback unit is used to collect user playback data; the business system mainly provides users with data integration and query services, including media asset data query services and user login services. The cache primarily improves interface response speed; for example, data from frequently accessed interfaces can be stored in the cache, and when a request arrives, the cached result can be directly returned to the user, avoiding the time-consuming process of querying the database each time. The database is mainly used to store persistent media asset data such as course information and student information, statistical summary data, and configuration information. The log system is mainly responsible for collecting user behavior data reported by the playback unit, performing statistical summaries according to specific dimensions, and providing this data to the business system.

[0092] In some embodiments, the statistical function can also be performed by a cloud server. This server is configured with business modules such as a business system, cache, database, and log system. The display device 200 acts as a terminal connected to the server. The display device 200 can then collect user playback data and send it to the server, triggering the business system, cache, database, and log system on the server to perform the statistical function. The statistical results are then fed back to the display device 200.

[0093] After a live-streamed course on media assets concludes, users can access the replay page and click the start playback button to play the media asset during review. To guide users on which courses to prioritize for replay, some embodiments include user-defined identifiers on the replay page. These identifiers can be used to mark the effectiveness of the review, such as "very effective" or "not effective," "learned" or "not learned." The marked content can be selected from a dropdown menu or be user-defined. After users mark their review progress with these user-defined identifiers, courses with poor review results or those not learned will be prioritized on the replay page. This guides users to prioritize courses requiring further review, improving the effectiveness of their review.

[0094] In response to a user's playback command, the display device 200 generates log data based on the user's playback action. In some embodiments, the playback unit may collect the user's playback data, which may include the start time, duration, media asset encoding, and user identifier of the media asset data. The start time is, for example, the time when the user clicks the play button while reviewing; the duration is, for example, the time period between the start of playback and the pause; the media asset encoding is, for example, the course code; and the user identifier is, for example, the user ID.

[0095] After each playback unit collects and reviews the data, it can assemble and report the log data according to the set rules. Figure 7 This is a schematic diagram of the log data reporting process provided in some embodiments of this application, such as... Figure 7 As shown, the display device 200 can assemble log data based on the start playback time, duration, media asset encoding, and user identifier. After assembly, the assembled log data can be reported to the log system. For example, the playback unit can report log data to the log system by calling the log reporting interface in the log system.

[0096] To ensure the quality of log data, the log system can verify the received log data and generate a verification result. It's easy to understand that the verification result can be categorized as verification passed or failed. To ensure the quality of the log data stored in the log system, the system can store log data that has passed verification while filtering out log data that has failed verification. For example, during the log data verification process, the validity of the data format and the validity of the data content can be checked. After step S100 is completed, step S200 can be executed.

[0097] Step S200: Calculate the time interval between the end time and the start time of the media asset data corresponding to the media asset code.

[0098] After the log system stores the log data, it can statistically analyze the previous day's log data at a preset time point and generate a media asset list based on the media asset code. In some embodiments, the preset time point can be 0:00, and the media asset code can be a course code. Thus, at 0:00 each day, the log system can calculate the previous day's log data playback content for each user under that course code, using the course code as the dimension. For example, the playback content may include the playback duration, total number of playbacks, start playback time, etc. Based on this information, the log system can write the statistically analyzed media asset list into the cache, using the course code as the dimension.

[0099] To ensure data integrity in the database, the cached data can be written to the database after a time threshold is exceeded. In some embodiments, the time threshold can be set according to actual needs; for example, the time threshold can be set to one day, and the cached log data can be written to the database at regular intervals each day, thus ensuring data integrity in the database. For example, combined with... Figure 6 The business system can periodically read the previous day's statistical data from the cache, assemble it, and write it to the database. In this way, complete user log data can be generated in the database, including the start time of playback the previous day, duration, number of replays, and total replay duration.

[0100] In order to distinguish between log data that has been statistically completed and log data that has not been statistically completed, in some embodiments, a completed flag can be added to the log data. Figure 8 This application provides flowcharts illustrating the statistical log data based on identifiers in some embodiments, such as... Figure 8 As shown, statistical log data based on identifiers can be achieved through the following steps:

[0101] Step S810: Add a completion flag to the cached flags for the log data that was statistically completed the previous day.

[0102] To identify log data that has been statistically analyzed, a "completed" flag can be added to the cached flags for log data analyzed the previous day. This flag indicates that the log data from the previous day has been statistically analyzed. Rules can be set during the flag addition process; for example, a value of 1 can be assigned to "completed," and a value of 0 can be assigned to "incomplete." After step S810 is completed, step S820 can be executed.

[0103] Step S820: At a preset time point, read the flag bit in the cache.

[0104] To prevent cached log data from being missed, in some embodiments, the cached log data can be compared with the log data in the database. Figure 9 The log data flow timing diagrams provided for some embodiments of this application are as follows: Figure 9 As shown, in response to log data where the target media asset data is not detected in the database, the log data corresponding to the target media asset data can be read from the cache according to the media asset encoding, and the read log data can be inserted into the database to further ensure the integrity of the log data in the database.

[0105] Continue to combine Figure 9In some embodiments, the preset time point can be 0:00. After 0:00, the flag bit in the cache can be read. For example, the business system can execute the following scheduled task after 0:00 every day. First, the flag bit in the cache is read. After step S820 is completed, step S830 can be executed.

[0106] Step S830: Determine the statistical status of the log data based on the flag bit.

[0107] After reading the flag bit, the statistical status of the log data can be determined based on the flag bit. For example, if the value of the flag bit is 1, it indicates that the log data has been statistically analyzed; if the value of the flag bit is 0, it indicates that the log data has not been statistically analyzed. After step S830 is completed, step S840 can be executed.

[0108] Step S840: If the statistical status of the log data is "statistics completed", traverse the list of media assets that have completed statistics in the database.

[0109] If the log data's statistical status indicates completion, the database can be iterated through to find the list of media assets for which statistics have been completed. For example, the media asset list could be a list of courses; when the log data's statistical status indicates completion, the database can be queried to retrieve a list of all completed live courses with media asset codes. After step S840 is completed, step S850 can be executed.

[0110] Step S850: Query the log data corresponding to the target media asset data according to the media asset code, and query the log data of the target user on the target date and / or the target media asset data according to the media asset code, user identifier and date code.

[0111] In some embodiments, the log data also includes a date code. After obtaining the list of media assets with media asset codes in step S840, combined with... Figure 6 It allows you to loop through a list of media assets, such as looping through a list of completed live courses, and query the log data corresponding to a target media asset based on its media asset code. For example, the media asset list may contain log data corresponding to multiple media asset codes. To query the log data corresponding to a specific target media asset, you can directly query it by its media asset code.

[0112] To query log data for a target user on a specified date or for a specific target media asset, some embodiments may further loop through the log data, such as looping through a user's playback data list, and query the target user's log data for the target date and / or target media asset based on the media asset code, user identifier, and date code. For example, the media asset list may contain a lot of information, such as user identifier and date code. If you want to query the log data of a specific user on a specific day or under a specific media asset, such as course data, you can directly query the media asset list based on the media asset code, user identifier, and date code.

[0113] It should be noted that the loop through the media asset list and log data can be determined in the program code logic or executed in the proxy logic. If the media asset list or log data has been traversed, execution can continue to the next step.

[0114] To obtain the time interval between the end time and the start time of media asset data corresponding to the media asset code, we can first query the end time of the target media asset data based on the media asset code. After obtaining the end time of the target media asset data, we calculate the time difference between the end time and the start time of the target media asset data to obtain the time interval. For example, to query the end time of a target media asset data, we can use the media asset code of the target media asset data. If the end time of the target media asset data is May 5, 2022, it means that the target media asset data was recorded live on May 5, and the start time of the user's replay is May 7, 2022. The time difference between the two is 2 days, that is, the time interval can be determined to be 2 days. After step S200 is completed, the following step S300 can be executed.

[0115] Step S300: Query the target sub-stage to which the log data belongs in the memory curve based on the time interval.

[0116] After calculating the time interval between the end time and the start time of the media asset data, the target sub-stage of the memory curve to which the log data belongs can be queried based on this time interval. In other words, by matching the time interval between the user's replay time and the live class time with the memory curve, it can be determined which stage of the memory curve the log data corresponding to the user's replay time belongs to.

[0117] It should be noted that in some embodiments of this application, the memory curve can be a curve established based on media asset encoding and user identification. For example, the memory curve can be a curve established based on multiple factors such as media asset data corresponding to the media asset encoding and user log data corresponding to the user identification. The memory curve exhibits certain temporal patterns. For instance, users' forgetting of learned knowledge follows a certain regularity; forgetting does not follow a linear downward trend, but rather the forgetting rate is faster in the initial stage, and slows down or even stops after a certain period. Therefore, the principle of the memory curve theory is that the earlier the review, the more likely it is to be remembered. It can guide users to maintain a high level of memory through repeated review during the rapid forgetting stage, that is, to guide users' learning habits towards the memory curve in a certain way.

[0118] In order to query the target sub-stage to which log data belongs in the memory curve based on time intervals, in some embodiments, the memory curve can be divided into multiple sub-stages according to time, wherein each sub-stage has a calculated weight. Figure 10 This application provides a flowchart illustrating the process of dividing a memory curve into a preset number of sub-stages in some embodiments. Firstly, one can obtain, as shown below... Figure 10 The memory curve shown can include the number of memories and the number of days of retention. The number of memories changes as the number of days changes. After obtaining the memory curve, its temporal patterns are analyzed. For example, it identifies the number of days with a faster rate of forgetting and the number of days with a slower rate of forgetting. Finally, based on these temporal patterns, the memory curve is divided into a preset number of sub-stages. The preset number can be set according to the patterns of the memory curve and actual needs, and each sub-stage can have a calculation weight, such as an integral.

[0119] For example, in some embodiments, the memory curve can be divided into segments based on its temporal pattern. Figure 10 The five sub-stages shown correspond to a certain number of days, and each sub-stage can be assigned a calculation weight, as shown in Table 1. For example, referring to Table 1, which is a memory curve stage division table, the first sub-stage corresponds to a time interval of 1 day, and its corresponding calculation weight (integral) is 100; the second sub-stage corresponds to a time interval of 2 days, and its corresponding calculation weight (integral) is 50; the third sub-stage corresponds to a time interval of 4 days, and its corresponding calculation weight (integral) is 25; the fourth sub-stage corresponds to a time interval of 7 days, and its corresponding calculation weight (integral) is 10; the fifth sub-stage corresponds to a time interval of 30 days, and its corresponding calculation weight (integral) is 5; after a time interval exceeding 30 days, the integral can be set to 0.

[0120] Table 1: Stages of the Memory Curve

[0121] First sub-phase 1 100 Second sub-phase 2 50 Third sub-stage 4 25 Fourth sub-phase 7 10 Fifth sub-stage 30 5 >30 0

[0122] In other words, the log data generated during user review corresponds to different sub-stages of the memory curve and earns different points. As shown in Table 1, the point system is designed to decrease progressively with time intervals, with zero points awarded outside the first five sub-stages. This point system is based on the temporal patterns of the memory curve. It's clear from these patterns that forgetting occurs more rapidly in the first two sub-stages. Therefore, to encourage users to review during these faster-forgetting sub-stages, higher points can be awarded for the first two sub-stages, thus guiding users to review more quickly.

[0123] To determine the target sub-stage to which the log data corresponding to the user's review belongs, the target sub-stage in the memory curve can be determined based on the time interval. Each sub-stage of the memory curve corresponds to a time interval. If the time difference between the review time and the course end time falls within the time interval corresponding to a certain stage of the memory curve, it can be determined that the log data corresponding to the target media asset data matches that sub-stage. For example, in some embodiments, the end time of the corresponding media asset data can be queried based on the media asset code. The time interval can be determined based on the difference between the start and end times during review, and then the sub-stage of the memory curve where the review is located can be determined based on the time interval. After step S300 is completed, step S400 can be executed.

[0124] Step S400: Calculate the integral value based on the duration and the calculation weight corresponding to the target sub-stage, and accumulate the integral value into the integral table.

[0125] After querying the target sub-stage to which the log data belongs in the memory curve based on the time interval, the integral value corresponding to the log data being reviewed can be calculated based on the duration of the review and the calculation weight corresponding to the target sub-stage, and the integral value can be added to the original integral table.

[0126] To calculate the points corresponding to the log data generated when a user reviews the content, rules for point calculation can be set. Figure 11 This is a schematic diagram of the integral calculation process provided for some embodiments of this application, such as... Figure 11 As shown, the integral value corresponding to log data can be calculated in the following ways:

[0127] Step S111: Obtain the total duration and duration of the media asset corresponding to the target media asset data.

[0128] Media asset data, such as the total playback duration of a media asset course during live streaming, and the corresponding duration of the replay during user viewing, can be obtained to calculate the points corresponding to the user's replay log data. After step S111 is completed, step S112 can be executed.

[0129] Step S112: Obtain the target sub-stage to which the log data belongs and the corresponding calculated weight of the target sub-stage.

[0130] To calculate the integral value corresponding to the log data, after obtaining the total duration and duration of the media asset, the target sub-stage to which the log data belongs and the calculation weight corresponding to the target sub-stage can be obtained based on the time interval. In some embodiments, the integral calculation method can be:

[0131] Points = (Duration of this review / Total duration of media assets) × Points for the target sub-stage.

[0132] That is, after determining which sub-stage of the memory curve the current playback is in, the score corresponding to the user's current log data can be calculated based on the scores of each sub-stage, combined with the duration and the total duration of the media assets. After step S112 is completed, step S113 can be executed.

[0133] Step S113: Perform a weighted summation calculation on the duration and total duration of media assets based on the calculated weights to obtain the new integral value.

[0134] To calculate the points for multiple viewings by the user, a weighted summation can be performed on the duration and total duration of the media asset based on the calculation weights to obtain additional points. For example, a user may have viewed the target media asset data multiple times, and points can be earned for each viewing. After step S113 is completed, step S114 can be executed.

[0135] Step S114: Calculate the sum of the newly added points and the accumulated points to obtain the points corresponding to the log data.

[0136] For users who watch multiple times, a weighted sum can be applied to each viewing. For example, if a user watches a video three times within a certain period, the scores from those three viewings can be added together to obtain additional points.

[0137] To prevent data anomalies caused by repeated viewings within a specific period, and also to prevent points accumulation, some implementations limit the number of times the same target media asset data can be viewed within a given period. For example, the same target media asset data cannot be viewed more than 5 times within a given period; if viewed more than 5 times, it will only be counted as 5 times, and any views exceeding 5 will not be added to the points. This avoids data anomalies caused by repeated viewings and also prevents users from maliciously accumulating points.

[0138] In the process of calculating the points corresponding to the log data, the user's review progress can be intuitively displayed by quantifying the points. Figure 12 This is a schematic diagram illustrating the user's review status as provided in some embodiments of this application, such as... Figure 12 As shown, some embodiments of this application can display user replay duration, number of replays, whether a replay was performed, etc., and can also be filtered based on certain conditions, thus enriching the statistical content of user replays during the live course replay process. Simultaneously, it can guide users to review, such as awarding more points for earlier review, thereby encouraging users to actively review learned knowledge during the optimal time period. It is understood that... Figure 12 It may also be displayed in other content or form, and this application does not specifically limit this. After step S400 is completed, step S500 can be executed.

[0139] Step S500: Control the display 260 to display an interface including an integral table and integral values.

[0140] After calculating the integral value based on the duration and the calculation weights corresponding to the target sub-stage, the display 260 can be controlled to show an interface including the integral table and the integral value. Figure 13 The integral illustration provided for some embodiments of this application, such as Figure 13 As shown, the monitor 260 can display a score table generated by the user's replay, and the score value obtained can be seen intuitively in the score table. In this way, the display content for users to watch during the replay of the live course is enriched, and the learning can be guided.

[0141] As can be seen from the above technical solutions, some embodiments of this application provide a method for displaying media asset data. In response to a user-inputted playback action command, log data is generated, including the start playback time, duration, media asset code, and user identifier of the media asset data. The method calculates the time interval between the end time and start playback time of the media asset data corresponding to the media asset code; queries the target sub-stage to which the log data belongs in the memory curve based on the time interval; calculates the integral value corresponding to the replayed log data based on the duration and the calculation weight corresponding to the target sub-stage; accumulates the integral value in an integral table; and controls the display 260 to display an interface including the integral table and the integral value. This application, by calculating and statistically analyzing the integral value of the log data replayed by the user, enriches the statistical content of user replay during the live course replay process and solves the problem of insufficient display of statistical information on user replay during the live course replay process.

[0142] Based on the above-described method for displaying media asset data, some embodiments of this application also provide a display device 200. Figure 14 This is a schematic diagram of a display device and execution flow provided in some embodiments of this application, such as... Figure 14 As shown, the display device 200 may include a display 260 and a controller 250. The display 260 is configured to display a playback interface, and the controller 250 is configured to perform the following steps:

[0143] Step S141: In response to the playback action command input by the user, the display device 200 generates log data, which includes the start playback time, duration, media asset encoding, and user identifier of the media asset data;

[0144] Step S142: Display device 200 calculates the time interval between the end time and the start time of the media asset data corresponding to the media asset code;

[0145] Step S143: The display device 200 queries the target sub-stage to which the log data belongs in the memory curve according to the time interval. The memory curve is a curve established according to the media asset code and user identifier. The memory curve is divided into multiple sub-stages according to time, and each sub-stage has a calculation weight.

[0146] Step S144: The display device 200 calculates the integral value based on the duration and the calculation weight corresponding to the target sub-stage, and accumulates the integral value into the integral table;

[0147] Step S145: Display device 200 controls display 260 to display an interface including an integral table and integral values.

[0148] As can be seen from the above technical solutions, some embodiments of this application provide a display device 200. This display device 200 enriches the statistical content of user replay during the live course replay process by calculating and statistically analyzing the log data points of user replay, thus solving the problem of insufficient display content of user replay statistics during the live course replay process.

[0149] This application also provides another display device 200 in some embodiments. The display device 200 may include a display 260, a communicator 220, and a controller 250. The display 260 is configured to display a playback interface; the communicator 220 is configured to establish a communication connection with the server 400; the controller 250 is configured to:

[0150] In response to user-inputted playback commands, log data is generated, including the start time, duration, media asset code, and user identifier of the media asset data. The log data is then sent to server 400, which calculates the time interval between the end time and start time of the media asset data corresponding to the media asset code. Based on the time interval, server 400 queries the target sub-stage to which the log data belongs in the memory curve, calculates the integral value based on the duration and the corresponding calculation weight of the target sub-stage, and accumulates the integral value in the integral table. The memory curve is established based on the media asset code and user identifier; it is divided into multiple sub-stages according to time, each with a calculation weight. Server 400 sends the integral value back, and server 400 controls the display 260 to show an interface including the integral table and the integral value.

[0151] As can be seen from the above technical solutions, some embodiments of this application provide a display device 200. The display device 200 sends log data to a server 400, which calculates the corresponding score value for the log data. Finally, the display device 200 controls the display 260 to display an interface including a score table and score values. The display device 200 establishes a communication connection with the server 400, enabling the display 260 to display an interface including a score table and score values, thereby enriching the statistical content of user replays during live course playback.

[0152] Based on the display device 200 described above, some embodiments of this application also provide a server 400, which includes a memory and a processor. The memory stores program instructions, and the processor executes the following steps by running the program instructions:

[0153] The system receives log data sent by the display device 200; calculates the time interval between the end time and the start time of the media data corresponding to the media asset code; queries the target sub-stage to which the log data belongs in the memory curve according to the time interval, calculates the integral value according to the duration and the calculation weight corresponding to the target sub-stage, and accumulates the integral value into the integral table; wherein, the memory curve is a curve established according to the media asset code and the user identifier; the memory curve is divided into multiple sub-stages according to time, and each sub-stage has a calculation weight; finally, the integral value is fed back to the display device 200.

[0154] As can be seen from the above technical solutions, some embodiments of this application provide a server 400, which calculates the integral value corresponding to the log data and feeds back the integral value to the display device 200, so as to enrich the statistical content of the user's replay during the live course replay process through the interaction between the server 400 and the display device 200.

[0155] Similar parts between the embodiments provided in this application can be referred to mutually. The specific implementation methods provided above are only a few examples under the general concept of some embodiments of this application and do not constitute a limitation on the protection scope of this application. For those skilled in the art, any other implementation methods extended from the solution of this application without creative effort shall fall within the protection scope of this application.

Claims

1. A server, characterized in that, include: The memory is configured to store program instructions; The processor executes the program instructions, and the processor is configured to: Receive log data sent by the display device; the log data includes the start time, duration, media asset encoding, and user identifier of the media asset data; Calculate the time interval between the end time of the media asset data corresponding to the media asset code and the start time of playback; The process involves querying the target sub-stage to which the log data belongs in the memory curve based on the time interval, calculating an integral value based on the duration and the corresponding weight of the target sub-stage, and accumulating the integral value in an integral table. The memory curve is established based on the media asset data corresponding to the media asset code and the log data corresponding to the user identifier. The memory curve characterizes the degree of forgetting of the media asset data by the user at different time intervals. The memory curve is divided into multiple sub-stages according to time, and each sub-stage has a calculation weight, which decreases as the time interval increases. The formula for calculating the integral value is: Integral score = (duration / total duration of media assets) × weight of the target sub-stage; The integral value is fed back to the display device.

2. The server according to claim 1, characterized in that, The processor is further configured to: Obtain the memory curve; Analyze the time pattern of the memory curve; The memory curve is divided into a preset number of sub-stages according to the time pattern.

3. The server according to claim 1, characterized in that, The processor is further configured to: The log data is assembled based on the start playback time, the duration, the media asset encoding, and the user identifier; Verify the log data; Store the log data that has passed verification.

4. The server according to claim 1, characterized in that, The processor is further configured to: The log data from the previous day is statistically analyzed at a preset time point; Generate a media asset list from the log data according to the media asset encoding; Write the completed list of media assets into the cache; After the write time to the cache exceeds the time threshold, the cache is written to the database.

5. The server according to claim 4, characterized in that, The log data also includes a date code, and the processor is further configured to: Add a completion flag to the flag bits of the cache for the log data that was statistically analyzed the previous day; At the preset time point, read the identifier bit from the cache; The statistical status of the log data is determined based on the identifier bit; If the statistical status of the log data is "statistics completed", traverse the list of media assets that have completed statistics in the database; The system queries the log data corresponding to the target media asset data based on the media asset code, and queries the log data of the target user on the target date and / or the target media asset data based on the media asset code, the user identifier, and the date code.

6. The server according to claim 5, characterized in that, The processor is further configured to: In response to log data where no target media asset data is detected in the database, log data corresponding to the target media asset data is read from the cache according to the media asset encoding; The read log data is inserted into the database.

7. The server according to claim 1, characterized in that, The processor executes a target sub-stage that queries the log data to which it belongs in the memory curve according to the time interval, and is further configured to: The end time of querying the target media asset data based on the media asset code; Calculate the time difference between the end time and the start time of the target media asset data to obtain the time interval; Based on the time interval, determine the target sub-stage to which the log data corresponding to the target media asset data belongs in the memory curve.

8. The server according to claim 1, characterized in that, The processor is further configured to calculate the integral value based on the duration and the computational weights corresponding to the target sub-stage. Obtain the total duration and duration of the media asset corresponding to the target media asset data; Obtain the target sub-stage to which the log data belongs and the corresponding calculated weight of the target sub-stage; A weighted summation is performed on the duration and the total duration of the media assets based on the calculated weights to obtain the new integral value; Calculate the sum of the newly added points and the accumulated points to obtain the points corresponding to the log data.

9. A display device, characterized in that, include: The monitor is configured to display the playback interface; The controller is configured as follows: In response to a user-inputted playback command, log data is generated, including the start time, duration, media asset encoding, and user identifier of the media asset data. Calculate the time interval between the end time of the media asset data corresponding to the media asset code and the start time of playback; query the target sub-stage to which the log data belongs in the memory curve according to the time interval, the memory curve is a curve established based on the media asset data corresponding to the media asset code and the log data corresponding to the user identifier, the memory curve is used to characterize the degree of forgetting of the media asset data by the user under different time intervals; the memory curve is divided into multiple sub-stages according to time, each sub-stage has a calculation weight, and the calculation weight decreases as the time interval increases; The integral value is calculated based on the duration and the calculation weight corresponding to the target sub-stage, and the integral value is accumulated in the integral table. The formula for calculating the integral value is as follows: Integral score = (duration / total duration of media assets) × weight of the target sub-stage; Control the display to show an interface including the integral table and the integral values.

10. A method for displaying media asset data, characterized in that, Applied to a display device, the display device including a display and a controller; the method for displaying the media asset data includes: In response to a user-inputted playback command, log data is generated, including the start time, duration, media asset encoding, and user identifier of the media asset data. Calculate the time interval between the end time of the media asset data corresponding to the media asset code and the start time of playback; The memory curve is used to query the target sub-stage to which the log data belongs in the memory curve according to the time interval. The memory curve is a curve established based on the media asset data corresponding to the media asset code and the log data corresponding to the user identifier. The memory curve is used to characterize the degree of forgetting of the media asset data by the user under different time intervals. The memory curve is divided into multiple sub-stages according to time. Each sub-stage has a calculation weight. The calculation weight decreases as the time interval increases. The integral value is calculated based on the duration and the calculation weight corresponding to the target sub-stage, and the integral value is accumulated in the integral table. The formula for calculating the integral value is as follows: Integral score = (duration / total duration of media assets) × weight of the target sub-stage; Control the display to show an interface including the integral table and the integral values.

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