Vocabulary processing method, apparatus, device, and computer-readable storage medium

Abstract

The application provides a vocabulary processing method and device, equipment and computer readable storage medium; it is related to computer technology and educational field; the method comprises the following steps: in response to the trigger operation of the entry for the target vocabulary unit, displaying the word card diagram corresponding to at least one group in the target vocabulary unit one by one on the man-machine interface, each word card diagram comprises the corresponding group, the phrase usage and the mastery degree of the corresponding group, and at least one vocabulary relationship diagram corresponding to at least one group is displayed on the man-machine interface, each vocabulary relationship diagram comprises a vocabulary node associated with any vocabulary in the corresponding group, and at least one phrase usage node connected with the vocabulary node, and the display attribute of the vocabulary node and the phrase usage node is related to the corresponding mastery degree. Through the application, the content and learning situation of the vocabulary unit can be intuitively reflected, and the intelligent degree and use experience in the learning process on the cloud education platform are improved.

Description

Technical Field

[0001] This application relates to the fields of computer technology and education, and in particular to a vocabulary processing method, apparatus, device, and computer-readable storage medium. Background Technology

[0002] Online education is an important application of the internet. Taking language learning as an example, when an application displays vocabulary for a specific vocabulary unit, it can show each word in the unit along with its phrase usage for the user to understand and memorize. However, users often find it difficult to track their progress across different units in a timely manner, thus hindering the development of targeted learning plans for each unit.

[0003] There is currently no effective technical solution for helping users understand their learning progress in a timely manner. Summary of the Invention

[0004] This application provides a vocabulary processing method, apparatus, terminal device, computer-readable storage medium, and computer program product, which can intuitively reflect the content and learning status of vocabulary units, and improve the intelligence level and user experience in the learning process.

[0005] The technical solution of this application embodiment is implemented as follows:

[0006] This application provides a vocabulary processing method, the method comprising:

[0007] In response to a trigger operation targeting an entry point of a vocabulary unit, word cards corresponding one-to-one with at least one group within the target vocabulary unit are displayed on the human-computer interaction interface. Each word card includes the corresponding group, the phrase usage of the corresponding group, and the level of mastery achieved.

[0008] The human-computer interaction interface displays at least one vocabulary relationship graph corresponding to the at least one group. Each vocabulary relationship graph includes a vocabulary node associated with any vocabulary in the corresponding group and at least one phrase usage node connected to the vocabulary node. The display attributes of the vocabulary node and the phrase usage node are related to the corresponding mastery level.

[0009] This application provides a vocabulary processing apparatus, the apparatus comprising:

[0010] The display module is configured to respond to a trigger operation on an entry point of a target vocabulary unit by displaying word cards on the human-computer interaction interface that correspond one-to-one with at least one group in the target vocabulary unit. Each word card includes the corresponding group, the phrase usage of the corresponding group, and the level of mastery for that group.

[0011] The display module is further configured to display at least one vocabulary relationship graph corresponding one-to-one with the at least one group on the human-computer interaction interface, wherein each vocabulary relationship graph includes a vocabulary node associated with any vocabulary in the corresponding group, and at least one phrase usage node connected to the vocabulary node, and the display attributes of the vocabulary node and the phrase usage node are related to the corresponding mastery level.

[0012] This application provides a terminal device for vocabulary processing, the terminal device comprising:

[0013] Memory, used to store executable instructions;

[0014] The processor, when executing executable instructions stored in the memory, implements any of the vocabulary processing methods provided in the embodiments of this application.

[0015] This application provides a computationally readable storage medium storing executable instructions for implementing the vocabulary processing method provided in this application when executed by a processor.

[0016] This application provides a computer program product, including a computer program or instructions, which, when executed by a processor, implement the vocabulary processing method provided in this application.

[0017] The embodiments of this application have the following beneficial effects:

[0018] By displaying vocabulary units with integrated flashcards and vocabulary relationship diagrams showing mastery levels, the vocabulary, vocabulary usage, and corresponding mastery levels within each unit can be visually presented in different forms. This helps users understand the content of the vocabulary unit and their current learning progress, providing valuable references for subsequent learning, enhancing the intelligence of human-computer interaction during the learning process, and contributing to a better user experience. Attached Figure Description

[0019] Figure 1A This is a schematic diagram illustrating the application mode of the vocabulary processing method provided in the embodiments of this application;

[0020] Figure 1B This is a schematic diagram illustrating the application mode of the vocabulary processing method provided in the embodiments of this application;

[0021] Figure 2 This is a schematic diagram of the structure of the terminal device 400 provided in the embodiments of this application;

[0022] Figure 3A This is a flowchart illustrating the vocabulary processing method provided in an embodiment of this application;

[0023] Figure 3BThis is a flowchart illustrating the vocabulary processing method provided in an embodiment of this application;

[0024] Figure 3C This is a flowchart illustrating the vocabulary processing method provided in an embodiment of this application;

[0025] Figure 3D This is a flowchart illustrating the vocabulary processing method provided in an embodiment of this application;

[0026] Figure 4 This is a flowchart illustrating the vocabulary processing method provided in an embodiment of this application;

[0027] Figure 5A This is a schematic diagram of the human-computer interaction interface provided in the embodiments of this application;

[0028] Figure 5B This is a schematic diagram of the human-computer interaction interface provided in the embodiments of this application;

[0029] Figure 5C This is a schematic diagram of the human-computer interaction interface provided in the embodiments of this application;

[0030] Figure 5D This is a schematic diagram of the human-computer interaction interface provided in the embodiments of this application;

[0031] Figure 6A This is a schematic diagram of the vocabulary relationship diagram provided in the embodiments of this application;

[0032] Figure 6B This is a schematic diagram of the vocabulary relationship diagram provided in the embodiments of this application;

[0033] Figure 7A This is a schematic diagram of the human-computer interaction interface provided in the embodiments of this application;

[0034] Figure 7B This is a schematic diagram of the human-computer interaction interface provided in the embodiments of this application;

[0035] Figure 7C This is a schematic diagram of the tree structure provided in the embodiments of this application;

[0036] Figure 8A This is an optional flowchart illustrating the vocabulary processing method provided in an embodiment of this application;

[0037] Figure 8B This is an optional flowchart illustrating the vocabulary processing method provided in an embodiment of this application;

[0038] Figure 8C This is an optional flowchart illustrating the vocabulary processing method provided in an embodiment of this application;

[0039] Figure 8DThis is an optional flowchart illustrating the vocabulary processing method provided in an embodiment of this application;

[0040] Figure 8E This is an optional flowchart of the vocabulary processing method provided in the embodiments of this application. Detailed Implementation

[0041] To make the objectives, technical solutions, and advantages of this application clearer, the application will be further described in detail below with reference to the accompanying drawings. The described embodiments should not be regarded as limitations on this application. All other embodiments obtained by those skilled in the art without creative effort are within the scope of protection of this application.

[0042] In the following description, the terms "first" and "second" are used merely to distinguish similar objects and do not represent a specific ordering of objects. It is understood that "first" and "second" may be interchanged in a specific order or sequence where permitted, so that the embodiments of this application described herein can be implemented in an order other than that illustrated or described herein.

[0043] Unless otherwise defined, all technical and scientific terms used herein have the same meaning as commonly understood by one of ordinary skill in the art to which this application belongs. The terminology used herein is for the purpose of describing embodiments of this application only and is not intended to limit this application.

[0044] In the implementation of this application, the collection and processing of relevant data should strictly comply with the requirements of relevant laws and regulations, obtain the informed consent or separate consent of the personal information subject, and carry out subsequent data use and processing within the scope of laws and regulations and the authorization of the personal information subject.

[0045] Before providing a further detailed description of the embodiments of this application, the nouns and terms involved in the embodiments of this application will be explained, and the nouns and terms involved in the embodiments of this application shall be interpreted as follows.

[0046] 1) In response to, used to indicate the conditions or states on which the operation performed depends. When the conditions or states on which it depends are met, one or more operations performed may be performed in real time or with a set delay. Unless otherwise specified, there is no restriction on the order in which the multiple operations are performed.

[0047] 2) Vocabulary Units: These are units arranged according to the overall structure of the vocabulary textbook. Each unit includes vocabulary, vocabulary notes, phrase usage, and phrase usage notes.

[0048] 3) Rendering, a technical means of mapping invisible data to visual graphics.

[0049] 4) Throttle, which means obtaining parameters once every certain period of time.

[0050] 5) Debouncing, or debounce, means executing only on the last trigger. The throttling debouncing function periodically retrieves the parameters of the monitored event to detect when the event is triggered. It then executes the subsequent operations corresponding to the event's trigger only when the event is last triggered. This prevents performance issues caused by frequent triggering of the monitored event.

[0051] 6) The mixins tool is used to mix child components into a parent component to create a new parent component. If the child component and the parent component have options with the same name, the options with the same name will be merged. For example, if the child component and the parent component have the same data object, the data objects will be recursively merged within the new parent component, and the data in the parent component will take precedence when data conflicts occur.

[0052] For language learning applications, taking English vocabulary learning as an example, the vocabulary and vocabulary annotations in a vocabulary unit are usually displayed separately so that users can memorize the words one by one. During the learning process, users find it difficult to understand the relationship between words, the relationship between words and the usage of related phrases, and also find it difficult to confirm the specific learning progress of the vocabulary unit.

[0053] To address the aforementioned technical problems, embodiments of this application provide a vocabulary processing control method, a vocabulary processing control device, a terminal device for vocabulary processing control, a computationally readable storage medium, and a computer program product. To facilitate a clearer understanding of the vocabulary processing control method provided in this application, exemplary implementation scenarios of the vocabulary processing method are first described. The human-computer interaction interface can be entirely based on the output of the terminal device, or based on the collaboration between the terminal device and the server.

[0054] The following section introduces the application scenarios in conjunction with terminal devices.

[0055] In one implementation scenario, refer to Figure 1A , Figure 1A This is a schematic diagram illustrating the application mode of the vocabulary processing method provided in this application embodiment. It is applicable to some application modes that rely entirely on the graphics processing hardware computing power of the terminal device 400 to complete the relevant data calculation of the human-computer interaction interface 100, such as stand-alone / offline mode applications, which output the screen of the human-computer interaction interface through various types of terminal devices 400 such as smartphones, tablets, and virtual reality / augmented reality devices.

[0056] When visual perception is formed in the human-computer interaction interface 100, the terminal device 400 calculates the data required for display through graphics computing hardware, and completes the loading, parsing and rendering of the display data. The graphics output hardware outputs video frames that can form visual perception of the human-computer interaction interface screen. For example, a two-dimensional video frame is presented on the screen of a smartphone, or a three-dimensional video frame is projected onto the lens of augmented reality / virtual reality glasses. In addition, in order to enrich the perception effect, the terminal device 400 can also use different hardware to form one or more of auditory perception, tactile perception, motion perception and taste perception.

[0057] As an example, the terminal device 400 runs a standalone vocabulary learning application. During the operation of the vocabulary learning application, it outputs the screen of the human-computer interaction interface. For example, when the user triggers the entry point of the target vocabulary unit in the human-computer interaction interface, the terminal device 400 responds to the triggering operation of the entry point of the target vocabulary unit and displays the word card diagram and vocabulary relationship diagram corresponding to the grouping of the target vocabulary unit in the human-computer interaction interface.

[0058] In another implementation scenario, see Figure 1B , Figure 1B This is a schematic diagram of the application mode of the vocabulary processing method provided in the embodiments of this application. It is applied to the terminal device 400 and the server 200, and is suitable for the application mode that relies on the computing power of the server 200 to complete the screen calculation of the human-computer interaction interface and output the screen of the human-computer interaction interface to the terminal device 400.

[0059] Taking the visual perception of the human-computer interaction interface 100 as an example, the server 200 calculates the display data (such as scene data) related to the human-computer interaction interface and sends it to the terminal device 400 via the network 300. The terminal device 400 relies on graphics computing hardware to load, parse, and render the calculated display data, and relies on graphics output hardware to output the image of the human-computer interaction interface to form visual perception. For example, two-dimensional video frames can be displayed on the screen of a smartphone, or video frames that achieve a three-dimensional display effect can be projected onto the lenses of augmented reality / virtual reality glasses. As for the perception of the form of the human-computer interaction interface image, it can be understood that it can be achieved with the help of the corresponding hardware output of the terminal device 400, such as using a microphone to form auditory perception, using a vibrator to form tactile perception, and so on.

[0060] As an example, terminal device 400 runs a client (e.g., a web-based vocabulary learning application) and interacts with the application by connecting to an application server (i.e., server 200). Terminal device 400 outputs the human-computer interaction interface of the vocabulary learning application. For example, when a user triggers an entry point for a target vocabulary unit in the human-computer interaction interface, the client in terminal device 400 responds to the triggering operation for the entry point of the target vocabulary unit by sending a trigger request for the target vocabulary unit to server 200. Server 200 obtains the word card diagram and vocabulary relationship diagram corresponding to the grouping of the target vocabulary unit and sends the word card diagram and vocabulary relationship diagram to terminal device 400 for display in the human-computer interaction interface 100 of terminal device 400.

[0061] In some embodiments, the terminal device 400 can implement the vocabulary processing method provided in this application embodiment by running a computer program. For example, the computer program can be a native program or software module in an operating system; it can be a native application (APP), that is, a program that needs to be installed in the operating system to run, such as a game APP (i.e., the client mentioned above); it can also be a mini-program, that is, a program that only needs to be downloaded into a browser environment to run; or it can be a mini-program that can be embedded in any APP. In short, the above-mentioned computer program can be any form of application, module or plugin.

[0062] The embodiments of this application can be implemented with the help of cloud technology, which refers to a hosting technology that unifies a series of resources such as hardware, software, and networks within a wide area network or local area network to realize the computation, storage, processing, and sharing of data.

[0063] Cloud Computing Education (CCEDU) refers to an education platform service based on a cloud computing business model. On the cloud platform, all educational institutions, training institutions, enrollment service agencies, publicity agencies, industry associations, management agencies, industry media, legal structures, etc., are centrally integrated into a resource pool. These resources can be displayed and interacted with, facilitating on-demand communication and reaching agreements, thereby reducing education costs and improving efficiency.

[0064] As an example, server 200 can be a standalone physical server, a server cluster or distributed system composed of multiple physical servers, or a cloud server providing basic cloud computing services such as cloud services, cloud databases, cloud computing, cloud functions, cloud storage, network services, cloud communication, middleware services, domain name services, security services, CDN, and big data and artificial intelligence platforms. Terminal device 400 can be a smartphone, tablet, laptop, desktop computer, smart speaker, or smartwatch, but is not limited to these. Terminal device 400 and server 200 can be directly or indirectly connected via wired or wireless communication, which is not limited in this embodiment.

[0065] In some embodiments, multiple servers may form a blockchain, and server 200 is a node on the blockchain. Each node in the blockchain may have an information connection, and the nodes may transmit information through the aforementioned information connection.

[0066] Blockchain is a novel application model of computer technologies such as distributed data storage, peer-to-peer transmission, consensus mechanisms, and encryption algorithms. Essentially, a blockchain is a decentralized database, a chain of data blocks linked using cryptographic methods. Each data block contains information about a batch of network transactions, used to verify the validity of the information (anti-counterfeiting) and generate the next block. A blockchain can include a blockchain underlying platform, a platform product service layer, and an application service layer. The data related to the vocabulary processing method provided in this application embodiment (e.g., the logic of vocabulary processing, the image presented after aggregation) can be stored on the blockchain.

[0067] See Figure 2 , Figure 2 This is a schematic diagram of the structure of the vocabulary processing terminal device 400 provided in the embodiments of this application. Figure 2 The terminal device 400 shown includes at least one processor 410, a memory 450, at least one network interface 420, and a user interface 430. The various components in the terminal device 400 are coupled together via a bus system 440. It is understood that the bus system 440 is used to implement communication between these components. In addition to a data bus, the bus system 440 also includes a power bus, a control bus, and a status signal bus. However, for clarity, ... Figure 2 The general labeled all buses as Bus System 440.

[0068] The processor 410 can be an integrated circuit chip with signal processing capabilities, such as a general-purpose processor, a digital signal processor (DSP), or other programmable logic devices, discrete gate or transistor logic devices, discrete hardware components, etc. The general-purpose processor can be a microprocessor or any conventional processor, etc.

[0069] User interface 430 includes one or more output devices 431 that enable the presentation of media content, including one or more speakers and / or one or more visual displays. User interface 430 also includes one or more input devices 432, including user interface components that facilitate user input, such as a keyboard, mouse, microphone, touch screen display, camera, other input buttons and controls.

[0070] The memory 450 may be removable, non-removable, or a combination thereof. Exemplary hardware devices include solid-state storage, hard disk drives, optical disk drives, etc. The memory 450 may optionally include one or more storage devices physically located away from the processor 410.

[0071] The memory 450 may include volatile memory or non-volatile memory, or both. The non-volatile memory may be read-only memory (ROM), and the volatile memory may be random access memory (RAM). The memory 450 described in this application embodiment is intended to include any suitable type of memory.

[0072] In some embodiments, memory 450 is capable of storing data to support various operations, examples of which include programs, modules, and data structures or subsets or supersets thereof, as illustrated below.

[0073] Operating system 451 includes system programs for handling various basic system services and performing hardware-related tasks, such as the framework layer, core library layer, and driver layer, for implementing various basic business functions and handling hardware-based tasks.

[0074] The network communication module 452 is used to reach other computing devices via one or more (wired or wireless) network interfaces 420, exemplary network interfaces 420 including Bluetooth, WiFi, and Universal Serial Bus (USB).

[0075] Presentation module 453 enables the presentation of information (e.g., a user interface for operating peripheral devices and displaying content and information) via one or more output devices 431 associated with user interface 430 (e.g., a display screen, a speaker, etc.).

[0076] The input processing module 454 is used to detect and translate one or more user inputs or interactions from one or more input devices 432.

[0077] In some embodiments, the apparatus provided in this application can be implemented in software. Figure 2 A vocabulary processing device 455 stored in memory 450 is shown. This device can be software in the form of programs and plug-ins, and includes the following software modules: a display module 4551. These modules are logically ordered and can therefore be arbitrarily combined or further separated according to their implemented functions. The functions of each module will be described below.

[0078] In other embodiments, the apparatus provided in this application can be implemented in hardware. For example, the apparatus provided in this application can be a processor in the form of a hardware decoding processor, which is programmed to execute the vocabulary processing method provided in this application. For example, the processor in the form of a hardware decoding processor can be one or more application-specific integrated circuits (ASICs), DSPs, programmable logic devices (PLDs), complex programmable logic devices (CPLDs), field-programmable gate arrays (FPGAs), or other electronic components.

[0079] In some embodiments, the terminal device or server can implement the vocabulary processing method provided in this application by running a computer program. For example, the computer program can be a native program or software module in an operating system; it can be a native application (APP), that is, a program that needs to be installed in the operating system to run, such as a vocabulary learning APP; it can also be a mini-program, that is, a program that only needs to be downloaded to a browser environment to run; or it can be a mini-program that can be embedded in any APP. In short, the above-mentioned computer program can be any form of application, module or plugin.

[0080] The vocabulary processing method provided in this application embodiment can be derived from... Figure 1AThe terminal device 400 can be executed independently, or it can be... Figure 1B The terminal device 400 and the server 200 work together to execute the task. For example, in step 101, the display of the word card diagram of the target vocabulary unit group can be executed by the terminal device 400 and the server 200 working together. After the server 200 calculates the display data of the word card diagram of the target vocabulary unit group, it returns the display data to the terminal device 400 for display.

[0081] Below, by Figure 1A The following is an example of a terminal device 400 executing the vocabulary processing method provided in this application embodiment. See also... Figure 3A , Figure 3A This is a flowchart illustrating the vocabulary processing provided in the embodiments of this application, which will be combined with... Figure 3A The steps shown will be explained, and the example will be taken with the terminal device as the execution subject.

[0082] It should be noted that, Figure 3A The method shown can be executed by various forms of computer programs running on terminal device 400, and is not limited to the client described above, such as the operating system 451, software modules and scripts mentioned above. Therefore, the client should not be regarded as a limitation on the embodiments of this application.

[0083] In step 101, in response to a trigger operation for an entry into the target vocabulary unit, word cards corresponding one-to-one with at least one group in the target vocabulary unit are displayed on the human-computer interaction interface.

[0084] Here, each word card includes the corresponding group, the usage of the phrases in the corresponding group, and the level of mastery.

[0085] As an example, the target vocabulary unit is one of multiple vocabulary units included in the vocabulary teaching material. In this application embodiment, the vocabulary can be English, French, Japanese, or other language vocabulary; this application embodiment uses English vocabulary as an example for illustration. The triggering operation can be a mouse click, mouse hover, touchscreen click, touchscreen long press, touchscreen swipe, etc.

[0086] As an example, the target vocabulary unit can be grouped based on derivational relationships or part-of-speech conversion relationships between words. Each group includes at least one word and a phrase usage associated with that word. The flashcard image is the flashcard image of the currently displayed group of the target vocabulary unit. The number and size of the flashcard images displayed in the human-computer interface depend on the size or resolution of the human-computer interface. The human-computer interface can display flashcard images corresponding to one or more groups, or flashcard images of all groups. When displaying multiple flashcard images, multiple flashcard images can be displayed using a page-turning or waterfall layout.

[0087] As an example, the level of mastery can be described verbally, such as: no mastery, partial mastery, complete mastery, etc. When mastery of a word has not been tested, the level of mastery can be marked as "untested mastery" or "partial mastery." Mastery can also be expressed as a percentage, such as: 0% mastery, 100% mastery, etc. There can be a conversion relationship between the mastery level shown as a percentage and the verbal description of mastery; for example, complete mastery corresponds to 100% mastery, and no mastery corresponds to 0% mastery.

[0088] refer to Figure 5A , Figure 5A This is a schematic diagram of the human-computer interaction interface provided in the embodiments of this application. Figure 5A 110 in the text is the word card image area. The word card image display area 110 is used to display at least one word card image. After receiving a trigger operation for the entry of the target vocabulary unit, the word card image area 110 displays word card images that correspond one-to-one with at least one group in the target vocabulary unit on the human-computer interaction interface.

[0089] In step 102, at least one word relationship diagram corresponding to at least one group is displayed on the human-computer interaction interface.

[0090] Here, the word card diagram and the vocabulary relationship diagram are displayed simultaneously, and step 102 is also executed after the trigger operation for the entry of the target vocabulary unit. Each vocabulary relationship diagram includes a vocabulary node associated with any word in the corresponding group, and at least one phrase usage node connected to the vocabulary node, and the display attributes of the vocabulary node and the phrase usage node are related to the corresponding mastery level.

[0091] As an example, the shape of the word nodes and phrase nodes in the word relationship graph can be circular or other shapes. The word nodes and phrase nodes in the word relationship graph are related through connections. At least one group of all word relationship graphs, a portion of the word relationship graphs, or all word relationship graphs can be displayed in the human-computer interaction interface.

[0092] Here, the types of display attributes include at least one of color, size, and special effects, and the degree of significance of the display attribute implementation is positively correlated with the degree of mastery of the display attribute representation.

[0093] As an example, a display attribute can be color; for instance, the higher the mastery level, the darker the color of the node. A display attribute can also be texture density; for instance, the higher the mastery level, the denser the texture. A display attribute can also be node size; for instance, the higher the mastery level, the larger the node.

[0094] Continue to refer to Figure 5A , Figure 5A 120 in the text represents the vocabulary relationship diagram area. Vocabulary relationship diagram area 120 is used to display at least one vocabulary relationship diagram. The ellipsis in vocabulary relationship diagram area 120 indicates that, in addition to... Figure 5A In addition to the vocabulary relationship diagram 1 shown in the image, the vocabulary relationship diagram area 120 can also display multiple vocabulary relationship diagrams.

[0095] As an example, upon receiving a trigger operation for an entry point targeting a lexical unit, at least one lexical relationship graph corresponding to at least one group is displayed in the lexical relationship graph area 120.

[0096] As an example, this application does not limit the actual area of ​​the word card diagram and vocabulary relationship diagram displayed in the human-computer interaction interface. Figure 5A Each region in the document is planned only for the convenience of explaining the embodiments of this application.

[0097] As an example, the data corresponding to the usage of words and phrases grouped by the target vocabulary unit can be rendered into a one-to-one correspondence word card chart and a vocabulary relationship chart based on the relationship graph in ECharts (a data visualization chart library). This embodiment uses ECharts as an example for illustration; in practical applications, other data visualization software or components can also be used to perform the rendering operations in this embodiment.

[0098] refer to Figure 6A , Figure 6A This is a schematic diagram of the vocabulary relationship diagram provided in the embodiments of this application. Figure 6A It includes two vocabulary relationship graphs. In the upper vocabulary relationship graph, each node has not yet been rendered according to the mastery level of each node. In the lower vocabulary relationship graph, each node is updated and rendered according to the mastery level of each node. Figure 6A Each node is represented as a circle, with texture as a display attribute. Different textures indicate the level of mastery corresponding to each node. 601 is a vocabulary node, corresponding to the vocabulary word "agreement." There are lines connecting vocabulary nodes and phrase nodes. 602 is a phrase node, one of which corresponds to the phrase usage "agreement on" associated with the vocabulary word.

[0099] In some embodiments, in response to a focusing operation on a target node, a numerical value indicating the level of mastery of the target node is displayed in the vocabulary relation graph.

[0100] As an example, refer to Figure 6B , Figure 6B This is a schematic diagram of a vocabulary relationship diagram provided in an embodiment of this application. Figure 6BTable 603 is a mastery level indicator. The target node is the phrase node corresponding to "agreement on". When the target node is selected by focusing, the vocabulary relationship graph in the human-computer interaction interface should display the mastery level indicator table 603 for the target node. The mastery level indicator table 603 includes a mastery level value of 50% and a mastery level progress bar, making the mastery level display more intuitive. Focusing operations can include hovering, clicking, and swiping.

[0101] In some embodiments, reference Figure 3B , Figure 3B This is a flowchart illustrating the vocabulary processing method provided in an embodiment of this application; for example, in Figure 3B Step 101 also includes: Step 1011.

[0102] In step 1011, a word card diagram corresponding one-to-one with at least one group in the target vocabulary unit is displayed on the human-computer interaction interface. The word card diagram displays multiple labels, at least one phrase usage corresponding to the vocabulary included in the focus label, the mastery level corresponding to the vocabulary included in the focus label, and the mastery level corresponding to at least one phrase usage of the vocabulary included in the focus label.

[0103] Here, each label includes a word from its corresponding group. Different labels correspond to different words. The state of a label includes a selected focused state and an unselected unfocused state. A focused label is the label that is in the focused state among multiple labels.

[0104] As an example, focus actions can include mouse click, mouse hover, long press, tap, and swipe.

[0105] refer to Figure 5B , Figure 5B This is a schematic diagram of the human-computer interaction interface provided in the embodiments of this application. Figure 5B In the word card image area 110, a word card image is displayed. The word card image includes three labels (agreement, disagree, and disagreement) for words belonging to the same group in the target vocabulary unit. If the currently selected focus label is the label corresponding to the word "agreement", then the phrase usage associated with the word "agreement" will be displayed. Figure 5B The students' mastery of the Chinese word "agreement" and its related phrases was 0%.

[0106] In some embodiments, the human-computer interaction interface can display multiple word cards, which can be displayed as a list. The word card list includes multiple word cards that correspond one-to-one with multiple groups in the target vocabulary unit. For example, displaying a word card list containing multiple word cards, with the currently selected word card displayed in full and the unselected word cards collapsed. Another example is displaying a word card list containing multiple word cards; when not focused, only the multiple labels corresponding to each word card are displayed; when a focus operation is received, the complete content of the word card corresponding to the label selected by the focus operation is displayed.

[0107] As an example, the sorting methods for multiple flashcards include: ascending or descending order of the learning time (which can be the cumulative learning time or the last learning time) of the groups corresponding to the flashcards, and ascending or descending order of the mastery level of the groups corresponding to the flashcards. For example, using the ascending order of cumulative learning time as the sorting criterion, the flashcard ranked first has the shortest cumulative learning time, and the cumulative learning time of the following flashcards increases sequentially. When two flashcards have the same cumulative learning time, they are sorted according to the ascending order of the last learning time.

[0108] As an example, if there is no corresponding learning record or mastery level for a word card, the sorting can be determined by the average time or mastery level of users using that word card in big data, or by sorting according to the default order in English textbooks.

[0109] As an example, the order of multiple tags can be sorted according to the mastery level of the corresponding vocabulary, learning time, default order, etc. Similarly, the phrase usages corresponding to the vocabulary included in the focused tags can also be sorted according to the mastery level of phrase usage, learning time, default order, etc. Learning time can be the cumulative learning time of the vocabulary corresponding to the tag or the last learning time.

[0110] In some embodiments, before displaying at least one phrase usage corresponding to the words included in the focus tag, multiple tags that are not in a focus state are displayed; in response to a selection operation, the selected tag among the multiple tags is used as the focus tag, the focus tag is displayed based on the display attributes of the focus state, and other tags among the multiple tags that are not in a focus state are displayed based on the display attributes of the non-focus state.

[0111] Here, the display attributes corresponding to the focused state and the unfocused state are different. The display attributes of the focused state are more significant than those of the unfocused state. The display attributes can be at least one of shape, size, color, and special effects.

[0112] As an example, continue to refer to Figure 5B , Figure 5BThe tag corresponding to "agreement" is in focus, and its height is greater than the height of other tags that are not in focus.

[0113] In some embodiments, before displaying at least one phrase usage corresponding to the words included in the focus tag, multiple tags are displayed in a specific sorting order, with the first tag in the sorting order being used as the focus tag by default or automatically, the focus tag being displayed based on the display attributes of the focus state, and other tags among the multiple tags that are not in the focus state being displayed based on the display attributes of the non-focus state.

[0114] As an example, sorting methods include: ascending or descending order of the learning time of the vocabulary included in the tags, and ascending or descending order of the mastery level of the vocabulary corresponding to the tags. Random sorting is also possible.

[0115] In some embodiments, the present application further includes: in response to a switching operation, replacing the old focus tag displayed before the switching operation with the tag triggered by the switching operation as a new focus tag, displaying at least one phrase usage corresponding to the words included in the new focus tag, and stopping the display of at least one phrase usage corresponding to the words included in the old focus tag; displaying the mastery level corresponding to the words included in the new focus tag and the mastery level corresponding to at least one phrase usage corresponding to the words included in the new focus tag, and stopping the display of the mastery level corresponding to the words included in the old focus tag and the mastery level corresponding to at least one phrase usage corresponding to the words included in the old focus tag.

[0116] Here, the display attributes based on the focus state show the newly focused label, while the display attributes based on the non-focus state show the other labels from the multiple labels, excluding the newly focused label. Multiple labels refer to multiple labels within the same card image.

[0117] In some embodiments, the number of phrases corresponding to the words included in the new focus label is different from that in the old focus label, and the area occupied when displayed is different. If the area occupied by the new focus label is larger or smaller, the size of the word card displayed in the human-computer interaction interface should be adjusted.

[0118] As an example, the target height of the word card is determined based on the number of at least one phrase usages corresponding to the words included in the new focus label, the rendering height, and the base height of the word card. The height of the word card image containing the label triggered by the switching operation is then updated based on the target height. The rendering height can be the height required for each phrase usage (phrase usage content + phrase usage annotation content) determined according to the font display size or resolution set in the human-computer interaction interface. The total phrase height is obtained by multiplying the number of at least one phrase usages corresponding to the words included in the new focus label by the rendering height. The target height of the word card is then obtained by adding the total phrase height to the base height of the word card. For example, when a label in the word card image is selected and switched by a focus operation, the number of phrase usages associated with the selected label is determined. The total phrase height is obtained by multiplying the number of phrase usages by the rendering height of each phrase usage. The target height of the word card is then obtained by adding the total phrase height to the base height of the word card.

[0119] Continuing with the example of rendering based on ECharts, we can set a listener for the resize event of the card chart's display area in each group of vocabulary units to detect changes in the display area. However, since the human-computer interaction interface can display multiple cards, there are multiple canvases for vocabulary unit groups. To facilitate unified processing, we use the mixins tool to implement a general charts-resize-mixin (repeated chart resizing). Inside the mixins tool, we first obtain the element identified as chart (i.e., the card chart in this embodiment) and initialize them one by one using echats.init. When the window.resize event is heard, the resize event of each chart is triggered. Alternatively, we can use a call-based triggering method. We can add a throttling and debouncing function inside the chart's resize event to prevent performance issues caused by frequent resize event triggering. Then, we introduce the mixins tool into the component corresponding to each card chart. When performing a label switching operation, the chart's resize event is triggered simultaneously, causing the card chart to be re-rendered.

[0120] As an example, refer to Figure 5B , Figure 5B The word card area 110 and the vocabulary relationship diagram area 120 are at the same height. If the height of the word card changes, the height of the vocabulary relationship diagram display area 120 will be adjusted accordingly.

[0121] In some embodiments, prior to step 102, the present application embodiment further includes: displaying a vocabulary relationship graph entry corresponding to each word card in the human-computer interaction interface; and proceeding to step 102 in response to a triggering operation for at least one vocabulary relationship graph entry.

[0122] As an example, the display of the vocabulary relationship diagram can be triggered by the user or automatically by the terminal device 400. The word card diagram and vocabulary relationship diagram can also be automatically displayed after triggering the entry point of a target vocabulary unit. When the required display area for the vocabulary relationship diagram is larger than the area of ​​the vocabulary relationship diagram region, the vocabulary relationship diagram region can be automatically adjusted according to the required display area, or a scroll bar can be set within the vocabulary relationship diagram region, allowing users to scroll through the various vocabulary relationship diagrams within the region.

[0123] In some embodiments, reference Figure 3C , Figure 3C This is a flowchart illustrating the vocabulary processing method provided in the embodiments of this application; Figure 3C Step 102 also includes step 1021, and step 1022 following step 1021.

[0124] In step 1021, at least one vocabulary relationship graph corresponding to at least one group is displayed on the human-computer interaction interface, wherein the display attributes of vocabulary nodes and phrase usage nodes are the default display attributes.

[0125] Here, each lexical relationship graph includes a lexical node associated with any word in the corresponding group, and at least one phrase usage node connected to the lexical node.

[0126] As an example, in step 1021, the display attributes of all nodes in the lexical relationship graph are uniform, and the default display attribute can be the lowest salience achieved by the display attribute. For example, if the display attribute is color, and the salience corresponding to color is the lightness or darkness of the color, then the default display attribute can be light color, and the lexical relationship graph should display all nodes as white. As another example, if the display attribute is size, and the salience corresponding to size is the size itself, then the default display attribute can be the smallest size within the size range, and the lexical relationship graph should display all nodes as the smallest size within the size range.

[0127] In step 1022, in response to the focus operation, the display target node is updated in the vocabulary relation graph according to the target display attributes of the focused target node.

[0128] Here, the target node can be a vocabulary node or a phrase usage node, and the target display attributes are related to the level of mastery of the vocabulary or phrase usage corresponding to the target node. Target display attributes include at least one of color, size, and effects.

[0129] As an example, focus actions can be clicks, swipes, or hovering.

[0130] As an example, after the focus operation, a parameter is determined to indicate the mastery level of the target vocabulary associated with the selected target node. Based on this mastery level parameter, the target display attribute of the target node is determined. For instance, if any node is selected as the target node by the focus operation, the mastery level of the target node is obtained. If the mastery level is "complete mastery," the display attribute of the target node is adjusted to the display attribute corresponding to "complete mastery," and the display of the target node is updated. For example, if the display attribute corresponding to "complete mastery" is dark red, the display color of the target node is updated from white to dark red.

[0131] In some embodiments, reference Figure 3D , Figure 3D This is a flowchart illustrating the vocabulary processing method provided in the embodiments of this application; Figure 3D Step 102 also includes step 1021, and step 1023 following step 1021. Figure 3D Step 1021 and Figure 3C The same as step 1021 in the previous section.

[0132] In step 1023, in response to the mastery level viewing operation, each node in the vocabulary relationship graph is updated and displayed according to the target display attribute of each node in the vocabulary relationship graph.

[0133] Here, the target display attributes of each node are related to the level of mastery of the corresponding vocabulary or phrase usage. Target display attributes include at least one of color, size, and effects.

[0134] As an example, the mastery level viewing operation can be applied to the word card diagram area or the vocabulary relationship diagram area in the human-computer interaction interface, or it can be applied to the blank area of ​​the human-computer interaction interface. The mastery level viewing operation can be a focus operation, such as clicking, swiping, or hovering. After the mastery level viewing operation, the word nodes and phrase usage nodes in each vocabulary relationship diagram are uniformly updated and displayed, and the display attributes of all vocabulary relationship diagrams are refreshed in batches.

[0135] In some embodiments, reference Figure 4 , Figure 4 This is a flowchart illustrating the vocabulary processing method provided in the embodiments of this application; steps 103, 104, and 105 are included before step 101.

[0136] In step 103, the detection entry for the target vocabulary unit is displayed.

[0137] As an example, refer to Figure 5A, Figure 5A 130 is the vocabulary test entry point, which is also the test entry point for the target vocabulary unit. The test entry point can be continuously displayed in the human-computer interaction interface in the vocabulary learning mode, or it can be automatically triggered when the user has learned all the words in the target vocabulary unit, or it can be triggered by a corresponding trigger operation.

[0138] In step 104, in response to a trigger operation on the detection entry point, multiple test questions associated with the target vocabulary unit are displayed on the human-computer interaction interface.

[0139] As an example, refer to Figure 7A , Figure 7A This is a schematic diagram of the human-computer interaction interface provided in an embodiment of this application. Upon receiving a trigger operation targeting the detection entry point, the screen in the human-computer interaction interface switches from the vocabulary learning screen to the test question screen. Figure 7A This is a diagram of the areas displayed on the human-computer interaction interface when test questions are shown. 550 is the answer sheet area, used to display the answer sheet; 560 is the test area, used to display the test questions and the answer key; 530 is the reference answer area, used to display the reference answers for the test questions; 540 is the page-turning button, which, in response to a trigger operation, switches the currently displayed test question to the next test question in the human-computer interaction interface.

[0140] As an example, refer to Figure 7B , Figure 7B This is a schematic diagram of the human-computer interaction interface provided in the embodiments of this application. Figure 7B This serves as an example of displaying test questions in a human-computer interaction interface. The answer sheet includes the question number for each test question, the test result for each test question, and the total time consumed or the remaining time for the test.

[0141] In some embodiments, in response to a trigger operation on the question number corresponding to each test question in the answer sheet, the currently displayed test question in the human-computer interaction interface is switched to the test question selected by the trigger operation. This allows the user to quickly switch the currently displayed test question.

[0142] As an example, the test questions can be written, multiple-choice, or matching, etc. The test questions assess the usage of words or phrases within the vocabulary units.

[0143] In step 105, in response to the submission of answers to multiple test questions, the mastery level of each word and each phrase in the target vocabulary unit is determined based on the submitted answers.

[0144] As an example, if no answer is submitted for any test question, the mastery level of the corresponding vocabulary or phrase usage is determined by the previous answer to that test question; if no previous answer exists, the mastery level of the corresponding vocabulary or phrase usage for any test question is marked as not mastered or to be tested.

[0145] In some embodiments, step 105 further includes determining the mastery level of each phrase usage based on the accuracy rate of the answers submitted for the test questions associated with each phrase usage; determining the sum of the mastery levels of each phrase usage corresponding to each word, and using the ratio of the sum to the number of phrase usages corresponding to each word as the mastery level of each word.

[0146] As an example: If there are two test questions associated with phrase usage A, and the number of correct answers to the two test questions is 1 and the number of incorrect answers is 1, then the correctness rate of the submitted answers to the test questions associated with phrase usage A is 50%, and the mastery level of phrase usage A is 50%.

[0147] As an example, refer to Figure 5C , Figure 5C The mastery level of "agreement" is 46%. "Agreement" is associated with four phrase usages, with mastery levels of 67%, 33%, 33%, and 50% for each phrase usage, respectively. The sum of these mastery levels is 183%. Since there are four phrase usages, the ratio of these four is rounded to obtain a mastery level of 46%. In this embodiment, the mastery level is rounded to two decimal places, but it can also be rounded to more decimal places, for example, the mastery level of "agreement" is 45.75%. Mastery level can also be expressed as a fraction, for example, the mastery levels of each phrase usage associated with "agreement" are two-thirds, one-third, one-third, and one-half.

[0148] In some embodiments, triggering the detection entry may fail. If triggering fails, the mastery level is determined based on the previous test results. If there are no previous test results and no historical data corresponding to the mastery level, the mastery level of all target vocabulary units is set to zero.

[0149] In some embodiments, the human-computer interaction interface also displays a mastery statistics chart corresponding to the target vocabulary unit; the mastery statistics chart includes at least one of the following: the total number of words in the target vocabulary unit, different mastery levels, and the corresponding number of words.

[0150] As an example, a mastery level chart can also include the number of words and phrases used at each mastery level, and the increase or decrease in the number of words or phrases used at each mastery level compared to the previous test or before the test. For reference... Figure 5B Alternatively, 5C and 140 can be designated as the mastery level scale area, used to display mastery level statistics charts or tables. Figure 5B The target vocabulary unit contains 57 test points, which are the usage of words or phrases. If the overall mastery level of the target vocabulary unit is zero, then the total number of test points to be tested is 57. Figure 5C The total number of test sites to be tested is 13, a decrease of 44 from 57; 15 test sites have been mastered, an increase of 15 from before the test; 16 test sites have been partially mastered, an increase of 16 from before the test; and 13 test sites have not been mastered, an increase of 13 from before the test.

[0151] In some embodiments, in response to a login operation for a client, the client's cache is queried; when data for any word unit stored during the last login is found, that word unit is used as the target word unit, and the entry corresponding to the target word unit is displayed; when no data for any word unit stored during the last login is found, a list of word units is displayed, which includes multiple word units and their corresponding word unit entries.

[0152] As an example, any vocabulary unit can be the last selected vocabulary unit, or the vocabulary unit with the lowest mastery level among multiple cached vocabulary unit data, or a vocabulary unit among multiple cached vocabulary unit data with records of incomplete testing.

[0153] In some embodiments, step 101 includes: generating a tree structure for the target vocabulary unit based on the vocabulary list corresponding to the semantic relationships of the target vocabulary unit. The vocabulary list includes the vocabulary and phrase usages of the target vocabulary unit, and the tree structure includes multiple first-level groups and multiple second-level groups; each first-level group includes: multiple words with the same root and existing prefix or suffix relationships, and phrase usages associated with each word in the first-level group; each first-level group is associated with at least one second-level group, and each second-level group includes: a word and a phrase usage associated with that word. The first-level groups are used as groups in the target vocabulary unit, and based on the vocabulary and phrase usages in each first-level group, and the level of mastery corresponding to the vocabulary and phrase usages in each first-level group, word cards corresponding one-to-one with at least one group in the target vocabulary unit are rendered on the human-computer interaction interface.

[0154] As an example, refer to Figure 7C , Figure 7C This is a schematic diagram of a tree structure provided in an embodiment of this application. Figure 7C The target vocabulary units can be divided into multiple groups based on lexical relationships, forming multiple first-level groups. Semantic relationships can be derivational relationships or parts-of-speech conversion relationships. Based on semantic relationships, words with the same root and exhibiting prefix or suffix relationships, along with their associated phrase usages, can be identified.

[0155] As an example, the data included in the target vocabulary unit are the vocabulary, vocabulary annotations, phrase usage, phrase usage annotations, etc. The data included in the target vocabulary unit is converted into tree structure data according to the tree structure, and the first-level group data of the tree structure data is rendered into word card diagrams corresponding to each group in the vocabulary unit.

[0156] In some embodiments, step 102 includes: determining secondary groups associated with each group in the vocabulary unit, and rendering at least one vocabulary relationship diagram corresponding one-to-one with at least one group in the target vocabulary unit on the human-computer interaction interface according to the mastery level of a vocabulary and a phrase associated with a vocabulary included in each associated secondary group and the vocabulary and phrase associated with a vocabulary included in each associated secondary group.

[0157] As an example, continue to refer to Figure 7C , Figure 7C It also includes multiple secondary groups, each of which includes vocabulary and phrase usages associated with the vocabulary. Each primary group corresponds to at least one secondary group.

[0158] As an example, the second-level grouped data of the tree structure is rendered into a word relationship graph corresponding to each group in the word unit.

[0159] In some embodiments, there are derivational or part-of-speech conversion relationships between the words in the corresponding groups of the word card diagram, and the words corresponding to the word nodes in the word relationship diagram are related to each other with the phrase usages corresponding to the phrase nodes.

[0160] As an example, refer to Figure 5C , Figure 5C This is a schematic diagram of the human-computer interaction interface provided in the embodiments of this application. Figure 5C The tags in the text are agreement, disagreement, and disagree, and there are derivational relationships between them, meaning that nouns can be converted into antonyms, antonyms, etc. (See reference) Figure 5D , Figure 5D This is a schematic diagram of the human-computer interaction interface provided in the embodiments of this application. Figure 5D The words corresponding to the labels on the Chinese word card are "add" and "addition," and there is a part-of-speech conversion relationship between the two, that is, the verb is converted into a noun.

[0161] The vocabulary processing method provided in this application helps users intuitively understand the relationships between words, the relationships between words and related phrases, and the mastery level of words and related phrases in language learning by displaying a vocabulary unit fusion card diagram and a vocabulary relationship diagram that shows the mastery level of vocabulary units. By obtaining mastery level data through vocabulary testing, the mastery level is made more consistent with the user's learning, which improves the intelligence of human-computer interaction in the learning process and enhances the user experience in the learning process.

[0162] The following will describe an exemplary application of the embodiments of this application in a real-world application scenario.

[0163] This application provides a vocabulary processing method that displays word card diagrams corresponding to groups in a textbook unit and at least one vocabulary relationship diagram corresponding to each group. The word card diagram includes the vocabulary in the group and its mastery level, as well as the usage of phrases associated with the vocabulary and their mastery level. The vocabulary relationship diagram includes a vocabulary node of at least one vocabulary in the corresponding group and a phrase usage node connected to the vocabulary node that corresponds to the phrase usage associated with the vocabulary. Both the vocabulary node and the phrase usage node are displayed according to their corresponding mastery level.

[0164] The following explanation combines flowcharts and diagrams for reference. Figure 8A , Figure 8A This is an optional flowchart of the vocabulary processing method provided in the embodiments of this application.

[0165] Figure 8A The process includes step 801A: Displaying the human-computer interaction interface. Step 802A: Determining if the current state is logged in. If the result of step 802A is yes, then proceed to step 804A: Requesting textbook list data. If the result of step 802A is no, then proceed to step 804A after proceeding to step 803A. Step 803A: Displaying the login window and receiving login operations. After step 804A, proceed to step 805A: Determining if the previously selected textbook and unit exist. If the result of step 805A is yes, then proceed to step 806A: Retrieving the previously selected textbook and unit, and using the selected unit as the target unit. If the result of step 805A is yes, then proceed to step 807A: Selecting the default textbook and unit, and using the selected unit as the target unit. After both steps 807A and 806A, proceed to step 808A: Retrieving the vocabulary list data of the target unit, and displaying the vocabulary card chart and vocabulary relationship diagram of the target unit.

[0166] For example, the human-computer interaction interface can be a graphical user interface (GUI). When displaying vocabulary learning content in the human-computer interaction interface of a terminal device, the system first checks whether the user is logged in. If the user is not logged in, the system prompts the user to log in, or automatically switches the display to a login window to prompt the user to log in. If the user has successfully logged in, the system checks the local cache or server cache for the previously selected textbook unit. If not, it selects the first textbook unit from the textbook unit list by default; if it does, it uses the previously selected textbook unit as the selected unit, and then requests the vocabulary list data and vocabulary relationship data for that unit based on the selected textbook unit.

[0167] Example, reference Figure 5B , Figure 5B This is a schematic diagram of the human-computer interaction interface provided in an embodiment of this application. The word card area 110 displays word cards, and the vocabulary relationship diagram area 120 displays the vocabulary relationship diagram. (Reference) Figure 6A , Figure 6A This is a schematic diagram of the vocabulary relationship diagram provided in the embodiments of this application. Figure 6A This demonstrates the process of updating and displaying each node in the vocabulary relationship graph based on the level of mastery. Figure 6A In the vocabulary relationship graph at the top center, each node represents the level of mastery through textures. Each node corresponds to a level of "not mastered." By obtaining the vocabulary mastery level, each node is updated and rendered accordingly. The updated and rendered vocabulary relationship graph is as follows: Figure 6A The vocabulary relationship diagram is shown in the lower middle section.

[0168] As an example, Figure 8B This is an optional flowchart of the vocabulary processing method provided in the embodiments of this application; after steps 807A and 806A, step 808B is also included, and step 808A is executed after step 808B. Step 808B: Receive the textbook unit selection operation, use the selected unit as the new target unit, and cache the selected textbook and unit.

[0169] For example, after the textbook unit is automatically selected in the human-computer interaction interface, users can also select the corresponding textbook unit according to their own needs.

[0170] In some embodiments, step 808B can also be executed immediately after the user logs in. For example, after completing the authentication and login operation, the user selects a textbook unit, receives a textbook unit selection operation, and directly uses the textbook unit corresponding to the textbook unit selection operation as the target unit.

[0171] As an example, Figure 8CThis is an optional flowchart illustrating the vocabulary processing method provided in this application embodiment; step 808A includes the following steps: Figure 8C As shown, Figure 8C The process includes step 801C: determining whether a word card diagram and a vocabulary relationship diagram for the target unit exist. If the result of step 801C is yes, then step 802C is executed: obtaining the vocabulary list data of the target unit and displaying the word card diagram and vocabulary relationship diagram of the target unit. If the result of step 801C is no, then step 803C is executed: obtaining the vocabulary list data of the target unit, and obtaining the tree structure relationship data of the target unit based on the vocabulary relationship and the vocabulary list data. After step 803, step 804C is executed: rendering the word card diagram based on the first-level grouping of the tree structure relationship data and displaying the word card diagram. After step 803C, step 805C is also executed: rendering the vocabulary relationship diagram based on the second-level grouping of the tree structure relationship data and displaying the vocabulary relationship diagram. Steps 805C and 804C are executed synchronously.

[0172] Example, reference Figure 7C To explain, Figure 7C This is a schematic diagram of the tree structure provided in the embodiments of this application. Figure 7C The target vocabulary unit can be divided into multiple groups based on vocabulary relationship data, forming multiple first-level groups. Vocabulary relationship data can include root relationships and five relationship fields: Relationship field 0 - no relationship, Relationship field 1 - prefix relationship, Relationship field 2 - suffix relationship, Relationship field 3 - parent-child relationship, and Relationship field 4 - child-parent relationship. If words share a root and relationship field is 1 or 2, they can be grouped into the same group. Simultaneously, phrase usages associated with the words are also grouped into the corresponding word group, forming first-level group data. Since roots determine word meaning, prefixes change word meaning, and suffixes determine word part of speech, the words in the groups exhibit derivative or part-of-speech conversion relationships.

[0173] For example, the first-level grouped data is used to render the flashcard image. Words belonging to derivatives or parts of speech conversion relationships are used as tab labels for the flashcards, and the vocabulary mastery level, explanation, and related phrase usage are used as tab pane content. The flashcard image can be rendered based on the tabs component of element-ui (a website rapid prototyping tool).

[0174] Continue to refer to Figure 7C , Figure 7CThe data also includes multiple second-level groups, each containing words and their corresponding phrase usages. Each first-level group corresponds to at least one second-level group. After determining all first-level group data, the phrase usages of the target word unit are traversed, and phrase usages with a relationship field of 3 or 4 with words in the first-level group are grouped into a second-level group. For example, each second-level group contains one phrase usage associated with one word.

[0175] Continue to refer to Figure 5B , Figure 5B A 120-square-meter area is reserved for rendering the vocabulary relationship graph. For example, based on the relationships between vocabulary and phrase usage, and using ECharts, multiple vocabulary relationship graphs are rendered. The height of the 120-square-meter vocabulary relationship graph area can be variable. During rendering, the vertical rendering center point needs to be set based on half of the height. The display attributes of each node are rendered according to the preset display attributes when generating the vocabulary tree structure data. The size of different nodes is set based on whether they are the root node of a vocabulary word. (Refer to...) Figure 6B , Figure 6B This is a schematic diagram of the vocabulary relationship diagram provided in the embodiments of this application. Figure 6B 603 is a mastery level indicator. When focusing on a node, a progress bar and a mastery level value are rendered using the set tooltips to more accurately display the specific mastery level of the vocabulary node. Display attributes can be at least one of color, size, or effects. Focusing operations can include hovering, clicking, and swiping.

[0176] Continue to refer to Figure 6B , Figure 6B In the lexical relationship graph, the lexical node is "agreement", and "agreement" corresponds to four phrase nodes. The relationship field between the four phrase nodes and "agreement" is 3 or 4.

[0177] As an example, the data corresponding to the usage of words and phrases grouped by the target vocabulary unit can be rendered into a one-to-one correspondence word card chart and a vocabulary relationship chart based on the relationship graph in ECharts (a data visualization chart library). This embodiment uses ECharts as an example for illustration; in practical applications, other data visualization software or components can also be used to perform the rendering operations in this embodiment.

[0178] For example, the embodiments of this application do not limit the actual shape of the vocabulary relationship diagram. The vocabulary relationship diagram can be a diagram where vocabulary nodes are in the center and phrase nodes are around them, with lines connecting the vocabulary nodes and phrase nodes; it can also be a diagram where vocabulary nodes are on one side and phrase nodes are on the other side, with lines connecting the vocabulary nodes and phrase nodes; or it can be a diagram where vocabulary nodes are in the center and phrase usage nodes are around them, with the vocabulary nodes and phrase nodes arranged close together in a flower shape, etc. If the display attribute of each node in the vocabulary relationship diagram is a color attribute, the node color can be a fixed preset color; or multiple optional schemes can be provided for users to choose from, and users can set different display schemes in the settings window of the human-computer interaction interface; the shape of each node in the vocabulary relationship diagram is set to a circle in this embodiment of the application, but it can also be other shapes. For example, if a vocabulary corresponds to four phrase usages, then the vocabulary node is a square, and each phrase node is a square or a circle, with lines connecting the vocabulary nodes and phrase nodes. By representing the degree of mastery through different display attributes, the display effect of the language learning application in the human-computer interaction interface is made more personalized and beautiful, enhancing the user's learning interest; for example, the display attributes can also reflect the degree of mastery of nodes, such as the degree of blur.

[0179] As an example, the tabs in the word card chart can be switched. Continuing with the example of rendering based on ECharts, a listener can be set to monitor the resize event of the display area in the word card chart to detect changes in the display area. However, since multiple word cards can be displayed in the human-computer interaction interface, there are multiple canvases grouped from word units. To facilitate unified processing, a mixins tool is used to implement a generic charts-resize-mixin. Inside the mixins tool, elements identified as "charts" (i.e., the word card chart in this embodiment) are first retrieved, and each is initialized individually using `echats.init`. When the `window.resize` event is detected, the resize event of each chart is triggered. Alternatively, a call-based triggering method can be used, adding a throttling and debouncing function inside the chart's resize event to prevent performance issues caused by frequent resize event triggering. The mixins tool is then introduced into the component corresponding to each word card chart. When performing a label switching operation, the charts' resize event is triggered simultaneously, causing the word card image to be re-rendered.

[0180] As an example, refer to Figure 8D , Figure 8DThis is an optional flowchart of the vocabulary processing method provided in this application embodiment; this application embodiment also includes step 801D: determining whether mastery level data exists. If the determination result of step 801D is "no", then step 803D is executed: setting the mastery level of each word and each phrase to "not mastered". If the determination result of step 801D is "yes", then step 802D is executed: determining the mastery level of each word and each phrase based on the mastery level data. After steps 802D and 803D, step 804D is executed: rendering a vocabulary relationship graph based on the secondary grouping of the tree structure relationship data and the mastery level, and displaying the vocabulary relationship graph.

[0181] For example, since there is no corresponding mastery level data for new users, the above steps are used to confirm whether the user's mastery level data exists locally or on the server. If not, the vocabulary relationship graph is displayed with the default display attributes. If mastery level data exists, each node in the vocabulary relationship graph is rendered according to the mastery level, so that the vocabulary relationship graph can intuitively display the mastery level of words and related phrases.

[0182] Continuing with reference to 6A, if no data on the level of mastery is available, then... Figure 6A The vocabulary relationship diagram at the top center displays the mastery level of each node, meaning that each node in the vocabulary relationship diagram is displayed according to a unified display attribute. If mastery level data exists, the display attributes of each node in the vocabulary relationship diagram are rendered according to the mastery level.

[0183] As an example, refer to Figure 8E , Figure 8E This is an optional flowchart of the vocabulary processing method provided in the embodiments of this application. Figure 8E The process includes step 801E: receiving a test request for the target unit, displaying the test questions for the target unit, receiving the answer submission operation, and recording the answer data; step 802E: obtaining the mastery level corresponding to each word node and each phrase node in the vocabulary relationship graph based on the answer data; and step 803E: updating and displaying each node in the vocabulary relationship graph based on the mastery level.

[0184] In some embodiments, reference Figure 7A , Figure 7A This is a schematic diagram of the human-computer interaction interface provided in an embodiment of this application. Upon receiving a test request, the screen in the human-computer interaction interface switches from the vocabulary learning screen to the test question screen. Figure 7AThis is a diagram of the areas displayed on the human-computer interaction interface when test questions are shown. 550 is the answer sheet area, used to display the answer sheet; 560 is the test area, used to display the test questions and the answer key; 530 is the reference answer area, used to display the reference answers to the test questions; 540 is the page-turning button. Responding to the triggering of the page-turning button will switch the currently displayed test question to the next test question on the human-computer interaction interface.

[0185] As an example, refer to Figure 7B , Figure 7B This is a schematic diagram of the human-computer interaction interface provided in the embodiments of this application. Figure 7B This serves as an example of displaying test questions in a human-computer interaction interface. The answer sheet includes the question number for each test question, the test result for each test question, and the time taken for the test or the remaining time for the test.

[0186] In some embodiments, in response to a trigger operation targeting the question number corresponding to a test question on the answer sheet, the currently displayed test question in the human-computer interaction interface is switched to the test question selected by the trigger operation. This allows the user to quickly switch the currently displayed test question. The test questions can be writing questions, multiple-choice questions, or matching questions, etc. The test points of the test questions correspond to the usage of vocabulary or phrases in the vocabulary unit.

[0187] The following description continues to illustrate the exemplary structure of the device 455 provided in the embodiments of this application as a software module. In some embodiments, such as Figure 2 As shown, the software modules stored in the vocabulary processing device 455 in the memory 440 may include: a display module 4551 configured to display, in response to a trigger operation for an entry into a target vocabulary unit, a word card diagram corresponding one-to-one with at least one group in the target vocabulary unit on a human-computer interaction interface, wherein each word card diagram includes the corresponding group, the phrase usage of the corresponding group, and the mastery level; and the display module 4551 is further configured to display, on the human-computer interaction interface, at least one vocabulary relationship diagram corresponding one-to-one with at least one group, wherein each vocabulary relationship diagram includes a vocabulary node associated with any vocabulary in the corresponding group, and at least one phrase usage node connected to the vocabulary node, and the display attributes of the vocabulary node and the phrase usage node are related to the corresponding mastery level.

[0188] In some embodiments, the display module 4551 is further configured to display word cards corresponding one-to-one with at least one group in the target vocabulary unit on the human-computer interaction interface, wherein each word card includes the following: multiple labels, each label including a word in the corresponding group; at least one phrase usage corresponding to the word included by the focus label, the focus label being the label in a focused state among the multiple labels; the mastery level corresponding to the word included by the focus label, and the mastery level corresponding to at least one phrase usage of the word included by the focus label.

[0189] In some embodiments, before displaying at least one phrase usage corresponding to the words included in the focus tag, the display module 4551 is further configured to display a plurality of tags that are not in a focus state; in response to a selection operation, the selected tag among the plurality of tags is used as the focus tag, the focus tag is displayed based on the display attributes of the focus state, and other tags among the plurality of tags that are not in a focus state are displayed based on the display attributes of the non-focus state.

[0190] In some embodiments, before displaying at least one phrase usage corresponding to the vocabulary included in the focused tag, the display module 4551 is further configured to display multiple tags according to a specific sorting method, using the first tag in the sorting method as the focused tag, displaying the focused tag based on the display attributes of the focused state, and displaying other tags among the multiple tags that are not in a focused state based on the display attributes of the unfocused state. The sorting method includes: ascending or descending order of the learning time of the vocabulary included in the tag, and ascending or descending order of the mastery level of the vocabulary corresponding to the tag.

[0191] In some embodiments, the display module 4551 is further configured to, in response to a switching operation, replace the old focus label displayed before the switching operation with the label triggered by the switching operation as the new focus label, display at least one phrase usage corresponding to the vocabulary included in the new focus label, and stop displaying at least one phrase usage corresponding to the vocabulary included in the old focus label. It also displays the level of mastery corresponding to the vocabulary included in the new focus label and the level of mastery corresponding to at least one phrase usage corresponding to the vocabulary included in the new focus label, and stops displaying the level of mastery corresponding to the vocabulary included in the old focus label and the level of mastery corresponding to at least one phrase usage corresponding to the vocabulary included in the old focus label.

[0192] In some embodiments, the display module 4551 is further configured to determine the target height of the word card based on the number of at least one phrase usages corresponding to the words included in the new focus label, the rendering height, and the basic height of the word card, and update the height of the word card image where the label triggered by the display switching operation is located based on the target height of the word card.

[0193] In some embodiments, the display module 4551 is further configured to display a list of word cards for the target vocabulary unit on the human-computer interaction interface, wherein the list of word cards includes multiple word cards that correspond one-to-one with multiple groups in the target vocabulary unit. The sorting of the multiple word cards includes: ascending or descending order of learning time for the groups corresponding to the word cards, and ascending or descending order of mastery level for the groups corresponding to the word cards.

[0194] In some embodiments, before displaying at least one vocabulary relationship diagram corresponding to at least one group in the human-computer interaction interface, the display module 4551 is further configured to display a vocabulary relationship diagram entry corresponding to each word card diagram in the human-computer interaction interface; in response to a trigger operation for at least one vocabulary relationship diagram entry, the process of displaying at least one vocabulary relationship diagram corresponding to at least one group in the human-computer interaction interface is initiated.

[0195] In some embodiments, the display module 4551 is further configured to display at least one vocabulary relationship graph corresponding one-to-one with at least one group on the human-computer interaction interface, wherein each vocabulary relationship graph includes a vocabulary node associated with any vocabulary in the corresponding group, and at least one phrase usage node connected to the vocabulary node, and the display attributes of the vocabulary node and the phrase usage node are default display attributes; in response to a focus operation, the display target node is updated in the vocabulary relationship graph according to the target display attribute of the focused target node, wherein the target display attribute is related to the mastery of the vocabulary or phrase usage corresponding to the target node.

[0196] In some embodiments, the display module 4551 is further configured to display at least one vocabulary relationship graph corresponding one-to-one with at least one group on the human-computer interaction interface, wherein each vocabulary relationship graph includes a vocabulary node associated with any vocabulary in the corresponding group, and at least one phrase usage node connected to the vocabulary node, and the display attributes of the vocabulary node and the phrase usage node are default display attributes; in response to the mastery level viewing operation, each node in the vocabulary relationship graph is updated and displayed according to the target display attribute of each node in the vocabulary relationship graph, wherein the target display attribute of each node is related to the mastery level of the corresponding vocabulary or phrase usage of each node.

[0197] In some embodiments, the display module 4551 is further configured to display a detection entry for the target vocabulary unit; in response to a trigger operation for the detection entry, display multiple test questions associated with the target vocabulary unit on the human-computer interaction interface; and in response to an answer submission operation for the multiple test questions, determine the mastery level of each word and each phrase in the target vocabulary unit based on the submitted answers.

[0198] In some embodiments, the display module 4551 is further configured to determine the mastery level of each phrase usage based on the accuracy rate of the answers submitted for the test questions associated with each phrase usage; determine the sum of the mastery levels of each phrase usage corresponding to each word, and use the ratio of the sum to the number of phrase usages corresponding to each word as the mastery level of each word.

[0199] In some embodiments, the display module 4551 is further configured to display a mastery statistics chart corresponding to the target vocabulary unit on the human-computer interaction interface; wherein the mastery statistics chart includes: the total number of words in the target vocabulary unit, different mastery levels, and the corresponding number of words.

[0200] In some embodiments, the display module 4551 is further configured to query the client's cache in response to a login operation for the client; when data of any word unit stored during the last login is found, the word unit is used as the target word unit and the entry corresponding to the target word unit is displayed; when data of any word unit stored during the last login is not found, a word unit list is displayed, which includes multiple word units and their corresponding word unit entries.

[0201] In some embodiments, the display module 4551 is further configured to generate a tree structure of the target vocabulary unit based on the vocabulary list corresponding to the target vocabulary unit according to the semantic relationship, wherein the vocabulary list includes the vocabulary and phrase usage of the target vocabulary unit, and the tree structure includes multiple first-level groups and multiple second-level groups; wherein each first-level group includes: multiple words with the same root and having a prefix or suffix relationship, and the phrase usage associated with each word in the first-level group; each first-level group is associated with at least one second-level group; each second-level group includes: a word and a phrase usage associated with the word; the first-level group is used as a group in the target vocabulary unit, and according to the vocabulary and phrase usage in each first-level group, and the mastery level corresponding to the vocabulary and phrase usage in each first-level group, a word card image corresponding one-to-one with at least one group in the target vocabulary unit is rendered on the human-computer interaction interface.

[0202] In some embodiments, the display module 4551 is further configured to determine the secondary groups associated with each group in the vocabulary unit, and to render at least one vocabulary relationship diagram corresponding to at least one group in the target vocabulary unit on the human-computer interaction interface according to the mastery level of a vocabulary and a phrase associated with each associated secondary group and the vocabulary and phrase associated with each associated secondary group.

[0203] This application provides a computer program product or computer program that includes computer instructions stored in a computer-readable storage medium. A processor of a computer device reads the computer instructions from the computer-readable storage medium and executes the computer instructions, causing the computer device to perform the vocabulary processing method described above in this application.

[0204] This application provides a computer-readable storage medium storing executable instructions. When these executable instructions are executed by a processor, they cause the processor to perform the vocabulary processing method provided in this application. For example, ... Figure 3A The vocabulary processing method shown.

[0205] In some embodiments, the computer-readable storage medium may be a memory such as FRAM, ROM, PROM, EPROM, EEPROM, flash memory, magnetic surface memory, optical disk, or CD-ROM; or it may be a variety of devices including one or any combination of the above-mentioned memories.

[0206] In some embodiments, executable instructions may take the form of a program, software, software module, script, or code, written in any form of programming language (including compiled or interpreted languages, or declarative or procedural languages), and may be deployed in any form, including as a standalone program or as a module, component, subroutine, or other unit suitable for use in a computing environment.

[0207] As an example, executable instructions may, but do not necessarily, correspond to files in a file system. They may be stored as part of a file that holds other programs or data, for example, in one or more scripts in a HyperText Markup Language (HTML) document, in a single file dedicated to the program in question, or in multiple collaborating files (e.g., files that store one or more modules, subroutines, or code sections).

[0208] As an example, executable instructions can be deployed to execute on a single computing device, or on multiple computing devices located in one location, or on multiple computing devices distributed across multiple locations and interconnected via a communication network.

[0209] In summary, the embodiments of this application display word card diagrams corresponding to groups in a textbook unit and at least one vocabulary relationship diagram corresponding to each group. The word card diagrams include the vocabulary in the group and their mastery levels, as well as the usage of phrases associated with the vocabulary and their mastery levels. The vocabulary relationship diagrams include vocabulary nodes of at least one vocabulary in the corresponding group and phrase usage nodes connected to the vocabulary nodes that correspond to the phrase usages associated with the vocabulary. Both the vocabulary nodes and the phrase usage nodes are displayed according to their corresponding mastery levels.

[0210] The above description is merely an embodiment of this application and is not intended to limit the scope of protection of this application. Any modifications, equivalent substitutions, and improvements made within the spirit and scope of this application are included within the scope of protection of this application.

Claims

1. A vocabulary processing method, characterized in that, The method includes: In response to a trigger operation targeting an entry point of a vocabulary unit, a word card image corresponding one-to-one with at least one group in the target vocabulary unit is displayed on the human-computer interaction interface. Each word card image includes: multiple labels, each label including a word from its corresponding group; at least one phrase usage corresponding to the word included by a focus label, the focus label being the label that is in a focused state among the multiple labels; the level of mastery corresponding to the word included by the focus label; and the level of mastery corresponding to at least one phrase usage of the word included by the focus label. In response to a switching operation for the plurality of tags, the tag triggered by the switching operation is used as a new focus tag to replace the old focus tag displayed before the switching operation, at least one phrase usage corresponding to the words included in the new focus tag is displayed, and the display of at least one phrase usage corresponding to the words included in the old focus tag is stopped. Displays the level of mastery corresponding to the vocabulary included in the new focus tag, and the level of mastery corresponding to at least one phrase usage corresponding to the vocabulary included in the new focus tag, and stops displaying the level of mastery corresponding to the vocabulary included in the old focus tag, and the level of mastery corresponding to at least one phrase usage corresponding to the vocabulary included in the old focus tag. The human-computer interaction interface displays at least one vocabulary relationship graph corresponding to the at least one group. Each vocabulary relationship graph includes a vocabulary node associated with any vocabulary in the corresponding group and at least one phrase usage node connected to the vocabulary node. The display attributes of the vocabulary node and the phrase usage node are related to the corresponding mastery level.

2. The method according to claim 1, characterized in that, Before displaying at least one phrase usage corresponding to the vocabulary included in the focus tag, the method further includes: Display the plurality of labels that are not in the focused state; In response to a selection operation, the selected label among the plurality of labels is designated as the focused label, the focused label is displayed based on the display attributes of the focused state, and the other labels among the plurality of labels that are not in the focused state are displayed based on the display attributes of the unfocused state.

3. The method according to claim 2, characterized in that, Before displaying at least one phrase usage corresponding to the vocabulary included in the focus tag, the method further includes: The multiple labels are displayed according to a specific sorting method, with the first label in the sorting method as the focused label. The focused label is displayed based on the display attributes of the focused state, and other labels among the multiple labels that are not in the focused state are displayed based on the display attributes of the unfocused state. The sorting method includes: ascending or descending order of the learning time of the vocabulary included in the tags, and ascending or descending order of the mastery level of the vocabulary corresponding to the tags.

4. The method according to claim 1, characterized in that, The method further includes: Based on the number of at least one phrase usages corresponding to the words included in the new focus label, the rendering height, and the basic height of the word card, the target height of the word card is determined, and the height of the word card image where the label triggered by the switching operation is displayed is updated based on the target height of the word card.

5. The method according to claim 1, characterized in that, When the number of the at least one group is multiple, the step of displaying word cards corresponding one-to-one with at least one group in the target vocabulary unit on the human-computer interaction interface includes: The human-computer interaction interface displays a list of word cards for the target vocabulary unit, wherein the list of word cards includes multiple word cards that correspond one-to-one with multiple groups in the target vocabulary unit; The sorting method of the multiple word cards includes: ascending or descending order of the learning time of the groups corresponding to the word cards, and ascending or descending order of the mastery level of the groups corresponding to the word cards.

6. The method according to claim 1, characterized in that, The method further includes: The human-computer interaction interface displays a statistical chart of mastery levels corresponding to the target vocabulary unit; The mastery level statistics chart includes at least one of the following: the total number of words in the target vocabulary unit, different mastery levels, and the corresponding number of words.

7. The method according to claim 1, characterized in that, The method further includes: In response to a login operation on the client, query the client's cache; When data for any word unit stored during the last login is retrieved, that word unit is used as the target word unit, and the entry corresponding to the target word unit is displayed. If no data for any vocabulary unit stored during the last login is found, a list of vocabulary units is displayed, which includes multiple vocabulary units and their corresponding entry points.

8. The method according to claim 1, characterized in that, The step of displaying word cards on the human-computer interaction interface that correspond one-to-one with at least one group in the target vocabulary unit includes: Based on the semantic relationships and the vocabulary list corresponding to the target vocabulary unit, a tree structure of the target vocabulary unit is generated, wherein the vocabulary list includes the vocabulary and phrase usage of the target vocabulary unit, and the tree structure includes multiple first-level groups and multiple second-level groups; Each of the first-level groups includes: multiple words with the same root and a preceding or following relationship, and phrase usages associated with each word in the first-level group. Each of the first-level groups is associated with at least one second-level group, and each second-level group includes a word and a phrase usage associated with the word. The first-level groups are used as groups in the target vocabulary unit. Based on the usage of words and phrases in each first-level group and the mastery level of the usage of words and phrases in each first-level group, word cards corresponding to at least one group in the target vocabulary unit are rendered on the human-computer interaction interface.

9. The method according to claim 8, characterized in that, The step of displaying at least one word relationship diagram corresponding one-to-one with the at least one group on the human-computer interaction interface includes: Determine the secondary groups associated with each group in the vocabulary unit, and render at least one vocabulary relationship graph corresponding to at least one group in the target vocabulary unit on the human-computer interaction interface, based on the vocabulary and phrase associated with each of the associated secondary groups, and the mastery level of each vocabulary and phrase associated with each of the associated secondary groups.

10. A vocabulary processing device, characterized in that, The device includes: The display module is configured to respond to a trigger operation on an entry point of a target vocabulary unit by displaying word cards on a human-computer interaction interface that correspond one-to-one with at least one group in the target vocabulary unit, wherein each word card includes: Multiple tags, each tag including a word in a corresponding group; at least one phrase usage corresponding to the word included in the focus tag, the focus tag being the tag in a focused state among the multiple tags; the level of mastery corresponding to the word included in the focus tag, and the level of mastery corresponding to at least one phrase usage of the word included in the focus tag; The display module is further configured to respond to a switching operation for the plurality of tags, replace the old focus tag displayed before the switching operation with the tag triggered by the switching operation as a new focus tag, display at least one phrase usage corresponding to the words included in the new focus tag, and stop displaying at least one phrase usage corresponding to the words included in the old focus tag. Displays the level of mastery corresponding to the vocabulary included in the new focus tag, and the level of mastery corresponding to at least one phrase usage corresponding to the vocabulary included in the new focus tag, and stops displaying the level of mastery corresponding to the vocabulary included in the old focus tag, and the level of mastery corresponding to at least one phrase usage corresponding to the vocabulary included in the old focus tag. The display module is further configured to display at least one vocabulary relationship graph corresponding one-to-one with the at least one group on the human-computer interaction interface, wherein each vocabulary relationship graph includes a vocabulary node associated with any vocabulary in the corresponding group, and at least one phrase usage node connected to the vocabulary node, and the display attributes of the vocabulary node and the phrase usage node are related to the corresponding mastery level.

11. The apparatus according to claim 10, characterized in that, The display module is also used to display the plurality of labels that are not in the focused state; In response to a selection operation, the selected label among the plurality of labels is designated as the focused label, the focused label is displayed based on the display attributes of the focused state, and the other labels among the plurality of labels that are not in the focused state are displayed based on the display attributes of the unfocused state.

12. The apparatus according to claim 11, characterized in that, The display module is further configured to display the plurality of labels according to a specific sorting method, take the first label in the sorting method as the focused label, display the focused label based on the display attributes of the focused state, and display other labels among the plurality of labels that are not in the focused state based on the display attributes of the unfocused state; The sorting method includes: ascending or descending order of the learning time of the vocabulary included in the tags, and ascending or descending order of the mastery level of the vocabulary corresponding to the tags.

13. A terminal device for vocabulary processing, characterized in that, The terminal device includes: Memory, used to store executable instructions; A processor, when executing executable instructions stored in the memory, implements the vocabulary processing method of any one of claims 1 to 9.

14. A computationally readable storage medium storing executable instructions, characterized in that, Used to implement the vocabulary processing method of any one of claims 1 to 9 when executed by a processor.

15. A computer program product, comprising a computer program or instructions, characterized in that, When the computer program or instructions are executed by a processor, they implement the vocabulary processing method of any one of claims 1 to 9.

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