Two-dimensional plane dynamic word cloud display method based on spherical mapping

Abstract

The invention relates to the technical field of data processing, in particular to a spherical mapping-based two-dimensional plane dynamic word cloud display method, which comprises the following steps of: creating an entry object pool to generate a data object comprising a text, a weight, an initial position and a moving speed; reading original position coordinates, executing linear conversion, and outputting standard coordinates; calculating the Euclidean distance from the entry to the central point; calculating an entry scaling value and a transparency value based on the parameters, so that the entry in the central area is enlarged and not transparent, and the edge is shrunk and transparent; freezing the moving state and activating a countdown timer when the zoom value and the transparency value meet a dual-threshold condition; updating the horizontal position according to the moving speed in an unfrozen state; and if the position exceeds the boundary, resetting to the initial area to allocate a new text. A visual depth of field is established through spatial parameter mapping, key information is locked by a focus freezing mechanism, a circular driving model maintains dynamic updating, and the problems of spatial level missing and focus dispersion of traditional dynamic word cloud are solved.

Description

Technical Field

[0001] The present invention relates to the field of data processing technology, and in particular to a two-dimensional plane dynamic word cloud display method based on spherical mapping. Background Art

[0002] Two-dimensional dynamic word cloud display is a text data visualization technology that assigns different font sizes and positions based on the frequency or weight of words in the corpus, and layouts vocabulary elements on a Cartesian coordinate system (XY plane). It avoids element overlap and highlights the distribution of importance through spatial optimization algorithms (such as force-directed layout). The dynamic characteristics drive the evolution of the word cloud with the help of animation engines or real-time data streams. For example, the word cloud changes size or position according to the newly added text, thereby revealing thematic trends and keyword correlations that change over time, and improving the user's interactive experience of data dynamics and pattern recognition.

[0003] Existing dynamic word clouds lack spatial hierarchy and attention-guiding mechanisms. Existing methods overly rely on simple linear animation layouts, which fail to simulate real-world spatial relationships, resulting in evenly distributed entries with no dynamic hierarchy. Because entry movement follows a uniform path, they lack a position-based distance perception mechanism and fail to create a visual focal point to highlight important keywords, thereby weakening users' ability to capture key information. For example, in data visualization applications, existing dynamic word clouds use entries of fixed size and transparency to move horizontally. When users are faced with evenly flowing text, important keywords are submerged in ordinary word clusters, making them difficult to quickly identify, ultimately reducing the efficiency of information communication. Summary of the Invention

[0004] In view of the shortcomings of the existing technology, the present invention provides a two-dimensional plane dynamic word cloud display method based on spherical mapping to solve the problem that dynamic word clouds in computer graphics display lack spatial hierarchy and attention guidance mechanism.

[0005] In order to solve the above technical problems, the specific technical solutions of the present invention are as follows: The present invention provides a two-dimensional dynamic word cloud display method based on spherical mapping, comprising: Step 1: Create a term object pool, traverse and obtain term data, and generate a data object for each term including text, weight, initial position coordinates and movement speed attributes; Step 2: Read the original position coordinates of the entry, perform linear transformation and output the coordinate values ​​of the standard coordinate system; Step 3: Use the standard coordinate system coordinate values ​​to calculate the Euclidean distance between the entry and the center point; Step 4: Map the Euclidean distance value to the spatial effect parameter through the cosine decay function, where a distance value of 0 corresponds to parameter 1, and a distance value of 1 corresponds to parameter 0; Step 5: Calculate the scaling value and transparency value of the entries based on the spatial effect parameters, so that the entries in the center area are enlarged and opaque, and the entries in the edge area are reduced and transparent; Step 6: When the scaling value of the entry is greater than or equal to the threshold value T1 and the transparency value of the entry is greater than or equal to the threshold value T2, the entry is determined to meet the focus condition; Step 7: In response to the focus condition, freeze the entry movement state and activate the countdown timer, and record the freeze state flag; Step 8: When the freeze state indicator indicates an unfrozen state, the horizontal position of the entry is updated according to the moving speed value generated in step 1; Step 9: When the horizontal position of the entry updated in step 8 exceeds the display boundary, reset the position of the entry that exceeds the display boundary to the initial area and allocate new text content; Step 10: At the end of each loop of steps 2 to 9, a graphical interface is called to render all entries in the entry object pool, and a dynamic word cloud is formed based on the scaling value, transparency value, and position of each entry in the entry object pool; Step 11: Loop through steps 2 to 10 to drive the entry object pool to update until the rendering termination instruction is triggered.

[0006] Furthermore, in the two-dimensional dynamic word cloud display method based on spherical mapping of the present invention, obtaining entry data in step 1 includes: S21: Read the original text data through the local database or remote API interface; S22: Input the original text data into the parser to extract the entry text and weight value; S23: performing a linear normalization operation on the extracted weight value and outputting it to a preset weight range; S24: marking a priority flag for the entry whose normalized weight value is ≥ the priority threshold; S25: Generate position coordinates based on the text, the marked priority identifier, and a preset initial position coordinate algorithm, and generate a data object in combination with a preset moving speed value.

[0007] Furthermore, the two-dimensional dynamic word cloud display method based on spherical mapping of the present invention includes, in step 2: S31: Establishing a coordinate system with the upper left corner of the display area as the origin; S32: Perform horizontal coordinate transformation on each entry: standard horizontal coordinate = 2×(original horizontal coordinate / display width)-1; S33: Perform vertical coordinate transformation on each entry: standard vertical coordinate = 1-2×(original vertical coordinate / display height); S34: When the display area size changes, re-execute S31 to establish the coordinate system and update the display width and display height parameter values ​​in S32-S33.

[0008] Furthermore, the two-dimensional dynamic word cloud display method based on spherical mapping of the present invention includes, in step 4: S41: Receive the Euclidean distance value calculated in step 3; S42: When the Euclidean distance value is 0, the calculated spatial effect parameter is 1; S43: When the Euclidean distance value is 1, the calculated spatial effect parameter is 0; S44: The Euclidean distance value is negatively correlated with the spatial effect parameter, and a continuous attenuation mapping from the [0, 1] interval is achieved through the cosine attenuation function, and the spatial effect parameter is output to step 5.

[0009] Furthermore, in the two-dimensional dynamic word cloud display method based on spherical mapping of the present invention, calculating the scaling value and transparency value of the entry in step 5 includes: S51: Perform the following operations based on the spatial effect parameters output in step 4: Scaling value calculation: Scaling ratio value = preset minimum scaling value + (preset maximum scaling value - preset minimum scaling value) × (spatial effect parameter)^γ; S52: Transparency value calculation: Transparency value = preset minimum transparency + (preset maximum transparency - preset minimum transparency) × spatial effect parameter; S53: Control the visual difference intensity between the center and edge areas by adjusting the γ value, where the γ value is a preset adjustable index factor.

[0010] Furthermore, in the two-dimensional dynamic word cloud display method based on spherical mapping of the present invention, determining in step 6 whether a term satisfies the focus condition includes: S61: Set the zoom ratio threshold = preset maximum zoom value × 0.9; S62: Set the transparency threshold = preset maximum transparency × 0.9; S63: When the zoom ratio value of the entry is greater than or equal to the zoom ratio threshold and the transparency value of the entry is greater than or equal to the transparency threshold, it is determined that the entry meets the focus condition.

[0011] Furthermore, in the two-dimensional dynamic word cloud display method based on spherical mapping of the present invention, freezing the entry movement state and activating the countdown timer in step 7 includes: S71: In response to the focus condition of step 63, freeze the entry position coordinate update function; S72: Activate the countdown timer to start counting; S73: After the countdown ends, the entry movement function is executed and the frozen state flag is cleared; S74: Mark the entry focus has been triggered.

[0012] Furthermore, in the two-dimensional dynamic word cloud display method based on spherical mapping of the present invention, updating the horizontal position of the entry in step 8 includes: S81: When the freeze state flag indicates an unfrozen state, obtain the moving speed value generated in step 1; S82: Based on the loop execution period of step 11, calculate the updated horizontal position coordinate: new horizontal coordinate = current horizontal coordinate + moving speed value; S83: Keep the vertical coordinate value unchanged and output the updated entry position.

[0013] Furthermore, the two-dimensional dynamic word cloud display method based on spherical mapping of the present invention includes in step 9: S91: When the horizontal position of the updated entry output in step 8 exceeds the display boundary, reset the horizontal position coordinates of the entry to the new coordinates generated by the initial position coordinate algorithm in step 1; S92: allocating new text content from the available entry list to overwrite the original entry according to the entry object pool management strategy; S93: Update the used entry record table and mark the original entry text as being in an allocable state.

[0014] Furthermore, in the two-dimensional dynamic word cloud display method based on spherical mapping of the present invention, the entry object pool management strategy in step 9 includes: S101: Reclaim entry object resources using the least recently used strategy; S102: Remove entry objects that exceed the display boundary and recycle text resources; S103: Select the new entry text content from the head of the available entry list; S104: Verify that the new entry text is not registered in the used entry record table, and update the record table to mark it as in use.

[0015] Beneficial effects of the present invention: The present invention converts the entry coordinates into nonlinear spatial effect parameters through a spherical mapping model, drives the visual amplification of the entries in the central area and the hierarchical effect of gradual transparency change in the edge area, and effectively constructs a two-dimensional dynamic layout with depth perception; the focus capture mechanism utilizes a dual-attribute threshold judgment and a mobile freezing system to forcibly lock the residence time of key information and prevent repeated triggering, breaking through the limitations of the traditional mobile word cloud average layout; the loop-driven displacement update and content reset strategy collaborates with the object pool management system, while maintaining dynamic content updates, strengthening the spatial hierarchy and visual focus guidance capabilities, and significantly improving the efficiency of users of the visual interface in identifying core data elements. BRIEF DESCRIPTION OF THE DRAWINGS

[0016] In order to more clearly illustrate the technical solution of the present invention, the following is a brief introduction to the drawings required for use in the embodiments. Obviously, for ordinary technicians in this field, other drawings can be obtained based on the drawings without paying any creative labor.

[0017] Figure 1 A flowchart of a two-dimensional dynamic word cloud display method based on spherical mapping provided in an embodiment of the present invention. DETAILED DESCRIPTION

[0018] In order to make the purpose, technical solutions and advantages of the present invention clearer, the technical solutions of the present invention will be clearly and completely described below in conjunction with the specific embodiments of the present invention and the corresponding drawings. Obviously, the embodiments described are only part of the embodiments of the present invention, not all of the embodiments. Based on the embodiments of the present invention, all other embodiments obtained by ordinary technicians in this field without making creative work are within the scope of protection of the present invention. The technical solutions provided by each embodiment of the present invention are described in detail below in conjunction with the drawings. In order to better understand the purpose of the present invention, the present invention is further described in detail below.

[0019] See also Figure 1 The present invention provides a two-dimensional dynamic word cloud display method based on spherical mapping, comprising: Step 1: Create a term object pool, traverse and obtain term data, and generate a data object for each term including text, weight, initial position coordinates and movement speed attributes; Step 2: Read the original position coordinates of the entry, perform linear transformation and output the coordinate values ​​of the standard coordinate system; Step 3: Use the standard coordinate system coordinate values ​​to calculate the Euclidean distance between the entry and the center point; Step 4: Map the Euclidean distance value to the spatial effect parameter through the cosine decay function, where a distance value of 0 corresponds to parameter 1, and a distance value of 1 corresponds to parameter 0; Step 5: Calculate the scaling value and transparency value of the entries based on the spatial effect parameters, so that the entries in the center area are enlarged and opaque, and the entries in the edge area are reduced and transparent; Step 6: When the scaling value of the entry is greater than or equal to the threshold value T1 and the transparency value of the entry is greater than or equal to the threshold value T2, the entry is determined to meet the focus condition; Step 7: In response to the focus condition, freeze the entry movement state and activate the countdown timer, and record the freeze state flag; Step 8: When the freeze state indicator indicates an unfrozen state, the horizontal position of the entry is updated according to the moving speed value generated in step 1; Step 9: When the horizontal position of the entry updated in step 8 exceeds the display boundary, reset the position of the entry that exceeds the display boundary to the initial area and allocate new text content; Step 10: At the end of each loop of steps 2 to 9, a graphical interface is called to render all entries in the entry object pool, and a dynamic word cloud is formed based on the scaling value, transparency value, and position of each entry in the entry object pool; Step 11: Loop through steps 2 to 10 to drive the entry object pool to update until the rendering termination instruction is triggered.

[0020] The entry object pool retrieves raw text data through a local database interface or a remote application programming interface, extracting the text content and corresponding weight values ​​using a parser. The weight values ​​are linearly normalized and mapped to a predefined weight range. Entries exceeding a priority threshold are annotated with a priority identifier. Initial position coordinates are calculated based on the text content, priority identifiers, and a preset random position generation algorithm. Combined with a preset movement speed parameter, a structured data object containing the aforementioned attributes is constructed and stored in the object pool.

[0021] Read the original position information of the entry and construct a rectangular coordinate system with the upper left corner of the display area as the coordinate origin. Perform standard coordinate transformation operations: use a linear transformation formula to map the original horizontal coordinate to the range [-1, 1] in the horizontal direction, and use a mirror transformation formula to process the original vertical coordinate in the vertical direction. When the display area size changes, the dynamic adaptation mechanism is triggered, re-establishing the coordinate system and updating the transformation parameters, outputting the normalized standard coordinate values.

[0022] Based on the converted standard coordinate values, a plane geometry algorithm is used to calculate the Euclidean distance between the center point of the entry and the origin of the coordinate system. This distance value serves as a quantitative indicator of spatial position relationship and provides input data for subsequent spatial effect conversion.

[0023] The Euclidean distance value is nonlinearly mapped to the spatial effect parameter using the cosine decay function. This mapping mechanism achieves a negative correlation between the distance value and the spatial parameter. The minimum distance value corresponds to the maximum parameter value, and the maximum distance value corresponds to the minimum parameter value. The intermediate values ​​follow the cosine function curve to complete the continuous decay, and the output parameter sequence conforms to the spherical distribution characteristics.

[0024] The visual properties of the entries are calculated based on the spatial effect parameters. The scaling property is calculated using an exponential adjustment formula, with an adjustable exponential factor controlling the visual gradient difference between the center and edge areas. The transparency property is calculated using a linear interpolation formula, ensuring that the central entry remains highly visible while the edge entries fade into the background. Both sets of calculation formulas share the spatial effect parameter inputs, generating visual control signals synchronously.

[0025] The focus condition detection module uses a dual-threshold determination mechanism. The zoom threshold is a fixed ratio of the maximum zoom value, and the transparency threshold is a fixed ratio of the maximum transparency value. When an entry meets both thresholds, the focus indicator is activated. This determination process provides the triggering basis for the attention guidance mechanism.

[0026] Responding to the focus indicator activates the freeze control command. This immediately locks the entry position update function, starts a countdown, and records the freeze status indicator. Once the countdown ends, the movement restriction is automatically released, the freeze indicator is cleared, and the focus is marked as triggered to prevent repeated responses, completing the closed-loop control of attention guidance.

[0027] When the freeze state flag indicates an unfrozen state, the entry's movement speed attribute is called to perform a displacement operation. The horizontal coordinate position of the entry is updated at a fixed speed value during the main loop cycle, while the vertical coordinate remains constant. This updated position information is output to the boundary detection module to achieve a flowing movement effect for the entry.

[0028] Monitor the updated horizontal coordinate position in real time. When the coordinate value exceeds the display area boundary, a reset operation is triggered. The initial position generation algorithm is used to recalculate the position coordinate. At the same time, new text content is allocated to overwrite the original entry according to the entry pool management strategy, and the usage status record table is updated to maintain data consistency.

[0029] At the end of the main loop, the graphics API is called to perform batch rendering operations. All data objects in the entry object pool are traversed, and the scaling value, transparency value, and position coordinates of each entry are calculated in real time to generate a dynamic word cloud visualization output with spatial depth of field effect.

[0030] The coordinate conversion process to rendered output is continuously executed in a loop until a rendering termination command is issued. This loop mechanism drives the dynamic update of the entry object pool, enabling the continuous evolution and update of data visualization content. The entire technical solution constructs a visual hierarchy through spatial mapping and combines it with a focus freezing mechanism to enhance attention guidance, forming a complete data visualization solution.

[0031] Specifically, the two-dimensional dynamic word cloud display method based on spherical mapping of the present invention, in step 1, obtaining entry data includes: S21: Read the original text data through the local database or remote API interface; S22: Input the original text data into the parser to extract the entry text and weight value; S23: performing a linear normalization operation on the extracted weight value and outputting it to a preset weight range; S24: marking a priority flag for the entry whose normalized weight value is ≥ the priority threshold; S25: Generate position coordinates based on the text, the marked priority identifier, and a preset initial position coordinate algorithm, and generate a data object in combination with a preset moving speed value.

[0032] In local database queries, the Structured Query Language (SQL) interface is used to read stored text datasets. When accessing data using the remote application programming interface (API), a Hypertext Transfer Protocol (HTTP) request is initiated to retrieve the standardized data packet returned by the server. The transmitted data is encapsulated in a lightweight data exchange format. A parser deconstructs the data packet content, identifies text fields and weight value fields, and extracts the term strings and corresponding raw weight data.

[0033] Linear normalization is performed on the extracted raw weight data. The difference between the upper and lower limits of the preset weight interval is used as the denominator, and the original weight minus the minimum weight is used as the numerator. The dispersed weights are mapped to the normalized interval through proportional conversion. This process maintains the comparability of weights from different sources and eliminates the impact of data dimensionality differences.

[0034] The normalized weight data is fed into the priority determination module. A fixed priority threshold parameter is set, and a comparator compares the weight against the preset threshold in real time. For entries above the threshold, a priority identifier is added and stored in the metadata structure. This identifier provides a basis for prioritization in subsequent processing stages.

[0035] The location coordinate generation process incorporates a random distribution algorithm. Initial region coordinate range parameters are preset, and a random number generator is weighted based on the term priority identifier. High-priority terms generate coordinates in the center region, while common terms generate coordinates in the periphery. The algorithm outputs a set of location coordinate points that conform to a two-dimensional uniform distribution.

[0036] Movement speed parameters are extracted from a preset speed configuration library. This library stores baseline movement speed values ​​and dynamically adjusts the actual speed value based on the display area size. Speed ​​parameters, along with position coordinates, form the foundation of an entry's movement trajectory.

[0037] The text content, priority identifier, location coordinates, and movement speed parameters are input into the structured data assembly module. This generates a data object consisting of fixed field key-value pairs. This object complies with the entry object pool management specification and stores the mapping relationship between key and value pairs in a hash table structure.

[0038] The entry object pool implements a memory management mechanism. It uses a least recently used strategy to dynamically maintain object lifecycles. When the number of objects in the pool reaches a threshold, the storage resources of objects that have not been used for a long time are automatically reclaimed. Newly generated data objects are added to the head of the object pool resource list, enabling efficient insertion operations.

[0039] The object pool management interface provides a unified access point. It supports three core operations: adding new objects, querying existing objects, and removing expired objects. Each operation is encapsulated as an atomic transaction to maintain the consistency of the object pool data state. Finally, the data object is returned to the main process for subsequent spatial mapping.

[0040] Specifically, the two-dimensional dynamic word cloud display method based on spherical mapping of the present invention includes, in step 2: S31: Establishing a coordinate system with the upper left corner of the display area as the origin; S32: Perform horizontal coordinate transformation on each entry: standard horizontal coordinate = 2×(original horizontal coordinate / display width)-1; S33: Perform vertical coordinate transformation on each entry: standard vertical coordinate = 1-2×(original vertical coordinate / display height); S34: When the display area size changes, re-execute S31 to establish the coordinate system and update the display width and display height parameter values ​​in S32-S33.

[0041] During the coordinate system construction phase, a two-dimensional rectangular coordinate system is established with the upper-left corner of the visual display area as the absolute origin. This coordinate system maps the physical pixel coordinate system to a standardized mathematical space, with the horizontal direction based on the total number of pixels in the horizontal direction of the display and the vertical direction based on the total number of pixels in the vertical direction, establishing a complete planar reference system.

[0042] Performs a horizontal coordinate transformation on the entry. Obtain the entry's original horizontal coordinate value and divide it by the actual width of the display area to obtain a normalized scale factor. This scale factor is linearly transformed to the range [-1, 1], where the original horizontal coordinate minimum is mapped to -1, the maximum is mapped to 1, and the center of the coordinate corresponds to zero, completing the horizontal normalization process.

[0043] Performs a vertical coordinate mirroring operation. Reads the original vertical coordinate value of the entry and normalizes it based on the actual height parameter of the display area. This mathematical transformation flips the coordinate direction so that the bottom of the display area corresponds to the negative region of the coordinate system, the top corresponds to the positive region, and the center of the coordinate system is located at the geometric center of the display area.

[0044] The coordinate transformation process is encapsulated as a separate function module. This module receives the original coordinates and display size parameters, calls the floating-point arithmetic unit to perform arithmetic operations, and outputs the coordinate values ​​in the standard coordinate system. The function implementation supports vectorized processing, allowing batch processing of coordinate data sets in the entry object pool.

[0045] The dynamic adaptation mechanism responds to display area size changes. When the operating system sends a resolution adjustment message or the window manager triggers a size change notification, the new display width and height values ​​are automatically captured. This update process does not interrupt the main processing flow, but executes parameter updates asynchronously in a background thread.

[0046] The coordinate system rebuild operation simultaneously refreshes all associated parameters. The coordinate system instance is reinitialized by calling the coordinate conversion function, injecting the newly acquired display size parameters into the horizontal and vertical transformation functions. The updated function instance is capable of handling the new resolution data, ensuring the continuity of coordinate conversion.

[0047] Transformation parameter updates utilize hot swap technology. While maintaining the integrity of the current frame, the next rendering cycle automatically switches to the new parameter version. This technology enables seamless transitions during resolution changes, avoiding data gaps during coordinate calculations.

[0048] Normalized coordinates are output to the downstream distance calculation module. The converted coordinate values ​​maintain double-precision floating-point accuracy, ensuring numerical stability for subsequent spatial calculations. The horizontal and vertical coordinate values ​​are combined to form a normalized position vector, providing the geometric data foundation for Euclidean distance calculations. All coordinate data is transferred via memory mapping, reducing data copying overhead.

[0049] The entire coordinate conversion system forms a data pre-processing pipeline. Raw pixel coordinates are input, standardized, and then output as unified mathematical space coordinates, forming the foundational data preparation stage of the spatial mapping process. The system supports dynamic maintenance of display parameters, adapting to the changing needs of various visualization application scenarios.

[0050] Specifically, the two-dimensional dynamic word cloud display method based on spherical mapping of the present invention includes, in step 4: S41: Receive the Euclidean distance value calculated in step 3; S42: When the Euclidean distance value is 0, the calculated spatial effect parameter is 1; S43: When the Euclidean distance value is 1, the calculated spatial effect parameter is 0; S44: The Euclidean distance value is negatively correlated with the spatial effect parameter, and a continuous attenuation mapping from the [0, 1] interval is achieved through the cosine attenuation function, and the spatial effect parameter is output to step 5.

[0051] During the spatial effect parameter generation phase, the system receives a Euclidean distance data stream from an upstream process. This data stream carries the scalar value of the two-dimensional distance between the entry center and the origin of the coordinate system, within a predefined closed interval. The spatial mapping system then implements differentiated parameter calculation strategies based on this distance value.

[0052] When the input distance value is at the lower limit of the range, the maximum value of the spatial effect parameter is directly returned. This processing mechanism represents the special state when the entry is located at the center point of the coordinate system, corresponding to the strongest visual performance weight in the spatial perception model.

[0053] When the distance value reaches the upper range threshold, the parameter minimum calculation rule is triggered. This calculation responds to the extreme case where the term is at the edge of the display area, and the spatial effect parameter converges to zero, corresponding to the visual performance weight attenuation characteristic.

[0054] A cosine decay function is used to implement nonlinear transformations for distance values ​​within open intervals. Distance values ​​are inversely proportional to spatial effect parameters, and the function curve exhibits a smooth, monotonically decreasing characteristic. Within the closed interval from zero to one, the function achieves continuous mapping output, eliminating data jumps.

[0055] The cosine function calculation process is implemented using a mathematical operation library. This module encapsulates the core trigonometric function algorithm. After the input value is processed by angle transformation, the cosine operation is performed to obtain the initial result. The initial result is then linearly corrected to adapt the output value to the spatial parameter domain.

[0056] The parameter mapping process uses a table lookup method to optimize real-time performance. A discretized lookup table of distance and parameter values ​​is pre-established. When the input distance value is within the allowed accuracy range, the corresponding interpolation result is returned. This mechanism reduces computing resource overhead in high-concurrency scenarios.

[0057] After the spatial effect parameters are generated, a numerical out-of-bounds check is performed. Calculation results that exceed the defined domain are clamped to within the standard range. Data that passes the check is marked as valid output and enters the subsequent transmission channel.

[0058] Computation results are transmitted to downstream systems via shared memory channels. A zero-copy transmission mechanism is used to reduce data movement overhead. The receiving module reads parameter data packets according to pre-set interface specifications. Output parameters carry timestamps and version numbers to maintain data traceability.

[0059] The mapping system implements both real-time and batch processing modes. The system automatically detects the size of the input data, employing real-time stream processing for small-scale data and batch computing for large-scale data sets. This mechanism balances computational efficiency and resource utilization.

[0060] The spatial effect parameter carries information about spatial attenuation characteristics. As a core intermediary variable, it provides spherical distribution characteristic data input for the subsequent visual attribute calculation module, bridging the transition from spatial position information to visual attributes. This entire process forms a standardized data processing pipeline.

[0061] Specifically, the two-dimensional dynamic word cloud display method based on spherical mapping of the present invention calculates the scaling value and transparency value of the entry in step 5, including: S51: Perform the following operations based on the spatial effect parameters output in step 4: Scaling value calculation: Scaling ratio value = preset minimum scaling value + (preset maximum scaling value - preset minimum scaling value) × (spatial effect parameter)^γ; S52: Transparency value calculation: Transparency value = preset minimum transparency + (preset maximum transparency - preset minimum transparency) × spatial effect parameter; S53: Control the visual difference intensity between the center and edge areas by adjusting the γ value, where the γ value is a preset adjustable index factor.

[0062] The spatial effect parameter serves as a key input to the visual attribute calculation module. This parameter represents the positional weight of a term in the spherical mapping space, and its value is negatively correlated with the distance from the term to the center. Scaling is calculated using an exponential interpolation algorithm. The minimum scale value provides a baseline for scaling, while the maximum scale value sets the upper limit. An exponential function is used to adjust the scaling gradient in the central region.

[0063] An adjustable gamma factor is embedded in the exponential term of the scaling formula. Increasing the gamma factor significantly amplifies entries in the center and accelerates the attenuation rate at the edges, while decreasing the gamma factor reduces spatial hierarchy. The gamma value configuration parameter is available through the adjustment interface, allowing users to dynamically control the intensity of visual hierarchy.

[0064] Transparency calculations use a linear interpolation scheme. The minimum transparency value sets the baseline transparency, while the maximum transparency value limits the upper limit of transparency variation. The spatial effect parameter acts as a coefficient to directly adjust the actual transparency output, achieving a continuous and smooth change in transparency with spatial position. The center area remains highly opaque, while the edges transition to a semi-transparent state.

[0065] The visual attribute calculation unit implements a batch parallel processing mechanism. After the spatial effect parameter sequence is input, the computing core processes all entry data objects simultaneously. The scaling and transparency values ​​are calculated using a dual-channel architecture, avoiding performance bottlenecks caused by serial calculations and improving system throughput efficiency.

[0066] The preset configuration library manages a collection of basic visual parameters. Configuration tuples, consisting of minimum zoom, maximum zoom, minimum transparency, and maximum transparency values, are stored in a runtime in-memory database. The configuration library supports a hot update mechanism, allowing for real-time adjustments to visual styles.

[0067] The calculated results are validated for numerical validity. Outliers that exceed the physical device's display capabilities are automatically calibrated, scaling is limited to the device's supported scale range, and transparency is constrained to the device's renderable range. Once the data passes the validation, it is marked as output-ready.

[0068] The scaling ratio and transparency values ​​are transmitted to downstream systems via a data bus. The calculation results are encapsulated in a structured data format, including three attribute fields: term identifier, scaling ratio value, and transparency value. A cyclic redundancy check (CRC) is added during data transmission to ensure content integrity.

[0069] Visual attribute data is injected into the word cloud rendering pipeline. The scaling value controls the coefficients of the text vector outline transformation matrix, while the transparency value sets the parameters of the text rendering transparency channel. These two sets of parameters work together to highlight the central word and gradually blur the peripheral words, achieving a spatial depth effect.

[0070] The system establishes a parameter adjustment feedback channel. Rendering output data is returned to the control terminal, providing a reference for gamma value tuning. Users can adjust exponential factor parameters based on real-time visualization to optimize spatial layer distribution. The entire computational process adheres to the performance constraints of the real-time rendering system.

[0071] Specifically, the two-dimensional dynamic word cloud display method based on spherical mapping of the present invention, in step 6, determines whether the entry meets the focus condition, including: S61: Set the zoom ratio threshold = preset maximum zoom value × 0.9; S62: Set the transparency threshold = preset maximum transparency × 0.9; S63: When the zoom ratio value of the entry is greater than or equal to the zoom ratio threshold and the transparency value of the entry is greater than or equal to the transparency threshold, it is determined that the entry meets the focus condition.

[0072] During focus condition detection, the visualization configuration database is called to load the preset maximum zoom and transparency values. The zoom threshold is calculated using a fixed scale factor. The maximum zoom value is multiplied by the predefined factor to generate the trigger threshold, forming the zoom dimension determination benchmark for spatial focus detection. The transparency threshold is calculated simultaneously: the maximum transparency is multiplied by the same scale factor to obtain the transparency dimension determination benchmark, maintaining the symmetry of the visual attribute detection design.

[0073] Receives a sequence of scaling values ​​from a pool of entry objects in real time. This scaling value stream is fed into a threshold comparator module, which performs a greater-than-or-equal-to logic operation. When the scaling value reaches or exceeds a preset threshold, a first condition-satisfied signal is generated, indicating that the entry has entered a candidate focus area in the zoom dimension.

[0074] The transparency value data stream is synchronously received. The transparency value is input into an independent comparison unit, which performs a non-less-than-or-missing match operation against a preset threshold. When the transparency value crosses the judgment threshold, a second condition is triggered, indicating that the entry has the focus area feature in the visibility dimension.

[0075] Construct a dual-condition joint decision logic circuit. When both the first and second condition satisfaction signals are active, a focus determination trigger signal is triggered. This signal carries the entry's unique identifier and is transmitted to the state control system via the event bus, generating a digital event indicating the focus determination result.

[0076] The judgment result is converted into a structured data object. The focus establishment trigger signal triggers the data encapsulation operation, outputting a focus event object that includes the entry identifier, timestamp, and location coordinates. The event object is stored in binary compression and pushed to the freeze instruction processing system via a message queue.

[0077] The threshold system supports dynamic adjustment. The scaling coefficient parameters are stored in a runtime configuration manager, and an API is exposed for external system modification. Coefficient adjustments trigger a threshold recalculation process, regenerating the detection baseline value and enabling online configuration of detection sensitivity.

[0078] The focus determination process implements a result verification mechanism. It analyzes the historical trajectory of terms that trigger focus events and suppresses repeated triggering actions when a focus event has recently been triggered. This mechanism is implemented through event log filters to maintain the validity status of focus triggers.

[0079] The decision system outputs a standardized event stream. Focus events are sorted by occurrence time and assigned a confidence score. This output stream is connected to a distributed event distribution network, allowing multiple subscribing systems to access real-time focus state change data, providing decision-making support for the attention guidance system. The entire detection process achieves millisecond-level response time, meeting the real-time interaction requirements of dynamic word clouds.

[0080] Specifically, the two-dimensional dynamic word cloud display method based on spherical mapping of the present invention freezes the entry movement state and activates the countdown timer in step 7, including: S71: In response to the focus condition of step 63, freeze the entry position coordinate update function; S72: Activate the countdown timer to start counting; S73: After the countdown ends, the entry movement function is executed and the frozen state flag is cleared; S74: Mark the entry focus has been triggered.

[0081] After the focus condition determination result is passed to the state control system, the freeze instruction generation module immediately responds to the valid focus event. This module sends a lock control signal to the entry position update system, blocking the execution permission of the position coordinate calculation function, making the entry position data enter an unchangeable state, and achieving the physical freezing effect of the moving state.

[0082] The timer control unit synchronizes the countdown process. It calls the system clock source to initialize the timing sequence, presetting a fixed duration as the focus dwell period. The timing thread runs independently of the main rendering thread and uses a non-blocking time monitoring mechanism to avoid affecting the system's real-time performance.

[0083] When the countdown reaches the end of the preset period, the automatic state transition operation is triggered. The position lock control signal is released, and the execution permission of the position coordinate calculation function is reopened. The frozen state identifier is deleted from the memory storage area, clearing the existing record of the frozen state.

[0084] The event marking system runs synchronously with the start of the freeze. A focus-triggered flag is added to the corresponding entry data structure. This flag is stored in the entry object's status field using a Boolean variable. While this flag is active, the focus detection module ignores repeated triggering attempts for the same object.

[0085] The state transition process implements multi-layer data validation. Before releasing the frozen state, the countdown sequence is verified for integrity and validity. The flag write operation includes data version verification to prevent state overwrite issues in multi-threaded scenarios. All state change operations are encapsulated as atomic transactions to maintain system state consistency.

[0086] Freeze status information is published via shared memory. The main rendering loop reads the freeze status identifier in real time to control the on / off status of the entry position update pipeline. The focus-triggered flag is subscribed to by the focus detection system, forming a cross-module collaborative control mechanism.

[0087] The countdown end event generates a state change log. This log records the event timestamp, operation term identifier, and operation type code, and writes it to the circular event buffer. Log data supports system failure recovery and provides state traceability.

[0088] The focus guidance control system completes the event response chain. Focus events trigger freezing and timer initiation, while the countdown's expiration triggers state restoration, forming a closed-loop control process. The system's state transitions maintain idempotence, ensuring that repeated execution of the same operation maintains a consistent final state. This overall mechanism achieves a complete technical closed loop from focus identification to attention guidance.

[0089] Specifically, the two-dimensional dynamic word cloud display method based on spherical mapping of the present invention, in step 8, updating the horizontal position of the entry includes: S81: When the freeze state flag indicates an unfrozen state, obtain the moving speed value generated in step 1; S82: Based on the loop execution period of step 11, calculate the updated horizontal position coordinate: new horizontal coordinate = current horizontal coordinate + moving speed value; S83: Keep the vertical coordinate value unchanged and output the updated entry position.

[0090] In the frozen state detection module, the Boolean status value of the frozen state identifier is polled in real time. If the identifier indicates an unfrozen state, the entry object pool is accessed to extract the corresponding data object's movement speed attribute. The movement speed value is read from the structured storage area as a scalar parameter and input into the displacement calculation unit for subsequent processing.

[0091] The main rendering loop triggers a position update transaction. Each time a pulse signal arrives, the motion processing engine retrieves the current horizontal position coordinate. The computation unit performs a scalar addition operation, summing the original horizontal coordinate value with the movement speed value to generate a new horizontal coordinate value. The result is stored in a temporary register.

[0092] The vertical coordinate maintenance mechanism uses a data persistence strategy. It copies the current vertical coordinate value from the coordinate memory to the output register, preserving the original vertical position data. This operation ensures that the entry's movement trajectory is strictly limited to the horizontal direction, conforming to the visual specifications of the flow layout.

[0093] The position update process implements computational overflow protection. Before submitting the new horizontal coordinate value, a numerical bounds check is performed, and exception handling is performed for results that exceed the floating-point representation range. Once the check passes, the new coordinate data, including the entry identifier, is written to the output queue, awaiting consumption by downstream processing nodes.

[0094] The output module encapsulates a standardized location data structure. It combines horizontal and vertical coordinates into a two-dimensional vector object, appending timestamps and version number metadata. Location update events are pushed to the boundary detection system via the messaging middleware, enabling loosely coupled communication between modules.

[0095] The motion processing system implements an incremental update model. A full output process is triggered only when there is an actual position change; a no-op command is issued if the position remains unchanged. This mechanism reduces system communication overhead and optimizes bus bandwidth utilization.

[0096] Coordinate change history is stored in a circular buffer. Each update operation records the coordinate change trajectory, preserving the position sequence of the most recent frames. This trajectory data supports dynamic effect retrospective analysis and provides data support for visual anomaly diagnosis.

[0097] The displacement parameter system establishes a feedback adjustment channel. The movement speed value opens an application configuration interface, allowing dynamic adjustment during runtime. When the user adjusts the movement rate parameter, the system automatically refreshes the internal buffer value of the calculation unit, realizing the parameter hot update function.

[0098] The entire position update process strictly adheres to state control constraints. Displacement calculations are automatically skipped when in a frozen state, while the computation pipeline is activated when in an unfrozen state. A built-in state machine manages operating mode switching, ensuring that position update behavior is consistent with the logic of the frozen control signals. The computation unit outputs seamlessly integrate into the boundary detection processing pipeline.

[0099] Specifically, the two-dimensional dynamic word cloud display method based on spherical mapping of the present invention includes in step 9: S91: When the horizontal position of the updated entry output in step 8 exceeds the display boundary, reset the horizontal position coordinates of the entry to the new coordinates generated by the initial position coordinate algorithm in step 1; S92: allocating new text content from the available entry list to overwrite the original entry according to the entry object pool management strategy; S93: Update the used entry record table and mark the original entry text as being in an allocable state.

[0100] The boundary detection module monitors the horizontal position coordinate data stream in real time. When the received horizontal coordinate value exceeds the physical boundary threshold of the display area, the resource reset workflow is triggered. The system calls the initial position generation engine, executes the random coordinate calculation algorithm, and outputs a new horizontal coordinate value. This coordinate data overwrites the original position record, achieving spatial position reset.

[0101] The entry object pool manager initiates the text resource replacement protocol. Based on the least recently used strategy, it scans the list of available text resources and extracts the unused text content at the top of the list. The replacement operation uses a write-on-write mechanism, modifying the text pointer while preserving the memory address, achieving atomic updates of the entry content.

[0102] The resource status management system simultaneously performs record table maintenance. It locates the index entry for the original entry in the used record table and changes the entry's status to the allocable flag. This flag change triggers the resource recycling thread, which reinserts the released text resource into the end of the available resource list, completing the resource recycling loop.

[0103] The record table implements a concurrent access control mechanism. Status updates utilize row-level locking technology, with version number verification to prevent multi-threaded write conflicts. A transaction log is generated for modified record tables, recording the operation timestamp and operator ID, supporting system rollbacks and audit trails.

[0104] Object pool maintenance operations trigger load balancing checks. When the length of the available resource list falls below the warning threshold, an asynchronous preloading thread is activated to replenish text resources from the persistent storage layer. This maintains a dynamic balance in resource pool capacity, ensuring the system's sustainable operation.

[0105] The replacement process implements a data integrity check mechanism. After the new text content is loaded into memory, it undergoes format verification to filter out illegal characters and overlong strings. Failure to verify triggers an exception handling process, rolling back to the previous valid text state to ensure system robustness.

[0106] Position reset events generate system monitoring metrics. These metrics record operational parameters such as the number of resets per unit time and resource replacement frequency, and convert them into performance monitoring data points. These metrics are fed into a real-time dashboard system, providing a quantitative basis for operational decisions.

[0107] An automated fault-tolerant recovery system is built throughout the entire process. Position reset failures are automatically retried, text replacement anomalies trigger backup resource scheduling, and record table corruption triggers a backup recovery mechanism. Multi-level fault tolerance ensures critical service continuity and meets the reliability requirements of production environments.

[0108] Specifically, in the two-dimensional dynamic word cloud display method based on spherical mapping of the present invention, the entry object pool management strategy in step 9 includes: S101: Reclaim entry object resources using the least recently used strategy; S102: Remove entry objects that exceed the display boundary and recycle text resources; S103: Select the new entry text content from the head of the available entry list; S104: Verify that the new entry text is not registered in the used entry record table, and update the record table to mark it as in use.

[0109] During the resource recovery phase, a least recently used (LRU) elimination algorithm is implemented to maintain the object pool. The access log database stores the timestamp information for each entry object, and a scheduled scan task is initiated to clean up the least recently accessed instances. The storage resources of removed objects are immediately released back to the memory management pool to maintain a dynamic balance in the total resource base.

[0110] The boundary overflow object processing process sets a dedicated trigger. Upon receiving a boundary overflow notification event from the boundary detection system, the corresponding entry object instance is located. Resource destruction is performed to remove references to the text content, and the released text string is recycled into a reusable resource pool.

[0111] The list of available text resources is managed using a queue data structure. Newly available resources are inserted at the end of the queue, and resource allocation operations extract content from the head of the queue. The allocation process reads the data block at the first node of the linked list, obtains the encapsulated text string resource, and passes it to the caller.

[0112] Perform a uniqueness check before loading new entries. Query the index structure of the used record table to check whether the candidate text exists in the active set. If a conflict exists, the current selection result is discarded, triggering the backup selection process to reschedule resources and prevent duplicate content from being displayed.

[0113] After the uniqueness check passes, the status marking operation is initiated. A new entry is created in the used record table, and the status flag is set to occupied. The registration information includes metadata such as the entry identifier, registration time, and resource location, and a runtime tracking record is established.

[0114] Record table update transactions include a pre-commit validation phase. After verifying that the newly registered entry does not conflict with the active set, an atomic commit operation is performed. If the commit fails, an automatic rollback mechanism is activated, resetting the record table state to maintain data consistency and avoid partial update anomalies.

[0115] The resource manager implements a capacity warning response mechanism. When the length of the available resource queue falls below the warning threshold, an asynchronous preload process is triggered. A batch load request is sent to the data source system to add new text resources to the end of the available queue, maintaining a continuous supply of resources.

[0116] The resource pool builds a hierarchical monitoring instrumentation system. This system collects operational metrics such as object removal frequency, resource reuse times, and allocation delays. This monitoring data is pushed to a real-time analysis engine, which generates resource utilization efficiency reports and drives the optimization of elimination strategy parameter configurations.

[0117] The system integrates an exception handling bus architecture. Resource allocation conflicts send exception events to the processing center, triggering resource reselection or capacity expansion. Errors in logging tables trigger backup and recovery procedures. Multiple security mechanisms address various edge scenarios, ensuring the sustainable supply of critical resource services.

[0118] This method constructs the spatial hierarchy of a dynamic word cloud using a spherical mapping model. First, the original coordinates of the entries are normalized to a standard coordinate system, and the Euclidean distance from the center point is calculated. Second, the distance value is nonlinearly mapped to a spatial effect parameter using a cosine decay function. The parameter output reaches its maximum value when the distance approaches zero, and the parameter value decreases continuously as the distance increases. Finally, the scaling and transparency values ​​of the entries are dynamically calculated based on the spatial effect parameters. The central region entries are magnified and opaque, while the peripheral regions entries are shrunk and transparent, creating a visual depth effect with a prominent center and diminishing edges.

[0119] The solution implements an attention-directing mechanism to address the issue of distracted focus. When an entry meets both the scaling and transparency thresholds, it enters the focus area. This immediately freezes the entry's movement, activating a countdown timer to maintain focus. Once the freeze is lifted, the focus indicator is marked as triggered, preventing repeated triggering from distracting the user. This mechanism enforces the locking of key information, breaking the limitations of a uniform, fluid layout.

[0120] The system establishes a closed loop of cyclic updates to maintain dynamic display. During the displacement update phase, only unfrozen entries are moved horizontally at a preset speed. When boundary detection is triggered, the position is reset to the initial area and new text content is assigned. During the rendering phase, word clouds are generated by integrating position, scale, and transparency parameters. The main loop drives the entire process from coordinate conversion to rendering. Position reset is connected to the object pool management system, enabling the coordination of content updates and spatial hierarchy reconstruction, ultimately forming a dynamic visualization system with spatial depth and focus guidance capabilities.

[0121] The specific implementation of the present invention is as follows: Spatial hierarchy construction: Create a pool of term objects and retrieve raw text data through a local database or remote API. The parser extracts the term text and weight values, performs linear normalization, and outputs them to a preset weight range. Terms with weights exceeding the priority threshold are marked with a priority flag. Position coordinates are generated using a preset initial position coordinate algorithm and packaged into a data object along with a preset movement speed value. A coordinate system is established with the upper-left corner of the display area as the origin. A linear transformation is used to map the raw position coordinates to standard coordinate values ​​(standard horizontal coordinate = 2 × original horizontal coordinate / display width - 1; standard vertical coordinate = 1 - 2 × original vertical coordinate / display height). The Euclidean distance from the term to the center point is calculated based on the standard coordinates. A cosine decay function is used to nonlinearly map the Euclidean distance value to a spatial effect parameter (distance value 0 corresponds to parameter 1, and distance value 1 corresponds to parameter 0). The scaling ratio and transparency values ​​of entries are calculated synchronously based on the spatial effect parameters. The scaling ratio calculation introduces an adjustable exponential factor γ to control the visual gradient difference between the center and the edge. The transparency value uses linear interpolation to achieve continuous change, so that the entries in the central area are significantly enlarged and opaque, and the entries in the edge area are reduced and transparent, forming a spherical distribution of visual depth of field effect.

[0122] Focus Lock Mechanism: When the zoom ratio of an entry reaches a fixed ratio threshold of the preset maximum zoom value, and the transparency value reaches a fixed ratio threshold of the preset maximum transparency, the focus condition is determined to be met. Triggering a freeze command immediately locks the entry's position update function, activating a countdown timer. After the countdown ends, the movement freeze state is automatically released, the freeze indicator is cleared, and the focus trigger indicator is marked to prevent repeated responses. This mechanism forces key information to remain in the visual focus area for a preset period of time, breaking through the distraction limitations of a uniform flow layout.

[0123] Dynamic loop drive: For entries in an unfrozen state, the horizontal position coordinates are updated according to the moving speed value according to the rendering cycle (new horizontal coordinate = current horizontal coordinate + moving speed value), and the vertical coordinate remains unchanged. When the horizontal position exceeds the display boundary after the update, the entry is reset to the initial area and new text content is allocated: the least recently used strategy is used to reclaim the original entry resources, and the new text is selected from the head of the available entry list. After checking that it has not been registered in the used record table, the original entry text is overwritten and the status mark is updated. At the end of each loop, the graphics interface is called to render the entry object pool, and a dynamic word cloud is output based on the real-time zoom value, transparency value and position coordinates. The main loop continues to drive the entire process of coordinate conversion to rendering until an external termination command is triggered, realizing the coordinated operation of dynamic content update and spatial hierarchy reconstruction.

[0124] The present invention uses a spherical mapping model to construct a visual space hierarchy. The spherical mapping model converts the entry position information into nonlinear spatial effect parameters to simulate the depth perception of real space. The specific algorithm includes a coordinate conversion algorithm and a distance mapping algorithm: the coordinate conversion algorithm first establishes a coordinate system with the upper left corner of the display area as the origin, and normalizes the original position coordinates to the standard coordinate system through linear transformation, so that the horizontal coordinates are mapped to the [-1,1] interval, and the vertical coordinates are mirrored; this processing ensures dynamic adaptation when the display size changes, such as automatically updating the parameters after the window size is adjusted. The distance mapping algorithm calculates the Euclidean distance value from the entry to the center point as a quantitative indicator of spatial position; the Euclidean distance value is input into the cosine attenuation function algorithm to achieve a continuous nonlinear mapping of the distance value from 0 to 1. When the distance is 0, the spatial effect parameter outputs the maximum value of 1, and when the distance is 1, the minimum value is 0, forming an attenuation effect with a strong center and weak edges. This algorithm combination solves the problem of missing spatial hierarchy in the background technology, so that the entry presents a spherical distribution of depth of field in a two-dimensional plane.

[0125] The visual attribute calculation strategy drives the appearance of entries based on spatial effect parameters, enhancing user attention guidance. The scaling calculation strategy introduces an adjustable exponential factor, γ, to control the magnification intensity of entries in the central region and the gradient of reduction at the edges. The transparency calculation strategy uses linear interpolation, with the spatial effect parameter directly determining the transparency value, achieving a visual effect where the central entry is opaque while the edges fade. The strategy design avoids relying on fixed values ​​and instead uses preset minimum and maximum scaling and transparency values ​​as a benchmark. The γ value is adjustable to accommodate different visualization requirements. For example, in data monitoring scenarios, adjusting the γ value can enhance the prominence of central keywords and prevent important information from being overwhelmed by peripheral entries.

[0126] The focus lock mechanism uses state management strategies to enforce the retention of key information. The focus condition determination strategy uses dual-threshold rules: the zoom threshold is a fixed ratio of the preset maximum zoom value (e.g., 0.9x), and the transparency threshold is a fixed ratio of the preset maximum transparency (e.g., 0.9x). When an entry meets both thresholds, it is determined to enter the focus area. In response to this determination, the freeze strategy is immediately activated: the freeze strategy locks the entry position update function and starts a countdown timer. After the countdown ends, it automatically unfreezes and marks the focus trigger indicator to prevent repeated responses. This strategy ensures that the focus entry remains in the visual center for a preset length of time, breaking through the distraction limitations of traditional uniform flow layouts and improving the efficiency of information communication.

[0127] The dynamic loop management strategy maintains the continuous operation of the system. In the unfrozen state, the position update strategy updates the horizontal coordinate according to the rendering cycle based on the movement speed value, and the vertical coordinate remains unchanged; the boundary detection strategy triggers a reset operation when the horizontal position exceeds the display boundary. The object pool management strategy adopts the least recently used strategy to recycle resources: remove out-of-bounds entries and recycle text content, select new text from the head of the available entry list, verify that it has not overwritten the original entry after registration in the used record table, and update the status mark. Strategy collaboration ensures dynamic content updates. For example, in a real-time data stream scenario, the loop drives the entire process from coordinate conversion to rendering. At the end of the main loop, the graphics interface is called to output the word cloud until the external instruction terminates.

Claims

1. A two-dimensional dynamic word cloud display method based on spherical mapping, characterized in that: include: Step 1: Create a term object pool, traverse and obtain term data, and generate a data object for each term including text, weight, initial position coordinates and movement speed attributes; Step 2: Read the original position coordinates of the entry, perform linear transformation and output the coordinate values ​​of the standard coordinate system; Step 3: Use the standard coordinate system coordinate values ​​to calculate the Euclidean distance between the entry and the center point; Step 4: Map the Euclidean distance value to the spatial effect parameter through the cosine decay function, where a distance value of 0 corresponds to parameter 1, and a distance value of 1 corresponds to parameter 0; Step 5: Calculate the scaling value and transparency value of the entries based on the spatial effect parameters, so that the entries in the center area are enlarged and opaque, and the entries in the edge area are reduced and transparent; Step 6: When the scaling value of the entry is greater than or equal to the threshold value T1 and the transparency value of the entry is greater than or equal to the threshold value T2, the entry is determined to meet the focus condition; Step 7: In response to the focus condition, freeze the entry movement state and activate the countdown timer, and record the freeze state flag; Step 8: When the freeze state indicator indicates an unfrozen state, the horizontal position of the entry is updated according to the moving speed value generated in step 1; Step 9: When the horizontal position of the entry updated in step 8 exceeds the display boundary, reset the position of the entry that exceeds the display boundary to the initial area and allocate new text content; Step 10: At the end of each loop of steps 2 to 9, a graphical interface is called to render all entries in the entry object pool, and a dynamic word cloud is formed based on the scaling value, transparency value, and position of each entry in the entry object pool; Step 11: Loop through steps 2 to 10 to drive the entry object pool to update until the rendering termination instruction is triggered.

2. The two-dimensional dynamic word cloud display method based on spherical mapping according to claim 1 is characterized in that: Obtaining entry data in step 1 includes: S21: Read the original text data through the local database or remote API interface; S22: Input the original text data into the parser to extract the entry text and weight value; S23: performing a linear normalization operation on the extracted weight value and outputting it to a preset weight range; S24: marking a priority flag for the entry whose normalized weight value is ≥ the priority threshold; S25: Generate position coordinates based on the text, the marked priority identifier, and a preset initial position coordinate algorithm, and generate a data object in combination with a preset moving speed value.

3. The two-dimensional dynamic word cloud display method based on spherical mapping according to claim 2 is characterized in that: Step 2 includes: S31: Establishing a coordinate system with the upper left corner of the display area as the origin; S32: Perform horizontal coordinate transformation on each entry: standard horizontal coordinate = 2×(original horizontal coordinate / display width)-1; S33: Perform vertical coordinate transformation on each entry: standard vertical coordinate = 1-2×(original vertical coordinate / display height); S34: When the display area size is changed, re-execute S31 to establish the coordinate system and update the display width and display height parameter values ​​in S32 to S33.

4. The two-dimensional dynamic word cloud display method based on spherical mapping according to claim 3 is characterized in that: Step 4 includes: S41: Receive the Euclidean distance value calculated in step 3; S42: When the Euclidean distance value is 0, the calculated spatial effect parameter is 1; S43: When the Euclidean distance value is 1, the calculated spatial effect parameter is 0; S44: The Euclidean distance value is negatively correlated with the spatial effect parameter, and a continuous attenuation mapping from the [0, 1] interval is achieved through the cosine attenuation function, and the spatial effect parameter is output to step 5.

5. The two-dimensional dynamic word cloud display method based on spherical mapping according to claim 4 is characterized in that: Calculating the scaling value and transparency value of the entry in step 5 includes: S51: Scaling value calculation: Scaling ratio value = preset minimum scaling value + (preset maximum scaling value - preset minimum scaling value) × (spatial effect parameter)^γ; S52: Transparency value calculation: Transparency value = preset minimum transparency + (preset maximum transparency - preset minimum transparency) × spatial effect parameter; S53: Control the visual difference intensity between the center and edge areas by adjusting the γ value, where the γ value is a preset adjustable index factor.

6. The two-dimensional dynamic word cloud display method based on spherical mapping according to claim 5 is characterized in that: In step 6, determining whether a term satisfies the focus condition includes: S61: Set the zoom ratio threshold = preset maximum zoom value × 0.9; S62: Set the transparency threshold = preset maximum transparency × 0.9; S63: When the zoom ratio value of the entry is greater than or equal to the zoom ratio threshold and the transparency value of the entry is greater than or equal to the transparency threshold, it is determined that the entry meets the focus condition.

7. The two-dimensional dynamic word cloud display method based on spherical mapping according to claim 6 is characterized in that: Freezing the entry movement status and activating the countdown timer in step 7 includes: S71: In response to the focus condition of step 63, freeze the entry position coordinate update function; S72: Activate the countdown timer to start counting; S73: After the countdown ends, the entry movement function is executed and the frozen state flag is cleared; S74: Mark the entry focus has been triggered.

8. The two-dimensional dynamic word cloud display method based on spherical mapping according to claim 7 is characterized in that: Updating the horizontal position of the entry in step 8 includes: S81: When the freeze state flag indicates an unfrozen state, obtain the moving speed value generated in step 1; S82: Based on the loop execution period of step 11, calculate the updated horizontal position coordinate: new horizontal coordinate = current horizontal coordinate + moving speed value; S83: Keep the vertical coordinate value unchanged and output the updated entry position.

9. The two-dimensional dynamic word cloud display method based on spherical mapping according to claim 8, characterized in that: Step 9 includes: S91: When the horizontal position of the updated entry output in step 8 exceeds the display boundary, reset the horizontal position coordinates of the entry to the new coordinates generated by the initial position coordinate algorithm in step 1; S92: allocating new text content from the available entry list to overwrite the original entry according to the entry object pool management strategy; S93: Update the used entry record table and mark the original entry text as being in an allocable state.

10. The two-dimensional dynamic word cloud display method based on spherical mapping according to claim 9, characterized in that: The entry object pool management strategy in step 9 includes: S101: Reclaim entry object resources using the least recently used strategy; S102: Remove entry objects that exceed the display boundary and recycle text resources; S103: Select the new entry text content from the head of the available entry list; S104: Verify that the new entry text is not registered in the used entry record table, and update the record table to mark it as in use.

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