Information processing method and device, electronic equipment and storage medium

Abstract

The embodiment of the invention provides an information processing method and device, electronic equipment and a storage medium. The method comprises the steps that a multi-dimensional screening instruction of a user is responded, a screening configuration interface of data items is displayed, and the screening configuration interface comprises a plurality of screening dimension areas and a plurality of screening conditions; responding to the operation of dragging the screening conditions to the screening dimension areas in sequence by the user, and configuring the corresponding screening conditions for the screening dimension areas; determining a composite screening rule according to the screening condition configured in each screening dimension region; screening and displaying the data items by applying a composite screening rule; wherein a data partition is displayed in each screening dimension area, and the data partitions are used for displaying a statistical result of composite screening classification on the data items based on the currently configured screening conditions in real time in the screening condition configuration process. By providing the intuitive and efficient multi-dimensional screening mechanism, the limitation of a traditional single screening mode in processing complex data query requirements is effectively solved, and the operation efficiency and experience of a user are greatly improved.

Description

Technical Field

[0001] The embodiments of the present invention relate to the field of computers, and more specifically, the embodiments of the present invention relate to an information processing method, apparatus, electronic device, and storage medium. Background Technology

[0002] This section is intended to provide background or context for embodiments of the invention as set forth in the claims. The description herein is not an admission that it is prior art simply because it is included in this section.

[0003] In existing game interfaces, especially in SLG (Strategy / Simulation) games, players typically need to view and manage a large number of virtual resources. These resources are usually displayed in list format, allowing players to perform simple single-dimensional filtering and sorting. However, when players need to perform multi-dimensional, complex filtering, existing technology can only provide single-dimensional filtering functionality, failing to meet players' needs for complex combinations of resources. This limitation forces players to perform multiple repetitive operations to obtain the required information, increasing operational complexity and reducing user experience. Furthermore, the lack of intuitive previews of filtering results makes it difficult for players to accurately judge the filtering effect, further reducing operational efficiency. In addition, frequent filtering operations increase system resource consumption, impacting game performance. Summary of the Invention

[0004] In this context, embodiments of the present invention aim to provide an information processing method, apparatus, electronic device, and storage medium to at least partially solve the aforementioned problems existing in the related art.

[0005] In a first aspect of the present invention, an information processing method is provided, comprising: responding to a user's multi-dimensional filtering instruction and displaying a filtering configuration interface for data items, the filtering configuration interface including multiple filtering dimension areas and multiple filtering conditions; responding to the user's operation of dragging filtering conditions sequentially to each filtering dimension area and configuring corresponding filtering conditions for each filtering dimension area; determining composite filtering rules based on the filtering conditions configured in each filtering dimension area; and applying the composite filtering rules to filter and display data items; wherein each filtering dimension area displays data partitions, the data partitions being used to display in real time the statistical results of composite filtering and classification of data items based on the currently configured filtering conditions during the filtering condition configuration process.

[0006] In a second aspect of the present invention, an information processing apparatus is provided, comprising: a filtering interface display module, configured to display a filtering configuration interface for data items in response to a user's multi-dimensional filtering command, the filtering configuration interface including multiple filtering dimension areas and multiple filtering conditions; a filtering condition configuration module, configured to configure corresponding filtering conditions for each filtering dimension area in response to a user's operation of dragging filtering conditions sequentially to each filtering dimension area; a rule determination module, configured to determine composite filtering rules based on the filtering conditions configured in each filtering dimension area; a filtering execution module, configured to apply the composite filtering rules to filter and display data items; and a data partition display module, configured to display data partitions in each filtering dimension area, the data partitions being used to display in real time the statistical results of composite filtering and classification of data items based on the currently configured filtering conditions during the filtering condition configuration process.

[0007] In a third aspect of the present invention, an electronic device is provided, comprising: a memory storing computer-executable instructions executable by a processor; and a processor for executing the computer-executable instructions to perform the steps in the above-described information processing method.

[0008] In a fourth aspect of the present invention, a computer-readable storage medium is provided, which stores a computer program that, when executed by a processor, implements the steps in the above-described information processing method.

[0009] The technical solution provided in this disclosure allows users to drag and drop different filter conditions into various dimensions within the filter configuration interface, creating intuitive multi-dimensional filter rules. During the filter configuration process, each filter dimension displays data partitions in real time. These partitions visually represent the data distribution based on the currently configured filter conditions, enabling users to clearly understand the statistical results after each filter operation. This approach not only simplifies the setting of complex filter conditions but also enhances users' perception of data distribution through visual data partitioning. By providing this intuitive and efficient multi-dimensional filtering mechanism, this disclosure effectively addresses the limitations of traditional single-filter methods in handling complex data query needs, significantly improving user efficiency and experience. Attached Figure Description

[0010] The above and other objects, features, and advantages of exemplary embodiments of the present invention will become readily apparent from the following detailed description taken in conjunction with the accompanying drawings. Several embodiments of the invention are illustrated in the drawings by way of example and not limitation, wherein: Figure 1 This is a schematic diagram illustrating the implementation environment of an information processing method provided in this embodiment of the disclosure. Figure 2A flowchart illustrating an information processing method provided in this embodiment of the disclosure; Figure 3 This is a schematic diagram of a data item list interface provided in an embodiment of the present disclosure; Figure 4 This is a schematic diagram of a filtering configuration interface provided in an embodiment of the present disclosure; Figure 5 This is a schematic diagram illustrating dragging filter conditions to a filter dimension area according to an embodiment of the present disclosure; Figure 6 This is a schematic diagram illustrating another method of dragging filter conditions to the filter dimension area, as provided in an embodiment of this disclosure. Figure 7 This is a schematic diagram of the structure of an information processing device provided in an embodiment of the present disclosure; Figure 8 This is a schematic diagram of the structure of an electronic device provided in an embodiment of this disclosure.

[0011] In the accompanying drawings, the same or corresponding reference numerals indicate the same or corresponding parts. Detailed Implementation

[0012] To enable those skilled in the art to better understand the present disclosure, the technical solutions of the present disclosure will be clearly and completely described below with reference to the accompanying drawings of the embodiments. Obviously, the described embodiments are only some embodiments of the present disclosure, and not all embodiments. Based on the embodiments of the present disclosure, all other embodiments obtained by those skilled in the art without creative effort should fall within the scope of protection of the present disclosure.

[0013] It should be noted that the terms "first," "second," etc., in the specification, claims, and accompanying drawings of this disclosure are used to distinguish similar objects and are not necessarily used to describe a specific order or sequence. It should be understood that such data can be interchanged where appropriate so that the embodiments of this disclosure described herein can be implemented in orders other than those illustrated or described herein. Furthermore, the terms "comprising" and "having," and any variations thereof, are intended to cover non-exclusive inclusion; for example, a process, method, system, product, or apparatus that comprises a series of steps or units is not necessarily limited to those steps or units explicitly listed, but may include other steps or units not explicitly listed or inherent to such processes, methods, products, or apparatus.

[0014] The accompanying drawings are schematic illustrations of this disclosure and are not necessarily drawn to scale. Some block diagrams shown in the drawings may be functional entities and do not necessarily correspond to physically or logically independent entities. These functional entities may be implemented in software, in hardware modules or integrated circuits, or in networks, processors, or microcontrollers. Implementations can be carried out in various forms and should not be construed as limited to the examples set forth herein. The features, structures, or characteristics described in this disclosure can be combined in any suitable manner in one or more embodiments. Numerous specific details are provided in the following description to give a thorough description of embodiments of this disclosure. However, those skilled in the art will recognize that one or more specific details may be omitted when implementing the technical solutions of this disclosure, or other methods, components, apparatuses, steps, etc., may be used to replace one or more specific details.

[0015] Figure 1 A system architecture diagram of the operating environment of this exemplary embodiment is shown. This system architecture may include a terminal device 110 and a server 120. The terminal device 110 may be a mobile phone, tablet computer, personal computer, smart wearable device, game console, etc., and has a display function capable of displaying a graphical user interface, which may include the operating system interface or the application interface. An application, such as a game program, is installed on the terminal device 110. The server 120 generally refers to the backend system providing application services in this exemplary embodiment; it may be a single server or a cluster of multiple servers. For example, a game server program is deployed on the server 120 to perform server-side game data processing. The terminal device 110 and the server 120 can be connected via a wired or wireless communication link for data transmission. The method in one exemplary embodiment of this disclosure can be executed by any one or more of the terminal device 110 and the server 120.

[0016] In one implementation, the above method can be implemented and executed based on a cloud interaction system. The cloud interaction system can be the system architecture described above. Various cloud applications, such as cloud gaming, can run under the cloud interaction system. Taking cloud gaming as an example, cloud gaming can be a game mode based on cloud computing. In the cloud gaming operation mode, the game program's execution entity and the game screen presentation entity are separated. The storage and execution of the game's control and interaction methods are completed on the cloud gaming server (such as the aforementioned server 120). The cloud gaming client (such as the aforementioned terminal device 110) is responsible for receiving and sending data and presenting the game screen. For example, the cloud gaming client can be a display device with data transmission capabilities located close to the user, such as a mobile terminal, television, computer, or PDA; while the cloud gaming server in the cloud performs information processing. When playing the game, the user operates the cloud gaming client to send operation commands to the cloud gaming server. The cloud gaming server runs the game according to the operation commands, encodes and compresses the game screen and other data, returns it to the cloud gaming client via the network, and finally, the cloud gaming client decodes and outputs the game screen.

[0017] In one implementation, the method described above can be implemented by the terminal device 110 alone. For example, without deploying the server 120, the terminal device 110 can run the application in a standalone environment to implement the game function and execute the method described above.

[0018] This embodiment provides an information processing method. Figure 2 This is a flowchart of an information processing method according to an embodiment of the present disclosure, such as... Figure 2 As shown, the process includes the following steps: Step S110: In response to the user's multi-dimensional filtering command, display the filtering configuration interface for the data items. The filtering configuration interface includes multiple filtering dimension areas and multiple filtering conditions.

[0019] Step S120: In response to the user's operation of dragging the filter conditions to each filter dimension area in sequence, configure the corresponding filter conditions for each filter dimension area.

[0020] Step S130: Determine the composite filtering rules based on the filtering conditions configured for each filtering dimension region.

[0021] Step S140: Apply composite filtering rules to filter and display the data items.

[0022] In step S150, each filter dimension area displays data partitions. These data partitions are used to display in real time the statistical results of composite filtering and classification of data items based on the currently configured filter conditions during the filter condition configuration process.

[0023] The method provided in this implementation allows users to construct composite filtering rules by dragging and dropping filter conditions to multiple filtering dimension areas, while simultaneously displaying the data distribution in real time during the configuration process. This visualized multidimensional filtering mechanism not only enhances the interactive experience, enabling users to intuitively understand data distribution and quickly adjust filtering strategies, but also enriches resource management in games, allowing players to more accurately find the virtual resources they need. Furthermore, by displaying data in real-time partitions and determining composite rules in one go, it reduces repetitive filtering operations and the data processing burden on the server, effectively solving the problem of low efficiency in multiple data queries and processing in the computer field.

[0024] The steps described above are explained in detail below.

[0025] In step S110, in response to the user's multi-dimensional filtering command, the filtering configuration interface of the data item is displayed. The filtering configuration interface includes multiple filtering dimension areas and multiple filtering conditions.

[0026] Optionally, multidimensional filtering commands are user-triggered operation commands used to activate the composite filtering function. For example, commands can be issued by clicking the composite filtering button or other interactive elements on the interface, or commands can be entered through other interaction methods such as voice or gestures.

[0027] Optionally, data items are information units that need to be filtered, which can be virtual resources in the game or other types of data records.

[0028] Optionally, the filter configuration interface is a dedicated interface for users to set filter conditions, containing multiple interactive elements for building filter rules.

[0029] Optionally, the filter dimension area is an interface component used to carry the user's configured filter conditions. Its function is to receive and display the filter conditions selected by the user, thereby supporting the construction of compound filter rules.

[0030] Optionally, the filter criteria are specific parameters used to filter data items, such as resource type, level, location information, etc., which can be dragged to the filter dimension area.

[0031] In step S120, in response to the user's operation of dragging the filter conditions to each filter dimension area in sequence, the corresponding filter conditions are configured for each filter dimension area.

[0032] Optionally, drag-and-drop is an interactive action where the user moves the filter criteria from the initial position to the target filter dimension area using an input device.

[0033] Optionally, configuring filter criteria is the process of associating specific filter criteria with corresponding filter dimension areas.

[0034] In step S130, composite filtering rules are determined based on the filtering conditions configured for each filtering dimension region.

[0035] Optionally, composite filtering rules are data filtering logics formed by combining multiple filtering conditions, used to classify and sort data items in multiple dimensions.

[0036] In step S140, composite filtering rules are applied to filter and display the data items.

[0037] Optionally, the filter display is the process of sorting and presenting data items according to composite filter rules.

[0038] In step S150, each filtering dimension area displays data partitions. These data partitions are used to display in real time the statistical results of composite filtering and classification of data items based on the currently configured filtering conditions during the filtering condition configuration process.

[0039] Optionally, data partitions are visual elements displayed in the filter dimension area to visually show the statistical distribution of filter results based on specific filter criteria.

[0040] Optionally, the statistical results of composite screening classification are data analysis information generated during the screening process, reflecting the distribution of data items under various combinations of screening conditions.

[0041] In a specific application of this embodiment, see Figures 3 to 6 In the game, when players need to manage multiple virtual resources, they can access the filter configuration interface by clicking the composite filter button on the resource list screen. This interface displays multiple filter dimensions in a parallel track format, showing various filter conditions including resource type, resource level, state capital, and distance from the main city. Players can drag the resource type condition to the first filter dimension area, which will then display data partitions for different resource types, visually showing the quantity proportion of each type of resource through the partition size. Subsequently, players can drag the level condition to the second filter dimension area, and the system will further display the distribution of different levels under each resource type based on the first-level filter results. After completing the multi-dimensional filter configuration, players confirm the operation, and the system applies this composite filter rule to display the filter results in the resource list, helping players quickly locate the specific resources they need.

[0042] In an optional implementation, in response to a user's multi-dimensional filtering command, a filtering configuration interface for data items is displayed, including: displaying a list interface of data items, where multiple filtering conditions and multi-dimensional filtering controls are shown; and displaying the filtering configuration interface in response to the user's operation on the multi-dimensional filtering controls. This simplifies the user's process of initiating composite filtering by providing an intuitive entry point for the multi-dimensional filtering controls, thus improving interaction efficiency.

[0043] For example, refer to Figure 3 , Figure 4 In the resource management system, when a user views the list of resource locations, the system first presents a standard list interface. At the top of this interface, multiple filter options are displayed, such as resource type, resource level, state capital, and distance from the main city. A multi-dimensional filter control button with a "composite filter" label is also prominently displayed. When the user clicks this button, the system responds and switches to the filter configuration interface. This interface contains multiple interactive filter dimensions and draggable filter conditions, allowing users to perform complex multi-dimensional filter configurations.

[0044] Optionally, the list interface is the main view for displaying data items, typically presented in table or card format. This interface not only displays basic information about the data items but also integrates filtering functionality. In a game scenario, the list interface can display various resources owned by the player, such as land, buildings, and equipment.

[0045] Optionally, a multi-dimensional filter control is an interactive element specifically designed to initiate composite filtering functionality. This control can be designed as a button, icon, or other visual form, typically placed in a prominent position on the list interface. In implementation, the multi-dimensional filter control needs to be linked to the background filtering logic. When the user triggers the control, the system needs to prepare the initial data required by the filtering configuration interface, including the available filter dimensions and condition options.

[0046] Optionally, filter criteria are parameters or standards used to filter and organize data items, representing various attributes or characteristics of the data items. In a composite filter system, filter criteria can be discrete, such as categorical data like resource type (grain, timber, iron ore, etc.), resource region (state capital, territory, etc.), and resource level (primary, intermediate, advanced); or they can be continuous, such as numerical data like distance from the main city, resource production efficiency, and time taken. Filter criteria can be presented as text labels, icons, drop-down menus, etc., typically using visually easily understood elements. In the design of filter criteria, frequently used criteria can be set to be visible by default, while less frequently used criteria can be placed in the "More Filters" category. For numerical filter criteria, a range selection function can be provided, allowing users to set minimum and maximum values. Filter criteria can have a hierarchical relationship, such as first selecting the resource type, then selecting the specific level under that type, forming a cascading effect of criteria.

[0047] Optionally, the filter configuration interface is an interactive area specifically designed for setting composite filter rules. The filter configuration interface can be a pop-up overlay on the list interface, a slide-in panel, or a standalone page. In terms of layout, the filter configuration interface is typically divided into multiple functional areas, including a filter condition selection area, a filter dimension area (such as a visual track), and an operation button area. The filter configuration interface supports intuitive drag-and-drop operations, allowing users to drag filter conditions to different filter dimension areas. In terms of interaction logic, the filter configuration interface supports adding, removing, and reordering filter conditions, and updates the statistical results of data partitions in real time.

[0048] In an optional implementation, the number of filter dimension areas is the same as the number of filter conditions. This one-to-one correspondence ensures that users can fully utilize all the filter conditions provided by the system for multi-dimensional filtering, simplifies the interface design, avoids user confusion caused by too many or too few filter dimension areas, and also optimizes system resource utilization by avoiding the creation of redundant filter areas.

[0049] For example, see Figure 4 In the filter configuration interface design, the system creates the same number of filter dimension areas as the total number of data attributes that can be used for filtering (such as resource type, resource level, state capital, distance from the main city, etc.). These areas are arranged in the form of parallel tracks. When the user enters the filter configuration interface, they can see that the top of the interface displays the same number of filter condition options as the number of tracks. The user can drag and drop any filter condition into any filter dimension area for configuration as needed, ensuring that each filter condition has its own dedicated dimension area for setting.

[0050] Optionally, the number of filter dimension areas directly impacts the overall structure and user experience of the multi-dimensional filtering system. In practice, the number of filter dimension areas can be dynamically adjusted based on the type and quantity of available filter conditions in the system. The layout of filter dimension areas in the interface typically employs vertical stacking or horizontal arrangement. Each area can be distinguished using different visual elements (such as color, border, or background) to help users identify different filter levels. In terms of interaction design, each filter dimension area can provide clear visual cues, guiding users on how to place and configure filter conditions within that area. The system can automatically adjust the area size and layout according to the screen size of different devices, ensuring a good user experience across various terminals.

[0051] Optionally, the number of filter criteria refers to the total number of different attributes or features available for filtering data items in the system. When designing a multidimensional filtering system, the number of filter criteria should be determined based on the characteristics of the data items and the actual needs of the users. Filter criteria can be categorized according to data type, such as categorical criteria (e.g., resource type, region), numerical criteria (e.g., level, distance, time), and Boolean criteria (e.g., whether occupied, whether interactive). The system can provide a fixed number of preset filter criteria or be designed to support user-defined filter criteria, increasing the system's flexibility. Filter criteria can be presented as text labels, icons, drop-down menus, or combo controls; the appropriate presentation format should be chosen based on the complexity and frequency of use of the criteria.

[0052] Optionally, a one-to-one correspondence means that the number of filter dimension areas is exactly equal to the number of filter conditions provided by the system, forming a precise pairing mechanism. During interface initialization, the system checks the total number of available filter conditions and then dynamically creates the same number of filter dimension areas. The one-to-one correspondence can be implemented in a fixed manner, meaning a specific filter condition can only be placed in a designated filter dimension area; or it can be a flexible one-to-one correspondence, meaning any filter condition can be placed in any filter dimension area, but the total number remains consistent. During interaction, when a user drags a filter condition to a filter dimension area, the system checks if the area already has a filter condition configured. If it does, it may prompt the user to replace the existing condition or automatically adjust to another available dimension area. The one-to-one correspondence can also be enhanced visually, such as using the same color or pattern to identify the corresponding filter condition and filter dimension area, or highlighting the target area during dragging. This correspondence also supports undo and redo functionality, allowing users to adjust or reset the allocation of filter conditions during configuration.

[0053] In an optional implementation, the filter dimension areas are arranged in a predetermined order. In response to the user dragging filter conditions sequentially to each filter dimension area, corresponding filter conditions are configured for each filter dimension area. This includes: in response to the user dragging filter conditions to each filter dimension area in a predetermined order, configuring corresponding filter conditions for each filter dimension area sequentially. In this way, by guiding the user to configure filter conditions step-by-step through the preset dimension area order, the hierarchical and coherent nature of the filtering logic is ensured, improving the accuracy and operability of composite filtering.

[0054] For example, see again Figures 4 to 6In the filter configuration interface, the system arranges the filter dimension areas into parallel tracks in a predetermined order from left to right. Users need to drag the filter conditions to each filter dimension area in order from left to right. First, drag the selected filter condition to the first dimension area on the left, then drag the selected second filter condition to the second dimension area from the left, and then drag the selected third filter condition to the third dimension area. After the user completes the filter condition configuration for the first dimension area, the area will display the statistical distribution based on the first filter condition. Subsequently, when the user configures the second dimension area, the system will automatically further statistically subdivide the data based on the classification results of the first dimension under the second filter condition.

[0055] Optionally, the pre-defined order is the logical arrangement of the filter dimension areas in the configuration interface, used to guide the configuration process of filter conditions. The pre-defined order can be reflected in spatial arrangement, such as from top to bottom, from left to right, or from center to outside, or it can be represented by visual elements such as serial numbers, color variations, or decreasing sizes.

[0056] Optionally, dragging filter criteria sequentially to each filter dimension area is an interactive workflow that requires users to place the filter criteria one by one into the corresponding dimension areas in a predetermined order as indicated by the interface. This approach first requires the system to provide clear visual guidance, such as using flashing borders, highlighting, or animations to indicate the dimension area that should be configured. During the operation, the system monitors the user's dragging behavior to ensure that the filter criteria are placed in the correct order. If the user attempts to skip a dimension area or configure it in the wrong order, the system can intervene through prompts or by preventing placement. Sequential dragging can be implemented using various interaction modes, such as traditional mouse drag and drop, finger swipes on a touchscreen, or keyboard shortcuts. To enhance the user experience, the system can provide real-time feedback during dragging, such as displaying the drag path, previewing the placement effect, or playing sound prompts. After configuring one dimension, the system may lock that dimension area to prevent subsequent accidental operations, while activating the next dimension area for continued configuration.

[0057] Optionally, configuring the corresponding filtering conditions for each filtering dimension region sequentially is an ordered configuration process, following a predefined dimension order to progressively complete the allocation of filtering conditions. Technically, the system maintains a filtering dimension queue and a configuration state manager, recording the configuration status and dependencies of each dimension region. After the user completes the configuration of the first dimension region, the system updates the data model and recalculates the filtering results for the second dimension region. This sequential configuration mechanism ensures that each subsequent dimension can be subdivided based on the filtering results of the previous dimension, forming a progressively layered data filtering structure. For example, when configuring resource management, if the user first configures "Resource Type = Iron Ore" in the first dimension region, the system will filter out all iron ore resources; then, if the user configures "Resource Level = High" in the second dimension region, the system will further filter out all high-level iron ore resources. This sequential configuration method not only aligns with user thinking habits but also optimizes the system's data processing flow, because each filtering step can be based on the result set of the previous step, without needing to rescan all the data.

[0058] In an optional implementation, composite filtering rules are determined based on the filtering conditions configured for each filtering dimension region. This includes establishing hierarchical composite filtering rules based on the filtering conditions and their configuration order for each filtering dimension region. In this way, by hierarchically combining the filtering conditions according to their configuration order, a composite filtering logic with a clear execution order is formed, ensuring the accuracy and consistency of the filtering results while improving filtering efficiency.

[0059] For example, after a user completes the filtering configuration, the system analyzes the order of the filtering dimension areas and the configured filtering conditions to construct a multi-level filtering rule tree. If the user configures the "resource type" condition in the first filtering dimension area, the "resource level" condition in the second filtering dimension area, and the "distance from the main city" condition in the third filtering dimension area, the system will create a three-level filtering rule. First, it filters all resources by type. Then, it further filters the different types of resources by resource level. Finally, it filters the different levels of resources under different types by distance from the main city, forming a progressive filtering process.

[0060] Optionally, a hierarchical composite filtering rule refers to a multi-level filtering logic formed by combining multiple filtering conditions in a specific order. Each filtering level is built upon the filtering results of the previous level, forming a progressive filtering process. In game resource management, this rule can ensure the accuracy and consistency of filtering results. For example, it can first group resources by type, then sort them by level within each group, and finally arrange them by distance within each level. The specific implementation of the rule can use a tree structure or a linked list structure to record each filtering condition and its sequential relationship.

[0061] Optionally, the configuration order refers to the order in which users set filter conditions for each filter dimension area. This order determines the execution flow of the composite filter rule and the application priority of each filter condition. The system will determine the order in which these conditions should be applied based on the arrangement order of the filter dimension areas and the filter conditions configured for each filter dimension area.

[0062] In an optional implementation, the data partitions displayed in each filtering dimension area correspond one-to-one with the composite filtering classification statistics results. The display size of each data partition is related to the number of data items contained in that partition, and the arrangement order of each data partition is determined based on the arrangement order of the data partitions in the previous filtering dimension area. In this way, through the visual presentation of data partitions, users can intuitively understand the impact of filtering conditions on data distribution. The size differences of the data partitions clearly show the proportional relationship of data volume under different categories, while the arrangement order based on the previous dimension ensures the logical coherence between data partitions, enabling users to easily track the flow and changes of data in the multi-dimensional filtering process.

[0063] For example, see Figure 4 When a user configures the "Resource Type" filter in the first filter dimension area, this area will display multiple data partitions, representing the statistical quantities of different resource types such as "Grain," "Timber," "Stone," and "Iron Ore," displayed as data partitions of corresponding sizes according to the proportion of each type. When a user configures the "Resource Level" filter in the second filter dimension area, this area will display the distribution of different levels of resources under each type in the order of resource types in the first area. For example, under the "Iron Ore" type, there are levels 10 and 11, with level 11 having a larger proportion. The size of the data partitions directly reflects the proportion of resources contained in each category, and the hierarchical relationship and data flow between the partitions are clearly displayed through visual elements such as color or connecting lines.

[0064] Optionally, data partitions are visual units used to visualize the distribution of data within a selected dimension area. They transform the statistical results of a dataset categorized according to specific filtering criteria into intuitive graphical interface elements. At the implementation level, data partitions can take various visual forms, such as rectangular blocks, bar charts, sector areas, or bubbles, with the appropriate representation chosen based on the interface design style and data characteristics. Each data partition typically contains several key visual attributes: shape defines the partition's basic appearance; size reflects the quantity or proportion of data contained within the partition; color can be used to distinguish different categories or represent data characteristics; labels display category names and data statistics; and boundary lines can enhance the visual separation between partitions. Data partitions are not only static display elements but can also have interactive functions, such as hovering to display detailed information, clicking to perform filtering operations, and dragging to adjust priorities.

[0065] Optionally, display size related to the number of data items means that the visual appearance of a partition on the interface is proportional to the actual amount of data it represents. In practice, this requires calculating the proportion of data in each category and then determining the partition's size parameters based on that proportion. In game resource filtering, this visual design helps players quickly grasp the distribution of resources, such as which types of resources are abundant and which levels of resources are scarce.

[0066] Optionally, the sorting order is determined based on the previous filter dimension region, meaning the partitioning order of the current dimension is inherited from the partitioning order of the previous dimension. This sequential inheritance maintains the consistency of the filtering logic, allowing users to track the flow of data across different filtering levels. The system needs to record the partitioning order of the previous dimension and apply the same sorting rules when generating the partitions for the current dimension. In game scenarios, this sequential consistency helps players understand the hierarchical relationships of composite filtering, such as the logical flow of grouping by type and then subdividing by level.

[0067] Optionally, the composite screening classification statistical result refers to the summary information obtained by the system classifying and counting data items according to the currently configured screening conditions. The statistical process includes steps such as data scanning, classification and grouping, and quantity calculation.

[0068] In an optional implementation, the filtering conditions include numerical filtering conditions, and the method further includes: responding to the user's interval division operation, dividing the numerical filtering conditions into multiple discrete interval filtering conditions; updating the composite filtering classification statistics of the data items based on the divided discrete interval filtering conditions; and displaying the data partitions in the filtering dimension area based on the updated composite filtering classification statistics. In this way, by converting continuous numerical data into discrete interval ranges, the problem of overly scattered data that may occur when filtering numerical data is solved, while providing a more meaningful data grouping method, allowing users to customize the division of numerical ranges according to actual needs, thus enhancing the flexibility and practicality of the filtering system.

[0069] For example, when a user drags the numerical filter "distance from the main city" to the filter dimension area, the system detects that this is a continuous numerical attribute and provides an interval division interface. The user can divide the distance value into multiple intervals, such as "0-100 meters", "101-300 meters", "301-500 meters" and "above 500 meters", by dragging the slider, entering a value, or selecting a preset range. The system then recalculates the resource distribution statistics based on these discrete intervals and generates corresponding data partitions in the filter dimension area. The size of each data partition intuitively represents the proportion of resources that meet the distance interval, allowing users to clearly understand the distribution of resources within different distance ranges and thus perform subsequent filtering operations more effectively. Optionally, numerical filtering criteria are a filtering method that processes continuous numerical attributes. They are used to filter or classify data items with quantifiable characteristics such as quantity, size, time, and distance. In multidimensional filtering systems, numerical filtering criteria differ from categorical filtering criteria, which typically handle discrete attributes with a limited number of options. The characteristics of numerical filtering criteria are that the data they process is continuous, comparable, and quantifiable.

[0071] Optionally, the interval division operation is an interactive process where users divide a continuous range of values ​​into multiple discrete segments, making the previously scattered numerical filtering more structured and manageable. In terms of user interface design, the interval division operation can be implemented through various interactive methods: users can drag interval separators to mark breakpoints on the number axis; they can directly enter interval boundary values ​​through input boxes; they can quickly create intervals using preset templates such as "equal distribution," "logarithmic distribution," or "custom"; and they can also visually determine interval boundaries through interactions on histograms or frequency distribution plots.

[0072] Optionally, discrete interval filtering conditions are a set of filtering rules formed by transforming a continuous numerical range into multiple intervals with clearly defined boundaries. Each interval represents an independent filtering category. This transformation process essentially discretizes continuous variables, making them more suitable for classification statistics and display. In technical implementation, each discrete interval is usually defined by upper and lower boundary values, such as [0,100], (100,300], etc., where square brackets and parentheses indicate whether the boundary values ​​are included or not, respectively.

[0073] Optionally, updating the composite filtering classification statistics is a data processing step. When the filtering conditions change, the system needs to recalculate and refresh the data classification statistics. After the interval division operation is completed, the data that might have been scattered across various discrete numerical points are now classified into a limited number of intervals. The system will perform statistical analysis on this reorganized data structure. Specifically, the system will traverse each item in the dataset, classify it according to all currently configured filtering conditions (including newly divided discrete intervals), and count the number of data items under each category combination. After the update process is complete, the system will trigger a UI refresh, passing the new statistical results to the visualization component for visual presentation.

[0074] In an optional implementation, composite filtering rules are applied to filter and display data items, including: responding to the user's confirmation and exiting the filtering configuration interface; sorting the data items step-by-step according to the hierarchical composite filtering rules; and displaying a list of data items based on the sorting results. In this way, by executing composite filtering rules in an orderly manner and presenting the final results, a complete process from configuration to application is achieved, ensuring the accuracy and consistency of the filtering results and improving the user experience.

[0075] For example, in game resource management, after the user completes the filter conditions for resource type, level and distance, they can click the confirmation button to exit the filter configuration interface. The system will then filter resources level by level in the order of type, level and distance, and finally display the sorted resource list on the list interface. For example, level 11 iron ore resources that are closest to the user will be listed first.

[0076] Optionally, the confirmation action refers to the interactive behavior that triggers the application of rules after the user completes the filtering configuration. This action is usually manifested as a button click, gesture, or voice command.

[0077] Optionally, exiting the filter configuration interface refers to the interface switching process from the configuration state to the data display state. The exit process needs to save the current configuration state, release related resources, and restore the display of the main interface.

[0078] Optionally, hierarchical filtering and sorting refers to a data processing process that applies filtering rules hierarchically according to the configured order of filtering conditions. Each level of filtering is based on the results of the previous level, forming a progressive data classification result.

[0079] Optionally, displaying a list of data items refers to an interface update operation that presents the final filtered results in a list format.

[0080] In an optional implementation, data items are filtered and sorted hierarchically according to a multi-level composite filtering rule. This includes filtering and sorting data items sequentially according to the configured order of the filtering conditions, where each filtering and sorting operation is based on the results of the previous filtering and classification. By executing multi-level filtering operations in an orderly manner, the hierarchical and coherent nature of the filtering logic is ensured, improving the accuracy and consistency of the filtering results while optimizing data processing efficiency.

[0081] For example, after a user completes the configuration of three filtering dimensions (such as selecting "Resource Type", "Resource Level" and "Distance from Main City" in sequence) and confirms the filtering, the system first filters and classifies all data items according to the first dimension "Resource Type", grouping resources by type; then, based on the results of the first filtering, the system continues to apply the filtering conditions of the second dimension "Resource Level", further subdividing each type of resource according to level; finally, based on the first two filterings, the system applies the condition of the third dimension "Distance from Main City", and sorts the resources in each level group according to distance, forming a three-level classification structure of type-level-distance, ultimately presenting the user with a list of resources that meet all filtering conditions and are arranged in the specified order.

[0082] Optionally, the configuration order refers to the order in which users add filter criteria to each filter dimension area, reflecting the hierarchical relationship of data filtering and classification.

[0083] Optionally, sequentially filtering and sorting data items is a method of processing data step-by-step according to a predetermined order. By applying multiple filtering conditions in succession, the original dataset is gradually refined into a result set that meets multiple conditions. This processing method constructs a filtering pipeline, where data starts from the initial complete set, passes through a series of filters, and finally produces results that meet all conditions.

[0084] Optionally, a continuous strategy in the multi-level filtering process can be adopted, based on the results of the previous filtering round. This ensures that each round of filtering is based on the result set of the previous round, rather than starting from the original data again. This chained processing model establishes dependencies between filtering steps, forming a directed graph structure for filtering. From a data flow perspective, the first filtering applies condition C1 to the original dataset A, producing an intermediate result set B; the second filtering applies condition C2 to B, producing a result set C; and so on, forming a processing chain of A→B→C→...

[0085] In an optional implementation, the data item is a virtual resource in the game, and the filtering criteria include at least one of the following: type, level, location information, and relative distance of the virtual resource. Thus, by applying a multi-dimensional filtering mechanism to game virtual resource management, refined classification and sorting of complex game resources are achieved, improving players' resource management efficiency and strategy formulation capabilities in the game.

[0086] For example, in the game resource filtering, users can choose to filter by multiple dimensions such as resource type (e.g., iron ore, wood), level (e.g., level 1-10), region (e.g., north, south), and distance from the main city (0-100 meters, 101-200 meters). The system will then accurately classify and sort the resources based on these conditions.

[0087] Optionally, virtual resources are interactive objects in a digital game environment, representing various elements within the game world that can be acquired, used, traded, or managed by players. In the context of strategy games, virtual resources typically include several categories: basic resources such as food, wood, iron ore, and oil, used for building construction and unit training; rare resources such as gems and special metals, used for advanced buildings and technology research; strategic resources such as territory and key locations, influencing players' expansion and strategic deployment in the game; and time-based resources such as building acceleration items and training acceleration items, used to shorten in-game progress waiting time. Each virtual resource in the system typically has a set of attributes, including basic information such as resource ID, name, icon, description text, acquisition method, and usage effect, as well as classification attributes such as type, level, rarity, location, and occupied space.

[0088] Optionally, type is a basic classification attribute of virtual resources, used to distinguish different types of in-game resources and establish a hierarchical management system for resources. Type is usually represented by predefined enumeration values ​​or a tag system. In game implementation, type conditions can support exact matching or fuzzy queries, such as filtering by resource category or subcategory.

[0089] Optionally, a level is a quantitative indicator that measures the value or strength of a virtual resource, usually expressed numerically, reflecting the resource's relative importance and rarity within the game system. In game design, a level system establishes a hierarchical structure for resources, allowing players to clearly judge the value differences between different resources. Level attributes are typically represented by discrete numerical values, such as levels 1-12, or descriptive labels, such as "common," "rare," and "legendary."

[0090] Optionally, using location information as a filter means filtering based on the spatial distribution of virtual resources in the game world. Location data may include absolute coordinates, regional divisions, or relative positional relationships. Location information is typically represented by a coordinate system, which can be two-dimensional coordinates (x, y) or three-dimensional coordinates (x, y, z), identifying the precise location of the resource on the game map.

[0091] Optionally, using relative distance as a filtering criterion means filtering based on the spatial distance between virtual resources and a reference point (such as the player's main city). Distance calculations may be based on Euclidean distance, Manhattan distance, or game-specific distance metrics. In the game implementation, distance filtering requires maintaining the location information of the reference point and efficiently calculating the relative distances between resource points. The handling of distance criteria can be optimized by combining spatial indexes, supporting range queries and nearest neighbor queries. The representation of distance data should consider the scale units and distance accuracy requirements of the game world.

[0092] In an optional implementation, the filtering dimension areas are presented as parallel tracks in the filtering configuration interface. This track-like layout visually displays the hierarchical relationship and execution flow of multi-dimensional filtering, improving interface comprehensibility and ease of operation, while also optimizing screen space utilization.

[0093] For example, in the filter configuration interface, the system presents the filter dimension areas in the form of multiple horizontally arranged parallel tracks. Each track represents a filter dimension, and users can drag and drop different filter conditions (such as resource type, level, distance, etc.) into these parallel tracks in sequence. When the first track is configured with the "resource type" filter condition, the track will display data partitions for different types of resources. Subsequently, when the second parallel track is configured with the "resource level" condition, the track will display the level distribution based on the filter results of the first track. This parallel track layout allows the filter results of each dimension to be presented in alignment in the same view, enabling users to intuitively track how data flows from one dimension to the next, forming a clear visual data filtering process.

[0094] Optionally, parallel tracks are an interface layout that arranges multiple filter dimensions in a parallel linear structure, forming a set of visually similar and spatially parallel interactive units. In terms of design implementation, parallel tracks have several key characteristics: each track typically uses a similar shape and size, such as rectangular areas of equal width, establishing a unified visual language; tracks maintain a certain spacing, forming clear visual separation, while visual elements such as background color, borders, or shadows reinforce the independence of each track; tracks can be arranged horizontally (from left to right) or vertically (from top to bottom), depending on the overall layout of the interface and the user's reading habits. At the interaction level, parallel tracks support multiple operation modes: drag and drop, allowing users to drag filter criteria to a specified track; click to select, allowing users to click on a track to activate it and then select the filter criteria to apply; and swipe to switch, allowing users to switch focus between tracks on touch devices. The visual design of the tracks can change according to their state: empty tracks can display prompts or dashed borders to guide users to add filter criteria; configured tracks display the current filter criteria and data partitions; active tracks may be highlighted to indicate that editing is in progress.

[0095] Corresponding to the above method embodiments, this invention provides an information processing device, see [link to previous document]. Figure 7The device includes: a filtering interface display module, used to respond to the user's multi-dimensional filtering instructions and display the filtering configuration interface of the data items, the filtering configuration interface including multiple filtering dimension areas and multiple filtering conditions; a filtering condition configuration module, used to respond to the user's operation of dragging filtering conditions to each filtering dimension area in sequence and configure the corresponding filtering conditions for each filtering dimension area; a rule determination module, used to determine the composite filtering rules based on the filtering conditions configured in each filtering dimension area; a filtering execution module, used to apply the composite filtering rules to filter and display the data items; and a data partition display module, used to display data partitions in each filtering dimension area, the data partitions being used to display in real time the statistical results of composite filtering and classification of data items based on the currently configured filtering conditions during the filtering condition configuration process.

[0096] In an optional implementation, the filtering interface display module includes: a list display unit for displaying a list of data items, the list display having multiple filtering conditions and multi-dimensional filtering controls; and an interface switching unit for displaying a filtering configuration interface in response to user operations on the multi-dimensional filtering controls.

[0097] In an optional implementation, the number of filter dimension regions is the same as the number of filter conditions.

[0098] In an optional implementation, the filter dimension areas are arranged in a predetermined order, and the filter condition configuration module includes: a sequence configuration unit, used to respond to the user dragging the filter conditions to each filter dimension area in a predetermined order, and to configure the corresponding filter conditions for each filter dimension area in sequence.

[0099] In an optional implementation, the rule determination module includes a rule establishment unit, used to establish hierarchical composite filtering rules based on the filtering conditions and configuration order configured for each filtering dimension region.

[0100] In an optional implementation, the data partition display module includes: a partition correspondence unit, used to make each data partition correspond one-to-one with the composite screening classification statistical results; a size adjustment unit, used to adjust the display size of each data partition according to the number of data items contained in each data partition; and an order determination unit, used to determine the arrangement order of each data partition in the current screening dimension region based on the arrangement order of each data partition in the previous screening dimension region.

[0101] In an optional implementation, the filtering conditions include numerical filtering conditions, and the device further includes: an interval division module, used to respond to the user's interval division operation and divide the numerical filtering conditions into multiple discrete interval filtering conditions; a statistical update module, used to update the composite filtering classification statistical results of the data items based on the divided discrete interval filtering conditions; and a partition update module, used to display the data partitions in the filtering dimension area based on the updated composite filtering classification statistical results.

[0102] In an optional implementation, the filtering execution module includes: an interface exit unit, used to respond to the user's confirmation operation and exit the filtering configuration interface; a step-by-step filtering unit, used to filter and sort the data items step-by-step according to the step-by-step composite filtering rules; and a result display unit, used to display a list of data items according to the sorting results.

[0103] In an optional implementation, the step-by-step filtering unit includes a sequential filtering subunit, used to sequentially filter and sort data items according to the configured order of the filtering conditions, wherein each filtering and sorting is performed based on the previous filtering and classification results.

[0104] In an optional implementation, the data item is a virtual resource in the game, and the filtering criteria include at least one of the following: type, level, location information, and relative distance of the virtual resource.

[0105] In an optional implementation, the filtering dimension regions are presented as parallel tracks in the filtering configuration interface.

[0106] The information processing apparatus provided in this disclosure has the same implementation principle and technical effects as the aforementioned method embodiments. For the sake of brevity, any parts not mentioned in the apparatus embodiments can be referred to the corresponding content in the aforementioned method embodiments.

[0107] It should be noted that although several units / modules or sub-units / modules of the device have been mentioned in the detailed description above, this division is merely exemplary and not mandatory. In fact, according to embodiments of the present invention, the features and functions of two or more units / modules described above can be embodied in one unit / module. Conversely, the features and functions of one unit / module described above can be further divided and embodied by multiple units / modules.

[0108] This invention also provides an electronic device, such as... Figure 8 As shown, the electronic device includes a processor and a memory. The memory stores computer-executable instructions that can be executed by the processor. The processor executes the computer-executable instructions to implement any information processing method of the embodiments of this disclosure. For specific implementation methods and the resulting technical effects, please refer to the method embodiments, which will not be repeated here.

[0109] Figure 8This is a schematic diagram of the structure of an electronic device. The electronic device 1100 includes a processor 1101 with one or more processing cores, a memory 1102 with one or more computer-readable storage media, and a computer program stored in the memory 1102 and executable on the processor. The processor 1101 and the memory 1102 are electrically connected. Those skilled in the art will understand that the electronic device structure shown in the figure does not constitute a limitation on the electronic device, and may include more or fewer components than shown, or combine certain components, or have different component arrangements.

[0110] The processor 1101 is the control center of the electronic device 1100. It connects various parts of the electronic device 1100 through various interfaces and lines. By running or loading software programs and / or modules stored in the memory 1102, and calling data stored in the memory 1102, it executes various functions of the electronic device 1100 and processes data, thereby performing overall monitoring of the electronic device 1100.

[0111] Optionally, the electronic device 1100 further includes: a touch display screen 1103, a radio frequency circuit 1104, an audio circuit 1105, an input unit 1106, and a power supply 1107. The processor 1101 is electrically connected to the touch display screen 1103, the radio frequency circuit 1104, the audio circuit 1105, the input unit 1106, and the power supply 1107. Those skilled in the art will understand that... Figure 8 The electronic device structure shown does not constitute a limitation on the electronic device and may include more or fewer components than shown, or combine certain components, or have different component arrangements.

[0112] This invention also provides a computer-readable storage medium storing a computer program, wherein the computer program is configured to execute any information processing method of this disclosure embodiment when run by a processor. For specific implementation methods and the resulting technical effects, please refer to the method embodiments, which will not be repeated here.

[0113] If the aforementioned functions are implemented as software functional units and sold or used as independent products, they can be stored in a computer-readable storage medium. Based on this understanding, the technical solution of this invention, essentially, or the part that contributes to the prior art, or a portion of the technical solution, can be embodied in the form of a software product. This computer software product is stored in a storage medium and includes several instructions to cause a computer device (which may be a personal computer, a terminal device, or a network device, etc.) to execute all or part of the steps of the methods described in the various embodiments of this invention. The aforementioned storage medium includes various media capable of storing program code, such as USB flash drives, portable hard drives, read-only memory (ROM), random access memory (RAM), magnetic disks, or optical disks.

[0114] In the description of this invention, it should be noted that the terms "center," "upper," "lower," "left," "right," "vertical," "horizontal," "inner," and "outer," etc., indicate the orientation or positional relationship based on the orientation or positional relationship shown in the accompanying drawings. They are used only for the convenience of describing the invention and for simplifying the description, and do not indicate or imply that the device or element referred to must have a specific orientation, or be constructed and operated in a specific orientation. Therefore, they should not be construed as limitations on the invention. Furthermore, the terms "first," "second," and "third" are used for descriptive purposes only and should not be construed as indicating or implying relative importance.

[0115] Finally, it should be noted that the above-described embodiments are merely specific implementations of the present invention, used to illustrate the technical solutions of the present invention, and not to limit it. The scope of protection of the present invention is not limited thereto. Although the present invention has been described in detail with reference to the foregoing embodiments, those skilled in the art should understand that any person skilled in the art can still modify or easily conceive of changes to the technical solutions described in the foregoing embodiments within the technical scope disclosed in the present invention, or make equivalent substitutions for some of the technical features; and these modifications, changes, or substitutions do not cause the essence of the corresponding technical solutions to deviate from the spirit and scope of the technical solutions of the embodiments of the present invention, and should all be covered within the scope of protection of the present invention. Therefore, the scope of protection of the present invention should be determined by the scope of the claims.

Claims

1. An information processing method, characterized in that, The method includes: In response to the user's multi-dimensional filtering command, the filtering configuration interface of the data item is displayed, which includes multiple filtering dimension areas and multiple filtering conditions; In response to the user's operation of dragging the filter criteria to each filter dimension area in sequence, configure the corresponding filter criteria for each filter dimension area; Based on the filtering conditions configured for each filtering dimension region, determine the composite filtering rules; The data items are filtered and displayed using the composite filtering rules described above; Each filtering dimension area displays data partitions, which are used to display statistical results of composite filtering and classification of the data items based on the currently configured filtering conditions in real time during the filtering condition configuration process.

2. The method according to claim 1, characterized in that, The response to the user's multi-dimensional filtering command, displaying the data item filtering configuration interface, includes: The list interface displays data items, and the list interface displays multiple filter conditions and multi-dimensional filter controls; In response to the user's operation on the multidimensional filter control, the filter configuration interface is displayed.

3. The method according to claim 1, characterized in that, The number of filtering dimension regions is the same as the number of filtering conditions.

4. The method according to claim 1, characterized in that, The filter dimension areas are arranged in a predetermined order. The step of configuring corresponding filter conditions for each filter dimension area in response to the user's operation of dragging filter conditions sequentially to each filter dimension area includes: In response to the user dragging the filter criteria to each filter dimension area in the predetermined order, the corresponding filter criteria are configured for each filter dimension area in sequence.

5. The method according to claim 4, characterized in that, The step of determining the composite filtering rules based on the filtering conditions configured for each filtering dimension region includes: Based on the filtering conditions and configuration order configured for each filtering dimension area, establish a hierarchical composite filtering rule.

6. The method according to claim 1, characterized in that, The data partitions displayed in each filtering dimension area correspond one-to-one with the composite filtering classification statistics results. The display size of each data partition is related to the number of data items contained in that partition. The arrangement order of each data partition is determined based on the arrangement order of each data partition in the previous filtering dimension area.

7. The method according to claim 6, characterized in that, The filtering criteria include numerical filtering criteria, and the method further includes: In response to the user's interval division operation, the numerical filtering conditions are divided into multiple discrete interval filtering conditions; The composite screening classification statistics of the data items are updated based on the screening conditions of the divided discrete intervals; Based on the updated composite screening classification statistics, data partitions are displayed in the screening dimension area.

8. The method according to claim 5, characterized in that, The process of applying the composite filtering rules to filter and display the data items includes: In response to the user's confirmation, exit the filter configuration interface; According to the aforementioned hierarchical composite filtering rules, the data items are filtered and sorted hierarchically. Based on the sorting results, the list of data items is displayed.

9. The method according to claim 8, characterized in that, The step of filtering and sorting the data items according to the step-by-step composite filtering rules includes: The data items are filtered and sorted sequentially according to the configured order of the filtering conditions, wherein each filtering and sorting is performed based on the filtering and classification results of the previous time.

10. The method according to claim 1, characterized in that, The data item is a virtual resource in the game, and the filtering criteria include at least one of the following: type, level, location information, and relative distance of the virtual resource.

11. The method according to claim 1, characterized in that, The filtering dimension areas are presented as parallel tracks in the filtering configuration interface.

12. An information processing device, characterized in that, The device includes: The filtering interface display module is used to respond to the user's multi-dimensional filtering instructions and display the filtering configuration interface of the data items. The filtering configuration interface includes multiple filtering dimension areas and multiple filtering conditions. The filter configuration module is used to respond to the user's operation of dragging filter conditions to each filter dimension area in sequence, and to configure the corresponding filter conditions for each filter dimension area. The rule determination module is used to determine composite filtering rules based on the filtering conditions configured in each filtering dimension region; The filtering execution module is used to apply the composite filtering rules to filter and display the data items; The data partition display module is used to display data partitions in each filter dimension area. The data partitions are used to display in real time the statistical results of composite filtering and classification of the data items based on the currently configured filter conditions during the filter condition configuration process.

13. An electronic device, characterized in that, include: Memory stores computer-executable instructions that can be executed by a processor; A processor for executing the computer-executable instructions to implement the method as claimed in any one of claims 1-11.

14. A computer-readable storage medium, characterized in that, The device contains a computer program that, when executed by a processor, implements the method as described in any one of claims 1-11.

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