CN115357321A - Automatic generation method and system for icon visualization - Google Patents

Abstract

The invention discloses an automatic generation method and system of icon visualization, which comprises the following steps: the receiving module is used for receiving data which are uploaded by a user and need to be visualized by icons; the metaphor image searching and processing module is used for searching a series of metaphor images for the received data according to metaphor image standards, deconstructing and processing the metaphor images to obtain visual elements and form a visual element list; the binding and drawing module is used for binding the received data with the visual elements in the visual element list, endowing the bound visual elements with coding properties according to the data types, and drawing the visual elements according to the coding properties to obtain metaphor-based icon visualization; and the editing module is used for providing an editing interface for a user, receiving the editing data of the user and drawing and generating a metaphor-based new icon visualization according to the editing data. The system and method enable automatic generation of metaphor-based icon visualizations.

Description

Automatic generation method and system for icon visualization

Technical Field

The invention belongs to the technical field of multi-dimensional data visualization design, and particularly relates to an automatic generation method and system for icon visualization.

Background

In the visualization of multidimensional data, icons are widely used. However, too many data dimensions can lead to too complex design of the icon, which in turn leads to an understanding problem of icon visualization. Researchers have attempted to use visual metaphors to aid understanding in that data-dependent, representative appearances are used to draw icons. Visual metaphors have been widely used in many areas, such as sports, urban applications, blockchains, and the like. Relevant studies have shown that suitable metaphors can help people to understand icons more quickly and accurately.

However, it is not easy to design and use metaphors in icons, and researchers must balance various factors such as expressiveness of visual representation and validity of data mapping. There are currently partial visualization authoring tools that can help create icon-based visualizations. However, most tools are difficult to balance between automation and customization during a particular build process. Some tools only consider basic geometric shapes or limited shapes and do not support the metaphor for creating icons. Some authoring tools are more customizable in that they support users making graphical elements from scratch by way of sketching or interacting, however creating graphical elements from scratch has some difficulty and the quality of the final icon is highly dependent on the user's design experience and expertise. Some tools reduce customization costs and simplify the authoring process by introducing online resources. However, excessive image design is prone to user confusion and may affect the final creation.

Based on the above background, researchers wish to utilize online resources to automatically generate metaphor-based visualizations of icons to assist ordinary users who are not designers or visualization experts in encoding multidimensional data.

However, researchers need to address two difficulties: the difficulty is how to design metaphors into the icon visualization. At present, a great number of visualizations use metaphors to help data expression, and existing researches have proved that the metaphors can be used for promoting the understanding of icons and are effective design strategies. However, there is currently a lack of a systematic investigation into such designs to guide the creation of metaphor-based visualizations of icons.

The second difficulty is the difficulty in automating the design process. The design process comprises a series of design decisions, such as selecting a proper metaphor design and binding data with various elements in the metaphor, the whole process needs to be considered comprehensively, and the current automatic method for designing and generating metaphor-based icon visualization does not receive much attention.

Disclosure of Invention

In view of the above, it is an object of the present invention to provide a method and system for automatic generation of icon visualizations by finding suitable metaphorical pictures as materials in a network and mapping data into different visual elements of the graph according to the degree of matching.

To achieve the above object, an embodiment of the present invention provides an automatic generation system for icon visualization, including:

the receiving module is used for receiving data which are uploaded by a user and need to be visualized by icons;

the metaphor picture searching and processing module is used for searching a series of metaphor pictures for the received data according to metaphor picture standards, deconstructing and processing the metaphor pictures to obtain visual elements and form a visual element list;

the binding and drawing module is used for binding the received data with the visual elements in the visual element list, endowing the bound visual elements with coding properties according to the data types, and drawing the visual elements according to the coding properties to obtain metaphor-based icon visualization;

and the editing module is used for providing an editing interface for a user, receiving the editing data of the user and drawing and generating a metaphor-based new icon visualization according to the editing data.

Preferably, the received data to be visualized by the icon is represented in a table form, wherein a table name represents a subject, each column in the table represents each specific data dimension, and a column name is understood as a subject of the data dimension.

Preferably, the metaphors picture criteria is determined by analyzing existing metaphors-based icon visualizations, including:

firstly, analyzing the existing metaphor-based icon visualization to obtain a design rule, wherein the design rule comprises the following steps: the method comprises the following steps of considering metaphors and icon placement types from the overall design, wherein the metaphors comprise semantic relevance indicating that the metaphors are related to data topics and structural relevance indicating that the metaphors are related to data structures, and the icon placement types comprise: data drivers indicating that the position of the icon is associated with a particular numerical value, structure drivers indicating that the data has a structural characteristic; considering the icon layout types from a single icon, the icon layout types including radial and non-radial; considering visual element classifications from the visual elements in the icons, the visual element classifications including shapes and charts;

then, determining a metaphor picture standard according to a design rule as follows: vector images that are semantically related to the data and are simple in structure.

Preferably, deconstructing and processing the metaphorical picture to derive the visual elements comprises:

dividing a single metaphor into a plurality of visual elements, screening the visual elements to remove the visual elements with the image area smaller than a set threshold value, determining the layout type of the metaphor picture to be radial or non-radial according to the remaining visual elements, forming a visual element list by the remaining visual elements, and recording

The type of layout of the visual elements in the icon.

Preferably, the binding the received data with the visual elements in the visual element list includes:

the visual elements are used as nodes, a Monte Carlo search tree is adopted to search the visual elements so as to determine a visual element set corresponding to a path with the highest reward value as an optimal data mapping space, and the received data and the visual elements are bound according to the optimal data mapping space;

when the Monte Carlo search tree is adopted to search the visual elements, the reward values of the nodes are updated according to the importance of the data attributes, the semantic correlation between the data attributes and the visual elements and the overlapping degree of the visual elements, and after the search is finished, the average value of the reward values of all the nodes in a single path is used as the reward value of the path.

Preferably, the editing data comprises a visual element and/or a coding attribute, and the personalized design of the visualization of the new icon is realized by modifying the coding attribute of the visual element and/or the visual element, wherein the coding attribute comprises color, numerical value size, transparency, quantity and rotation angle.

In order to achieve the above object, an embodiment provides an automatic icon visualization generating method, where the method applies the above system, and the method includes the following steps:

receiving data which needs icon visualization and is uploaded by a user by using a receiving module;

searching a series of metaphor pictures for received data by using a metaphor picture searching and processing module according to metaphor picture standards, deconstructing and processing the metaphor pictures to obtain visual elements, and forming a visual element list;

binding the received data with visual elements in the visual element list by using a binding and drawing module, endowing the bound visual elements with coding attributes according to the data types, and drawing the visual elements according to the coding attributes to obtain metaphor-based icon visualization;

and receiving the editing data of a user by using an editing interface provided by the editing module, and drawing and generating a metaphor-based new icon visualization according to the editing data.

Compared with the prior art, the invention has the beneficial effects that at least:

(1) Automated icon design simultaneously uses semantically related metaphor-based design. Metaphors are widely used in the field of visualization, and can link data semantics with topics. The invention aims to automatically generate icons and ensure that the visual elements thereof are semantically associated with metaphorical graphics.

(2) Balancing the effectiveness of design expressiveness and perception. The increase in data dimensionality can lead to more complex metaphor-based icon designs and thus to comprehension problems. Some of the visual elements in the metaphorical graphic are suitable for encoding data attributes, while some are more suitable for decorative purposes. The invention balances the encoding data dimensionality and visual elements with the perception constraint.

(3) Providing design inspiration. Given metaphors selection and visual mapping, the design space for metaphors-based icon visualization can be very large and it is not possible for designers to try all alternatives. Designers prefer to start with the designs they are accustomed to, rather, the machine enumerates all the possibilities and may accidentally create new designs, thereby providing the designer with new design inspiration.

Drawings

In order to more clearly illustrate the embodiments of the present invention or the technical solutions in the prior art, the drawings used in the embodiments or the description of the prior art will be briefly described below, it is obvious that the drawings in the following description are only some embodiments of the present invention, and it is obvious for those skilled in the art that other drawings can be obtained according to these drawings without creative efforts.

FIG. 1 is a schematic structural diagram of an automatic generation system for an icon visualization provided by an embodiment;

FIG. 2 is an interface diagram of an automatic generation system for icon visualizations provided by an embodiment;

FIG. 3 is a flow diagram for exploration using a Monte Carlo search tree, provided by an embodiment;

FIG. 4 is a flowchart of an automatic generation method of an icon visualization provided by an embodiment.

Detailed Description

In order to make the objects, technical solutions and advantages of the present invention more apparent, the present invention will be further described in detail with reference to the accompanying drawings and examples. It should be understood that the detailed description and specific examples, while indicating the scope of the invention, are intended for purposes of illustration only and are not intended to limit the scope of the invention.

Fig. 1 is a schematic structural diagram of an automatic generation system of an icon visualization provided by an embodiment. FIG. 2 is an interface diagram of an automatic generation system for icon visualizations, according to an embodiment. As shown in fig. 1 and 2, the embodiment provides an automatic generation system of icon visualization, which includes a receiving module, a metaphor picture searching and processing module, a binding and drawing module, and an editing module.

The receiving module is used for receiving data which is uploaded by a user and needs icon visualization. In an embodiment, data to be visualized by an icon is represented in a table form, where a table name represents a data topic, each column in the table represents each specific data dimension, and a column name may be understood as a topic of a data dimension. For example, for hamburger type data, the data subject is hamburger, and the information of each dimension of the data comprises the type of the hamburger, the composition of the hamburger such as bacon, chicken leg and the like, the price of the hamburger, the size of the hamburger and the like.

The metaphor picture searching and processing module is used for searching a series of metaphor pictures for the received data according to metaphor picture standards, deconstructing and processing the metaphor pictures to obtain visual elements and form a visual element list.

In an embodiment, the metaphors picture criteria is determined by analyzing existing metaphors-based icon visualizations, including: first, the existing metaphor-based icon visualization is analyzed to obtain a design rule, which provides guidance for automated design. Then, determining a metaphor picture standard according to the design rule obtained by analysis as follows: vector images that are semantically related to the data and are simple in structure.

Specifically, analyzing existing metaphor-based iconic visualizations includes: stage one: focusing on the overall design, it is known to the designer how to design metaphors into the visualization, and how to place all icons in the visualization. There are two categories of metaphor types: semantic correlation and structural correlation. The former indicates that metaphors are related to data topics, and designers often use metaphors in specific individual icon designs. The latter representation metaphors are related to the data structure, in which case the metaphors are primarily embodied in the visualization layout. The part of the design simultaneously satisfies semantic correlation and structural correlation. There are two categories in icon placement: data driving and structure driving. The position of the data-driven presentation icon is associated with a particular numerical value. Such icons are typically placed in a cartesian coordinate system, and certain numerical values may be used directly as x-values or y-values. The structure driver indicates that the data has a structural feature. Designers prefer to employ metaphors in structure-driven icons, such as using maps and clocks;

and in the second stage, the design of specific icons is focused, and the layout of the icons is focused. The layout of the icons is divided into two categories: radial and non-radial. A radial icon is an icon placed on a polar coordinate system. Each element shares the origin of the coordinate system and is associated with a circle. The icons in the non-radial layout may be placed in a cartesian coordinate system.

And stage three, focusing on visual elements in the icons. Visual elements in icons are divided into two categories: shapes and diagrams. Shape level elements refer to different shapes, including basic geometric shapes (e.g., circles, polygons) and complex shapes (e.g., leaves). Chart level elements are variant charts in icons that may convey more information. Designers mainly use pie charts, circle charts, star charts, heatmaps, and box charts. The information conveyed by an icon is limited, with metaphors encoding elements ranging in number from 2 to 6 elements.

The metaphor picture standard is embedded in the system, when data needing icon visualization is received, the metaphor picture searching and processing module searches a series of metaphor pictures for the received data according to the metaphor picture standard, deconstructs and processes the metaphor pictures to obtain visual elements, and forms a visual element list.

In an embodiment, deconstructing and processing the metaphorical picture to derive visual elements includes: firstly, a single metaphor is divided into a plurality of visual elements, each path in the SVG file is converted into an independent SVG file, each file is a visual element, then, the visual elements are screened, unnecessary visual elements with image areas smaller than a set threshold value are removed, the set threshold value can be 0.5% of the area of a metaphor picture, next, the layout type of the metaphor picture is determined to be radial or non-radial according to the remaining necessary visual elements, and finally, the remaining visual elements form a visual element list and the layout type of the visual elements in the icon is recorded.

The binding and drawing module is used for binding the received data with the visual elements in the visual element list, endowing the bound visual elements with coding properties according to the data types, and drawing the visual elements according to the coding properties to obtain metaphor-based icon visualization.

In an embodiment, the input data has fixed dimensions, each dimension has corresponding data attributes, including numerical type and category type, the number in the element list is fixed, but not all data need to be displayed in the final icon visualization. Thus, the data mapping space is explored by constructing a Monte Carlo search tree, where each node of the tree is a particular visual element in the list of visual elements, and the height of the tree corresponds to a particular data dimension. According to the method, all data dimensions need to be ranked according to importance, the evaluation index is the relevance between the evaluation index and the data theme, and specifically, the data dimensions are ranked by calculating the cosine distance between the data dimension description and the data theme.

In the embodiment, the Monte Carlo search tree is adopted to search the visual elements so as to determine the visual element set corresponding to the path with the highest reward value as the optimal data mapping space, and the received data and the visual elements are bound according to the optimal data mapping space. The tree is first initialized with an empty root node. Next, specifically, as shown in fig. 3, the search process is divided into the following four stages:

stage one: and (4) selecting. The goal of the selection phase is to find the most appropriate element node. This step starts with the root node and selects a child node with the highest confidence cap each time, taking into account the balance between nodes with lower access and nodes with higher access. The selection phase ends when the most urgent scalable node is accessed. If a node is not visited (i.e., not expanded), then the node is an expandable leaf node.

And stage two, expanding. The tree is expanded by adding a child node, embodied by adding a random visual element, and initializing the number of visits and rewards to zero. It is noted that if this data dimension is not shown in the visualization, it appears as adding a null node.

And step three, simulation. The simulation process starts with a new node and expands by randomly and quickly selecting a node until it cannot expand to produce a result. For faster simulation, this phase does not pursue high payback, but rather seeks to simulate more times in a limited time to obtain a high prize.

And step four, backtracking. The results of the simulation are used to trace back to update the selected nodes, with new nodes being added to the tree after updating the reward value and gaining access time. If other visited nodes have a larger reward value, the reward value needs to be updated and one access time needs to be increased.

And ending one cycle after the fourth stage is ended, and returning to the first stage again to continue a new cycle. The search process will return to the selection phase or terminate when the time limit is exceeded or the search tree is exhausted.

In the embodiment, when the Monte Carlo search tree is adopted to search the visual elements, the reward values of the nodes are updated according to the importance of the data attributes, the semantic correlation between the data attributes and the visual elements and the overlapping degree of the visual elements, after the search is finished, the average value of the reward values of all the nodes in a single path is used as the reward value of the path, and the path with the highest reward value is determined as the optimal mapping space.

During the search process, the reward system is calculated through three aspect criteria, so as to evaluate the quality of the final icon visualization. Wherein the importance score is used to estimate the importance of a data attribute. The importance scores in the data dimension ordering process are normalized to serve as final importance scores, and therefore feasibility of the model is guaranteed. Specifically, the calculation process of the importance score includes: and acquiring the theme of the data from the title of the table, acquiring the description of each data dimension from the column name of each dimension of the data, calculating the semantic relevance of the two texts, and performing normalization processing.

The semantic relevance of the data attribute and the visual element is used for evaluating the semantic relevance between the visual element and one data attribute, and the specific calculation is as follows: obtaining a thermodynamic diagram according to the description of each data dimension of the data and the metaphorical picture, wherein each point of the thermodynamic diagram corresponds to the correlation between each point and the theme in the metaphorical picture; for a given visual element, calculating the correlation mean value of all pixel points where the given visual element is located, namely the semantic correlation between the given visual element and the data attribute.

The overlap score is used for evaluating the overlap degree between all visual elements of the final icon visualization, and the specific calculation is as follows: and calculating to obtain the overlapping area among the visual elements, wherein if the overlapping area exceeds 30% of the whole icon visualization bounding box, the overlapping area is too large, the overlapping degree is 0, and otherwise, the overlapping area is 1.

And calculating the product of the importance and the semantic relevance of each node aiming at a single path, wherein the overlapping degree obtained by multiplying the accumulated average value of all the nodes by the path is the final reward value of the path.

After the data attributes and the visual elements are bound through the optimal mapping space, coding attributes are given to the bound visual elements according to the data types, and the visual elements are drawn according to the coding attributes so as to obtain metaphor-based icon visualization. In an embodiment, the encoding attribute includes color, numerical value size, transparency, number, and rotation angle, and when the data attribute is a numerical value type, the assigned encoding attribute is the numerical value size, and when the data attribute is an image type, the assigned encoding attribute is color, and the like.

The editing module is used for previewing the metaphor-based icon visualization, providing an editing interface for a user, receiving editing data of the user and drawing and generating a metaphor-based new icon visualization according to the editing data. The editing data comprises the bound visual elements and/or the coding properties, and the personalized design of the visualization of the new icon is realized by modifying the visual elements and/or the coding properties of the visual elements.

The automatic generation system of icon visualization provided by the embodiment mainly considers the following three points in the design:

the semantics are related. Reasonable metaphor-based iconic visualization can facilitate interpretation of data. Thus, data semantics are crucial for selecting an appropriate metaphor design, while taking into account the rationality of the mapping between particular data dimensions and individual visual elements.

Automatic and efficient generation is supported. On-line picture resources may provide design inspiration, however, it is difficult for a designer to select an appropriate metaphor image from a large number of on-line resources. Meanwhile, manual data mapping is time-consuming and labor-consuming, because the user needs to calculate different attributes (i.e., size and angle) for encoding. A simplified way is to automate the process, including in image selection and data mapping. Meanwhile, the automated process needs to be efficient and fast, and therefore a plurality of filtering conditions need to be set in different steps, so that the finally generated visualization can be balanced between quality and efficiency.

And (4) a man-machine cooperation workflow. Although automated systems provide convenience, the generated visualization may not meet the user's expectations. Therefore, the user should participate in the creation process. The system provides some preliminary results for the user to select and modify, and then the user can modify the system for a specific data dimension, and the system can update, providing an alternative according to the user's preference.

Based on the same inventive concept, as shown in fig. 4, the embodiment further provides an automatic icon visualization generation method, which applies the system and includes the following steps:

step 1, receiving data which needs icon visualization and is uploaded by a user by using a receiving module;

step 2, searching a series of metaphor pictures for the received data by using a metaphor picture searching and processing module according to metaphor picture standards, deconstructing and processing the metaphor pictures to obtain visual elements, and forming a visual element list;

step 3, binding the received data and the visual elements in the visual element list by using a binding and drawing module, endowing the bound visual elements with coding properties according to the data types, and drawing the visual elements according to the coding properties to obtain metaphor-based icon visualization;

and 4, receiving the editing data of the user by using an editing interface provided by the editing module, and drawing and generating a metaphor-based new icon visualization according to the editing data.

As shown in fig. 2, the specific process of designing by using the automatic generation system for icon visualization is as follows:

first, a data form is uploaded in a data menu bar as input. The next step (triggering the metaphor module) is performed after clicking the generate button. The system automatically generates the initial several icon visualizations from the data, which are displayed in the preview view and the candidate list view (triggering the binding and rendering module). Wherein the icon visualization in the preview view is the option with the highest score after the system has computed. The edit view provides a small panel for each data dimension, each small panel corresponding to the detailed information for that data dimension, including the title of the column of data, the type of data, the elements of the map, and the corresponding encoding channel. The different data dimensions are ranked according to importance scores. The user can modify the mapping relationship of the data by pulling down the menu bar. After clicking the update button, the system will recalculate and create a new icon visualization based on the user's input. Finally, the user can click the export button to export the designed visual file for further creation.

According to the system and the method provided by the embodiment, given table data, the metaphor-based icon visualization can be automatically generated according to the characteristics of the data and semantic information, so that a user can understand the data in a more intuitive mode. The method takes data importance and semantic relevance into consideration to select the metaphor graph and map visual elements in the graph to data, and meanwhile the system supports editing of interactive mapping relations of icon visualization to meet different design requirements.

The above-mentioned embodiments are intended to illustrate the technical solutions and advantages of the present invention, and it should be understood that the above-mentioned embodiments are only the most preferred embodiments of the present invention, and are not intended to limit the present invention, and any modifications, additions, equivalents, etc. made within the scope of the principles of the present invention should be included in the scope of the present invention.

Claims (8)

1. An automatic generation system for icon visualization, comprising:

the receiving module is used for receiving data which are uploaded by a user and need to be visualized by icons;

the metaphor image searching and processing module is used for searching a series of metaphor images for the received data according to metaphor image standards, deconstructing and processing the metaphor images to obtain visual elements and form a visual element list;

the binding and drawing module is used for binding the received data with the visual elements in the visual element list, endowing the bound visual elements with coding properties according to the data types, and drawing the visual elements according to the coding properties to obtain metaphor-based icon visualization;

and the editing module is used for providing an editing interface for a user, receiving the editing data of the user and drawing and generating a metaphor-based new icon visualization according to the editing data.

2. The system of claim 1, wherein the received data to be visualized is represented in a table format, wherein a table name represents a data topic, each column in the table represents each data dimension, and a column name is understood as a topic of the data dimension.

3. The automatic generation system of an iconic visualization of claim 1, wherein the metaphorical picture criteria is determined by analyzing existing metaphorical-based iconic visualizations, comprising:

firstly, analyzing the existing metaphor-based icon visualization to obtain a design rule, wherein the design rule comprises the following steps: considering metaphors types and icon placement types from the overall design, wherein metaphors types include semantic relevance indicating that metaphors are related to data subject, structural relevance indicating that metaphors are related to data structure, and icon placement types include: data drivers indicating that the position of the icon is associated with a particular numerical value, structure drivers indicating that the data has a structural characteristic; considering the icon layout types from a single icon, the icon layout types including radial and non-radial; considering visual element classifications from the visual elements in the icons, the visual element classifications including shapes and charts;

then, determining the metaphor picture standard according to the design rule as follows: vector images that are semantically related to data and are simple in structure.

4. The system for automatically generating an iconic visualization according to claim 1, wherein the deconstructing and processing metaphorical pictures for visual elements comprises:

the method comprises the steps of dividing a single metaphor into a plurality of visual elements, screening the visual elements to remove the visual elements with the image area smaller than a set threshold value, determining the layout type of a metaphor picture to be radial or non-radial according to the remaining visual elements, forming a visual element list by the remaining visual elements, and recording the layout type of the visual elements in icons.

5. The system for automatically generating an icon visualization according to claim 1, wherein the binding of the received data with the visual elements in the list of visual elements comprises:

taking the visual elements as nodes, searching the visual elements by adopting a Monte Carlo search tree to determine a visual element set corresponding to a path with the highest reward value as an optimal data mapping space, and binding the received data and the visual elements according to the optimal data mapping space;

when the Monte Carlo search tree is adopted to search the visual elements, the reward values of the nodes are updated according to the importance of the data attributes, the semantic relevance of the visual elements of the data attributes and the overlapping degree of the visual elements, and after the search is finished, the average value of the reward values of all the nodes in a single path is used as the reward value of the path.

6. The system of claim 5, wherein the computing of the importance of the data attributes comprises: and acquiring the theme of the data from the title of the table, acquiring the description of each data dimension from the column name of each dimension of the data, calculating the semantic relevance of the two texts, and performing normalization processing.

The calculation of the semantic relevance of the data attributes to the visual elements includes: the method comprises the steps of obtaining description of data dimensions according to column names of each dimension of data and metaphoric pictures, obtaining a thermodynamic diagram according to the metaphoric pictures, wherein each point of the thermodynamic diagram corresponds to the correlation between each point and a theme in the metaphoric pictures, and calculating the mean value of the correlations of all pixel points where a given visual element is located, namely the semantic correlation between the visual element and data attributes.

The calculation of the degree of overlap of the visual elements comprises: calculating to obtain the overlapping area among the visual elements, if the overlapping area exceeds 30% of the whole icon visual bounding box, the overlapping area is too large, the overlapping degree is 0, otherwise, the overlapping area is 1;

and calculating the product of the importance and the semantic relevance of each node aiming at a single path, wherein the overlapping degree obtained by multiplying the accumulated average value of all the nodes by the path is the final reward value of the path.

7. The system of claim 1, wherein the editing data comprises visual elements and/or coding properties, and the personalized design of the new icon visualization is achieved by modifying the visual elements and/or the coding properties of the visual elements, wherein the coding properties comprise color, numerical size, transparency, number, and rotation angle.

8. A method for automatic generation of icon visualizations, characterized in that the method applies the system of any one of claims 1-7, the method comprising the steps of:

receiving data which is uploaded by a user and needs icon visualization by using a receiving module;

searching a series of metaphor pictures for received data by using a metaphor picture searching and processing module according to metaphor picture standards, deconstructing and processing the metaphor pictures to obtain visual elements, and forming a visual element list;

binding the received data with visual elements in the visual element list by using a binding and drawing module, endowing the bound visual elements with coding attributes according to the data types, and drawing the visual elements according to the coding attributes to obtain metaphor-based icon visualization;

and receiving the editing data of a user by using an editing interface provided by the editing module, and drawing and generating a metaphor-based new icon visualization according to the editing data.

Images