CN106095919B - Data variation trend spring visualization system and method towards analysis of central issue - Google Patents
Data variation trend spring visualization system and method towards analysis of central issue Download PDFInfo
- Publication number
- CN106095919B CN106095919B CN201610405588.8A CN201610405588A CN106095919B CN 106095919 B CN106095919 B CN 106095919B CN 201610405588 A CN201610405588 A CN 201610405588A CN 106095919 B CN106095919 B CN 106095919B
- Authority
- CN
- China
- Prior art keywords
- data
- unit
- module
- icon
- display
- Prior art date
- Legal status (The legal status is an assumption and is not a legal conclusion. Google has not performed a legal analysis and makes no representation as to the accuracy of the status listed.)
- Expired - Fee Related
Links
- 238000012800 visualization Methods 0.000 title claims abstract description 51
- 238000004458 analytical method Methods 0.000 title claims abstract description 29
- 238000000034 method Methods 0.000 title claims abstract description 25
- 238000004364 calculation method Methods 0.000 claims abstract description 59
- 230000003993 interaction Effects 0.000 claims abstract description 19
- 230000008859 change Effects 0.000 claims abstract description 17
- 230000008569 process Effects 0.000 claims abstract description 10
- 230000000007 visual effect Effects 0.000 claims description 22
- 238000000605 extraction Methods 0.000 claims description 10
- 230000007774 longterm Effects 0.000 claims description 9
- 230000002452 interceptive effect Effects 0.000 claims description 8
- XLYOFNOQVPJJNP-UHFFFAOYSA-N water Substances O XLYOFNOQVPJJNP-UHFFFAOYSA-N 0.000 claims description 7
- 239000000284 extract Substances 0.000 claims description 4
- 230000003068 static effect Effects 0.000 claims description 4
- 238000009792 diffusion process Methods 0.000 claims description 3
- 238000009877 rendering Methods 0.000 claims 2
- 230000002265 prevention Effects 0.000 claims 1
- 238000007794 visualization technique Methods 0.000 description 12
- 238000011161 development Methods 0.000 description 5
- 238000005516 engineering process Methods 0.000 description 4
- 238000010586 diagram Methods 0.000 description 3
- 238000013079 data visualisation Methods 0.000 description 2
- 238000001514 detection method Methods 0.000 description 2
- 230000000694 effects Effects 0.000 description 2
- 235000019580 granularity Nutrition 0.000 description 2
- 238000012545 processing Methods 0.000 description 2
- 208000035473 Communicable disease Diseases 0.000 description 1
- 238000006243 chemical reaction Methods 0.000 description 1
- 238000007635 classification algorithm Methods 0.000 description 1
- 238000007405 data analysis Methods 0.000 description 1
- 238000013480 data collection Methods 0.000 description 1
- 230000007423 decrease Effects 0.000 description 1
- 230000003247 decreasing effect Effects 0.000 description 1
- 230000007812 deficiency Effects 0.000 description 1
- 208000015181 infectious disease Diseases 0.000 description 1
- 230000002093 peripheral effect Effects 0.000 description 1
- 230000009467 reduction Effects 0.000 description 1
- 230000004044 response Effects 0.000 description 1
- 238000012216 screening Methods 0.000 description 1
Classifications
-
- G—PHYSICS
- G06—COMPUTING; CALCULATING OR COUNTING
- G06F—ELECTRIC DIGITAL DATA PROCESSING
- G06F16/00—Information retrieval; Database structures therefor; File system structures therefor
- G06F16/90—Details of database functions independent of the retrieved data types
- G06F16/904—Browsing; Visualisation therefor
Landscapes
- Engineering & Computer Science (AREA)
- Databases & Information Systems (AREA)
- Theoretical Computer Science (AREA)
- Data Mining & Analysis (AREA)
- Physics & Mathematics (AREA)
- General Engineering & Computer Science (AREA)
- General Physics & Mathematics (AREA)
- User Interface Of Digital Computer (AREA)
Abstract
一种面向热点分析的数据变化趋势涌泉可视化系统及方法，包括：设置模块、数据读取模块、计算模块、调度模块以及交互模块，其中：设置模块向用户提供参数设置功能；数据读取模块读取来自用户数据流文件，计算热点数据；计算模块读取来自数据读取模块的热点数据，计算可视化数据；交互模块读取来自计算模块的可视化数据在显示设备中处理图标的显示，并处理用户的操作；调度模块保存可视化数据，并调用交互模块进行图像呈现。通过模拟涌泉模型，将热点显示为涌泉图标，从中心区域涌出并随时间扩散、移动和消失，该方法可表现热点及其热度，并表现热点随时间的变化趋势，便于用户进行热点跟踪和分析。
A data change trend spring visualization system and method for hotspot analysis, including: a setting module, a data reading module, a calculation module, a scheduling module, and an interaction module, wherein: the setting module provides parameter setting functions for users; the data reading module Read the data stream file from the user, and calculate the hotspot data; the calculation module reads the hotspot data from the data reading module, and calculates the visualization data; the interaction module reads the visualization data from the calculation module, and processes the icon display in the display device, and processes The user's operation; the scheduling module saves the visualization data, and calls the interaction module for image presentation. By simulating the spring model, the hot spot is displayed as a spring icon, which emerges from the central area and spreads, moves, and disappears with time. This method can represent the hot spot and its heat, and show the trend of the hot spot over time, which is convenient for users to identify hot spots. tracking and analysis.
Description
技术领域technical field
本发明涉及的是一种数据可视化分析领域的技术，具体是一种面向热点分析的数据变化趋势涌泉可视化系统及方法。The present invention relates to a technology in the field of data visualization analysis, in particular to a hotspot analysis-oriented data change trend spring visualization system and method.
背景技术Background technique
热点分析相关类型的数据最显著的特征就是数据数量多，数据之间存在语义关联且语义类型丰富，随时间不断生成的数据根据其各自的语义，数据的数量具有涌现的特点，即某类语义相近的数据在数量上周期性或者一次性达到相对其他类型较高的数值，因此在进行此类型数据的可视化分析时，需要根据数据数量的多少，突出显示数量较高的数据，即突出热点的显示，并且可同时呈现即时性热点分布和热点历史发展，从而方便对热点的分析和跟踪。The most notable feature of hotspot analysis related types of data is that there is a large amount of data, there are semantic associations between the data and the semantic types are rich, and the data generated continuously over time according to their respective semantics, the number of data has the characteristics of emergence, that is, a certain type of semantics The number of similar data reaches a higher value than other types periodically or at one time. Therefore, when performing visual analysis of this type of data, it is necessary to highlight the data with a high amount according to the amount of data, that is, to highlight hot spots. Display, and can simultaneously present the real-time distribution of hotspots and the historical development of hotspots, so as to facilitate the analysis and tracking of hotspots.
在现有的对时变数据的可视化方法中，对不同应用需要不同的可视化方案和方法，各种可视化方法也具有各自的特点和优势。例如，有的可视化方法针对维数较低的数据，利用比较传统的可视化技术，如折线、散点图等来显示特征数据与时间的关系；还有一些可视化方法则针对高维数据的静态，通过对传统的可视化方法进行改进或是提出全新的可视化方法，通过降维方法将高维数据的特征量展示在低维图形中。针对在包含但不限于新闻热点分析、传染病流行分析等各类热点分析应用中，一种同时可呈现即时性热点分布和热点历史发展的数据可视化方法将有着广泛的应用价值。In the existing visualization methods for time-varying data, different visualization schemes and methods are required for different applications, and various visualization methods also have their own characteristics and advantages. For example, some visualization methods use traditional visualization techniques, such as polylines and scatter plots, to display the relationship between feature data and time for low-dimensional data; By improving the traditional visualization method or proposing a new visualization method, the feature quantity of high-dimensional data is displayed in a low-dimensional graph through a dimensionality reduction method. For various hot spot analysis applications including but not limited to news hot spot analysis and infectious disease epidemic analysis, a data visualization method that can simultaneously present instant hot spot distribution and hot spot historical development will have extensive application value.
发明内容SUMMARY OF THE INVENTION
本发明针对现有技术存在的上述不足，提出一种面向热点分析的数据变化趋势涌泉可视化系统及方法，在可视化显示区域内，将语义相近的一组数据表示为一个图标单元。当一组数据的热度满足显示条件时，该组数据所对应的图标单元将显示在可视化显示区域中。图标单元的显示模拟涌泉物理模型，类似涌泉水泡的图标单元从显示区域的中心区域涌出，水泡根据数据的热度及其他属性值确定图标单元的大小、位置、颜色、透明度等的属性，随时间所有的图标单元动态地显现、移动和消失，综合动态地表现数据热点随时间的变化情况，便于用户对数据中的热点进行观察分析和跟踪。Aiming at the above-mentioned deficiencies in the prior art, the present invention proposes a data change trend spring visualization system and method for hotspot analysis, in which a group of data with similar semantics is represented as an icon unit in the visualization display area. When the popularity of a set of data meets the display conditions, the icon unit corresponding to the set of data will be displayed in the visual display area. The display of the icon unit simulates the physical model of the spring. The icon unit similar to the bubble of the spring emerges from the center of the display area. The bubble determines the size, position, color, transparency and other attributes of the icon unit according to the heat of the data and other attribute values. All the icon units dynamically appear, move and disappear over time, and comprehensively and dynamically show the changes of data hotspots over time, which is convenient for users to observe, analyze and track hotspots in the data.
本发明是通过以下技术方案实现的：The present invention is achieved through the following technical solutions:
本发明包括：设置模块、数据读取模块、计算模块、调度模块以及交互模块，其中：设置模块向用户提供显示参数和计算参数的参数设置功能；数据读取模块读取来自用户提供的数据流文件，提取数据的语义信息，并根据语义信息进行热点分析和热度计算；计算模块读取来自数据读取模块的热点及热度数据，将热点和热点的热度数据映射到涌泉可视化模型中，计算得出可视化数据；调度模块读取设置模块的设置参数，保存可视化数据，并根据交互模块中用户的操作命令，取出可视化数据，并调用交互模块进行刷新显示；交互模块生成最终的显示图像，并处理用户输入。The present invention includes: a setting module, a data reading module, a calculation module, a scheduling module and an interaction module, wherein: the setting module provides the user with a parameter setting function of display parameters and calculation parameters; the data reading module reads the data stream provided by the user file, extract the semantic information of the data, and perform hot spot analysis and heat calculation according to the semantic information; the calculation module reads the hot spot and heat data from the data reading module, maps the hot spot and the heat data of the hot spot to the Yongquan visualization model, and calculates Obtain the visualization data; the scheduling module reads the setting parameters of the setting module, saves the visualization data, and takes out the visualization data according to the user's operation command in the interaction module, and calls the interaction module to refresh the display; the interaction module generates the final display image, and Handle user input.
所述的涌泉可视化模型用于模拟现实中的涌泉的物理形态，热点在模型中显示为一个图标，图标模拟了涌泉物理模型中涌出的水泡。在涌泉物理模型中，当热点第一次出现时从中心区域涌出，随时间逐渐向四周扩散，扩散过程中根据热度的变化情况，图标的颜色、大小、内部图形等属性不断发生变化，并最终随热度的下降热点消失而消失。随着原始数据中热点的转换和热度的不断变化，图标的属性，如颜色、边框、大小、内部呈现等随之根据数据热度及其他属性值的变化而变动，生成持续动态的可视化图形。The visualization model of the spring is used to simulate the physical form of the spring in reality, and the hot spot is displayed as an icon in the model, and the icon simulates the bubbles gushing out of the physical model of the spring. In the Yongquan physical model, when the hotspot first appears, it emerges from the central area and gradually spreads to the surroundings over time. During the diffusion process, according to the change of heat, the attributes such as the color, size, and internal graphics of the icon are constantly changing. And finally disappear with the decline of heat. With the conversion of hotspots in the original data and the continuous change of popularity, the attributes of icons, such as color, border, size, and internal presentation, etc. will change according to the changes of data heat and other attribute values, generating continuous and dynamic visual graphics.
所述的设置模块包括：显示参数设置单元、计算参数设置单元和参数存取单元，其中：显示参数设置单元与参数存取单元相连并处理用户的显示参数输入并传输信息；计算参数设置单元与参数管理单元相连并处理用户的计算参数输入并传输信息；参数存取单元分别与数据读取模块和计算模块和调度模块相连以存取参数。The setting module includes: a display parameter setting unit, a calculation parameter setting unit and a parameter access unit, wherein: the display parameter setting unit is connected to the parameter access unit and processes the user’s display parameter input and transmits information; the calculation parameter setting unit is connected to the parameter access unit. The parameter management unit is connected to process the user's calculation parameter input and transmit information; the parameter access unit is respectively connected to the data reading module, the calculation module and the scheduling module to access the parameters.
所述的显示参数包括但不限于待呈现数据的类别选择、动画速度、显示区域大小、图标大小、字体及大小、最小热度阈值、可视化画面刷新时间间隔、最大可显示热点数量、显示宽松系数(可视化图标之间允许的拥挤程度，取值范围为1.1～1.5)等。The display parameters include but are not limited to category selection of the data to be presented, animation speed, display area size, icon size, font and size, minimum heat threshold, visual screen refresh time interval, maximum number of displayable hotspots, display relaxation coefficient ( The allowable crowding degree between visual icons, the value range is 1.1～1.5), etc.
所述的计算参数包括但不限于热度计算公式中的时间周期、热度计算所涉及到的数据类型和各自的权重等。The calculation parameters include, but are not limited to, the time period in the heat calculation formula, the data types and respective weights involved in the heat calculation, and the like.
所述的数据读取模块包括：数据读取单元、语义提取单元、热点分析及热度计算单元，其中：数据读取单元与语义提取单元相连，解析并传输原始数据；语义提取单元与热点分析和热度计算单元相连并传输分类后的数据；热点分析和热度计算单元与计算模块相连并传输热点及其不同时间周期的热度数据。The data reading module includes: a data reading unit, a semantic extraction unit, a hotspot analysis and a heat calculation unit, wherein: the data reading unit is connected with the semantic extraction unit, parses and transmits the original data; the semantic extraction unit is connected with the hotspot analysis and The thermal calculation unit is connected and transmits the classified data; the hot spot analysis and thermal calculation unit is connected with the calculation module and transmits the thermal data of the hot spots and their different time periods.
所述的数据读取模块中的数据读取单元、语义提取单元、热点分析及热度计算单元均根据用户提供数据的更新频率同步计算和更新各自的数据。The data reading unit, semantic extraction unit, hotspot analysis and heat calculation unit in the data reading module all synchronously calculate and update their respective data according to the update frequency of the data provided by the user.
所述的语义提取单元对随时间不断生成的数据根据其内在语义进行层次型分类，即首先将全部数据进行分类，其后对某一个类别的数据再进行分类，分类的总数量应大于显示参数中最大可显示热点数量。The semantic extraction unit classifies the data continuously generated over time according to its intrinsic semantics, that is, first classifies all the data, and then classifies the data of a certain category. The total number of classifications should be greater than the display parameter The maximum number of hotspots that can be displayed in .
所述的热点是指热度超过最小热度阈值的某语义类别，热点的热度是指根据某类别数据的生成情况计算得来的数据，表示某类别发展的情况，热度越高，表明该类别数据发生速度快，发生数量多，具体为：其中Δt为设置模块中设置的单位时间，D为该类别特定相关数据类型的新增数量，w为该特定相关数据类型的权重。该公式计算得到在单位时间内相关该类别的各项数据的新增数据加权总和。The hot spot refers to a certain semantic category whose heat exceeds the minimum heat threshold. The heat of a hot spot refers to the data calculated according to the generation of a certain type of data, which indicates the development of a certain type. The speed is fast and the number of occurrences is large, specifically: Where Δt is the unit time set in the setting module, D is the newly added quantity of the specific related data type of this category, and w is the weight of the specific related data type. This formula calculates the weighted sum of newly added data of each data related to this category within a unit time.
所述的不同时间周期的热度数据是指根据不同的单位时间得出的热度值，其中：热度计算按照三个周期：长周期、中周期、短周期，其中长周期一般设定为用户给定数据中热点平均持续时间T的α倍数，其中α取值范围一般为[1.0,3.0]；中周期设定为约等于热点的热度波动周期Tp的时间，短周期一般由用户设置，是用户希望监测的最短时间。The heat data of different time periods refers to the heat value obtained according to different unit time, wherein: the heat is calculated according to three cycles: long cycle, medium cycle, and short cycle, and the long cycle is generally set to be given by the user. The α multiple of the average duration T of hotspots in the data, where the value range of α is generally [1.0,3.0]; the medium period is set to be approximately equal to the time of the heat fluctuation period T p of the hotspot, and the short period is generally set by the user. The minimum time you want to monitor.
所述的可视化数据是指可视化呈现区域中显示图标的类型、标签、位置等显示内容及其属性数据，包括：当前的显示数据和历史显示数据，并可根据多个显示数据从而形成动态的显示图像。The visualized data refers to the display content such as the type, label, and position of the icon displayed in the visualized presentation area and its attribute data, including: current display data and historical display data, and can form a dynamic display according to multiple display data image.
所述的计算模块包括：坐标计算单元、图标属性计算单元和微调单元，其中：坐标计算单元与微调单元相连，计算并传输图标的理论坐标；图标属性计算单元与微调单元相连，计算并传输图标的属性；微调单元与调度模块相连，计算并传输最终可视化数据。The calculation module includes: a coordinate calculation unit, an icon attribute calculation unit and a fine-tuning unit, wherein: the coordinate calculation unit is connected to the fine-tuning unit to calculate and transmit the theoretical coordinates of the icon; the icon attribute calculation unit is connected to the fine-tuning unit to calculate and transmit the icon properties; the fine-tuning unit is connected with the scheduling module to calculate and transmit the final visualization data.
所述的图标的理论坐标是指表示热点的图标中心在可视化呈现区域中的位置。该位置由热点所处的语义类别所在的扇形区域角度和热点距离可视化呈现区域中心的距离决定。设可视化数据中所有图标的语义分类为n个类别，各个类别的长周期热度分别为(H1,H2…Hn)，将可视化呈现区域分为n个扇形区域，第k个语义类别所在扇形的角度从到根据热点的语义类别，热点将平均分配到扇形区域之内的某一角度上。热点距离可视化呈现区域中心的距离是热点持续时间Tc决定的，设可视化呈现区域边缘与中心距离的最远距离为L，热点距离可视化呈现区域中心的距离可根据计算初值，其中：a的取值范围为0.3～0.7，并限制距离的最大值为L。即热点的位置随着热点持续时间的延长，而移动到可视化呈现区域的边缘，并保持在边缘直到热点消失。The theoretical coordinates of the icon refer to the position of the center of the icon representing the hotspot in the visual presentation area. The location is determined by the angle of the fan-shaped area where the semantic category of the hotspot is located and the distance between the hotspot and the center of the visual presentation area. Assume that the semantic classification of all icons in the visualization data is divided into n categories, and the long-term popularity of each category is (H 1 , H 2 ...H n ), and the visualization presentation area is divided into n fan-shaped areas, where the kth semantic category is located fan angle from arrive According to the semantic category of the hot spot, the hot spot will be evenly distributed to a certain angle within the fan-shaped area. The distance between the hot spot and the center of the visual presentation area is determined by the hot spot duration Tc. Let the farthest distance between the edge of the visual presentation area and the center be L, and the distance between the hot spot and the center of the visual presentation area can be determined according to Calculate the initial value, where: the value range of a is 0.3-0.7, and the maximum value of the limited distance is L. That is, the location of the hotspot moves to the edge of the visualization presentation area as the duration of the hotspot increases, and remains at the edge until the hotspot disappears.
所述的微调单元根据所有图标的理论大小计算尺寸微调系数γ，根据尺寸微调系数调整图标尺寸大小。微调单元还对图标相互之间的重叠进行碰撞检测，通过调整图标位置来避免重叠。尺寸微调系数为所有图标理论面积之和乘以显示宽松系数再除以显示区域的面积。当尺寸微调系数大于1时，图标理论尺寸要除以微调系数，保证图标显示较为宽松，避免拥挤。微调单元按长周期热度对所有图标进行排序，并从长周期热度较小的图标开始根据每一个图标的位置及其大小逐一检查是否与其他图标存在重叠。一旦发现重叠，则将长周期热度较大的图标向外侧移动，直到消除重叠现象。微调单元计算得出图标的最终显示坐标。The fine-tuning unit calculates a size fine-tuning coefficient γ according to the theoretical sizes of all icons, and adjusts the size of the icons according to the size fine-tuning coefficient. The fine-tuning unit also performs collision detection on the overlapping of the icons, and avoids overlapping by adjusting the position of the icons. The size fine-tuning factor is the sum of the theoretical areas of all icons multiplied by the display easing factor and divided by the area of the display area. When the size fine-tuning coefficient is greater than 1, the theoretical size of the icon should be divided by the fine-tuning coefficient to ensure that the icon display is looser and avoids crowding. The fine-tuning unit sorts all the icons according to the long-term popularity, and checks whether there is overlap with other icons one by one according to the position and size of each icon starting from the icon with the lower long-term popularity. Once the overlap is found, move the icons with higher long-term popularity to the outside until the overlap is eliminated. The fine-tuning unit calculates the final display coordinates of the icon.
所述的调度模块根据设置模块中设置的显示参数及交互模块的用户操作单元中的交互式输入对可视化数据及其显示方式进行调度，该调度模块包括：可视化数据存取单元和动态控制单元，其中：可视化数据存取单元与计算模块相连，保存并传输可视化数据，动态控制单元与交互模块相连，传输用于当前图像显示的可视化数据及控制数据。The scheduling module schedules the visualization data and its display mode according to the display parameters set in the setting module and the interactive input in the user operation unit of the interaction module, the scheduling module includes: a visualization data access unit and a dynamic control unit, Among them: the visualization data access unit is connected with the calculation module to save and transmit the visualization data, and the dynamic control unit is connected to the interaction module to transmit the visualization data and control data for current image display.
所述的动态控制单元根据交互模块的用户操作单元中用户对图像呈现方式和数据查看模式的选择对图像呈现内容进行控制。所述的图像呈现方式是指自动或手动的浏览模式。所述的数据查看模式是指实时或历史数据查看模式。所述的自动浏览模式是按热度计算的短周期进行自动更新的图像呈现方式，手动的浏览模式则是用户手动进行刷新的图像呈现方式。历史数据的查看模式是指用户选定历史时段，显示历史数据的模式，实时数据查看模式是指根据系统最新的数据输入进行实时数据的模式。The dynamic control unit controls the image presentation content according to the user's selection of the image presentation mode and the data viewing mode in the user operation unit of the interaction module. The image presentation mode mentioned refers to an automatic or manual browsing mode. The data viewing mode refers to a real-time or historical data viewing mode. The automatic browsing mode is an image presentation mode in which the images are automatically updated in a short cycle calculated by the popularity, and the manual browsing mode is an image presentation mode in which the user manually refreshes the images. The viewing mode of historical data refers to the mode in which the user selects a historical time period and displays historical data, and the viewing mode of real-time data refers to the mode of performing real-time data according to the latest data input of the system.
所述的交互模块包括：动画单元、静态单元和用户操作单元，其中：动画单元根据调度模块传递过来的可视化数据及控制数据调整或者重新设置可视化呈现区域中图标的位置等属性，并根据图标原有位置等属性设置动画动作的显示。静态单元在动画单元完成动画显示后控制可视化呈现区域中显示，处理鼠标、键盘等用户输入，并处理鼠标悬浮、鼠标点击等操作，以显示图标的更多数据和进行语义类别定制。用户操作单元根据所述动态控制单元的控制数据设置控制控件状态，显示控制控件，处理用户对控制控件的操作。用户操作单元与所述的动态控制单元相连，更新并传输用户对图像呈现方式和数据查看模式的选择和变更。The interaction module includes: an animation unit, a static unit and a user operation unit, wherein: the animation unit adjusts or resets the attributes such as the position of the icon in the visualization presentation area according to the visualization data and control data delivered by the scheduling module, and according to the icon original There are properties such as position to set the display of animation actions. After the animation unit completes the animation display, the static unit controls the display in the visual presentation area, handles user input such as mouse and keyboard, and handles operations such as mouse hover and mouse click to display more data of icons and customize semantic categories. The user operation unit sets the state of the control control according to the control data of the dynamic control unit, displays the control control, and processes the user's operation on the control control. The user operation unit is connected to the dynamic control unit to update and transmit the user's selection and change of the image presentation mode and data viewing mode.
技术效果technical effect
与现有技术相比，本发明不仅呈现当前时刻热点的具体情况，突出了热度大的数据，还兼顾了用户需要关注的热点较长期的发展状态，通过将距离因素与时间推演联系起来，可以更好的表现出热点随着时间变化的趋势，在视觉角度更容易人们根据时间因素发现原始数据中隐藏的信息。总的来说，该方法可以对多个热点在多个时间周期内的热度变化情况进行展示。本发明的技术效果进一步包括：Compared with the existing technology, the present invention not only presents the specific situation of the hot spots at the current moment, highlights the hot data, but also takes into account the long-term development status of the hot spots that users need to pay attention to. By linking the distance factor with the time deduction, it can It better shows the trend of hotspots changing over time, and it is easier for people to discover the hidden information in the original data based on time factors from a visual perspective. In general, this method can display the temperature changes of multiple hotspots in multiple time periods. Technical effect of the present invention further comprises:
1、与现有的Tag云技术相比，本可视化方法中图标的位置和大小不仅与热点的热度相关，而且可以展示热点的热度变化情况，因此，用户在可视化图像上可以获得有关热点的热度演变情况。1. Compared with the existing Tag cloud technology, the position and size of the icon in this visualization method are not only related to the heat of the hotspot, but also can display the heat change of the hotspot. Therefore, the user can obtain the heat of the hotspot on the visualized image evolution.
2、本可视化方法与现有折线图、二维气泡图等可视化方法相比，适用于同时显示大量热点的情况，呈现密度做到接近Tag云技术，适用于不同大小尺寸的显示设备；2. Compared with the existing visualization methods such as line graphs and two-dimensional bubble graphs, this visualization method is suitable for displaying a large number of hotspots at the same time. The presentation density is close to that of Tag cloud technology, and it is suitable for display devices of different sizes;
3、本可视化方法通过设定图标的位置变动、内部呈现等图标呈现属性呈现更多时间周期内的热点变化情况；3. This visualization method presents the changes of hotspots in more time periods by setting icon presentation attributes such as icon position changes and internal presentation;
4、本可视化方法适用于各类热点分析应用，通过数据的语义进行分类，呈现结果的粒度取决于语义分类数据，因此可在不同粒度下的进行呈现；4. This visualization method is suitable for all kinds of hot spot analysis applications. It classifies the semantics of the data. The granularity of the presentation results depends on the semantic classification data, so it can be presented at different granularities;
5、本可视化方法适用于大型数据的分析，也同样适用于少量数据的分析和可视化。5. This visualization method is suitable for the analysis of large data, and also suitable for the analysis and visualization of a small amount of data.
附图说明Description of drawings
图1为本发明实现系统的结构框图；Fig. 1 is the structural block diagram of the realization system of the present invention;
图2为本发明可视化程序的可视化结果示意图。Fig. 2 is a schematic diagram of the visualization result of the visualization program of the present invention.
具体实施方式Detailed ways
本实施例实现的涌泉可视化模型的系统面向的热点分析数据集为新闻文本集W，该新闻文本集合中的每一个新闻包含有如下特征：发布时间、新闻内容、新闻来源以及新闻阅读量、转发量、评论量、点赞量等。如图1所示，本实施例包括：设置模块、数据读取模块、计算模块、调度模块以及交互模块，其中：设置模块向用户提供显示参数和计算参数的参数设置功能；数据读取模块读取来自用户提供的数据流文件，提取数据的语义信息，并根据语义信息进行热点分析和热度计算；计算模块读取来自数据读取模块的热点及热度数据，将热点和热点的热度数据映射到涌泉可视化模型中，计算得出可视化数据；调度模块读取设置模块的设置参数，保存可视化数据，并根据交互模块中用户的操作命令，取出可视化数据，并调用交互模块进行刷新显示；交互模块生成最终的显示图像，并处理用户输入。The system-oriented hotspot analysis data set of the Yongquan visualization model implemented in this embodiment is a news text set W, and each news in this news text set includes the following features: release time, news content, news source, and news reading volume, Retweets, comments, likes, etc. As shown in Figure 1, the present embodiment includes: a setting module, a data reading module, a calculation module, a scheduling module and an interaction module, wherein: the setting module provides the user with a parameter setting function of display parameters and calculation parameters; the data reading module reads Take the data stream file provided by the user, extract the semantic information of the data, and perform hot spot analysis and heat calculation according to the semantic information; the calculation module reads the hot spot and heat data from the data reading module, and maps the hot spot and the heat data of the hot spot to In the Yongquan visualization model, the visualization data is calculated; the scheduling module reads the setting parameters of the setting module, saves the visualization data, and takes out the visualization data according to the user's operation command in the interaction module, and calls the interaction module to refresh the display; the interaction module Generate the final display image, and handle user input.
所述的设置模块可供用户设置显示参数、计算参数等参数。其中一般情况下新闻类型数据的热点平均持续时间为3天，因此用户可设置长周期为6天或者1周，新闻热点的热度波动周期一般为一天，即一天内新闻的热度数据有明显的周期性波动，因此新闻中周期可设置为1天，新闻数据分析的短周期可设置为1小时或者2小时，短周期参数设置一方面由用户数据收集速度确定，一方面由对热点反应速度的要求决定；设置模块中，用户设置图标的属性与热点数据的对应关系，在本实施例中，图标的颜色属性设置为对应热点的短周期热度，图标的大小属性设置为热点的中周期热度。The setting module can be used for users to set display parameters, calculation parameters and other parameters. Under normal circumstances, the average duration of hot spots in news-type data is 3 days, so users can set the long cycle to 6 days or 1 week. The heat fluctuation cycle of news hotspots is generally one day, that is, the heat data of news within a day has an obvious cycle. Therefore, the medium cycle of news can be set to 1 day, and the short cycle of news data analysis can be set to 1 hour or 2 hours. The parameter setting of the short cycle is determined by the user data collection speed on the one hand, and the response speed requirements on hot spots on the other hand. Decision; in the setting module, the user sets the corresponding relationship between the attribute of the icon and the hotspot data. In this embodiment, the color attribute of the icon is set to the short-cycle heat of the corresponding hot spot, and the size attribute of the icon is set to the medium-cycle heat of the hot spot.
所述的数据读取模块读取用户所收集的全部新闻及其新闻的实时数据，其中包括新闻本身的文本以及每一条新闻实时变化的阅读数、评论数、评论文字、点赞数量等。数据读取模块读取用户的数据，并对新闻进行语义分析及相关统计，根据用户设置或者自动分类算法将新闻分为几个类别，提取新闻的关键词，并在类别下使用关键词组合分析新闻的具体类别，计算每一个热点类别的多周期热度，热度的计算公式为，R＝a1Y+a2P+a3Z+a4L，其中Y为某一热点的某周期新增阅读量，P为某一热点的某周期新增评论量，Z为新增转发量，L为新增点赞量，a1～a4为设置模块中设置的加权参数，一般可设置为[1,2,2,1.5]。高于中周期热度阈值的被判定为热点，中周期阈值一般可设置为近期中周期热度最高值的0.001倍。The data reading module reads all the news collected by the user and its real-time data, including the text of the news itself and the number of readings, comments, comment text, and likes of each news in real time. The data reading module reads the user's data, and performs semantic analysis and related statistics on news, divides news into several categories according to user settings or automatic classification algorithms, extracts keywords of news, and uses keyword combination analysis under categories For the specific category of news, calculate the multi-period popularity of each hot category. The formula for calculating the popularity is, R=a 1 Y+a 2 P+a 3 Z+a 4 L, where Y is the new addition of a hot spot in a certain period The number of readings, P is the number of new comments in a certain period of a certain hotspot, Z is the number of new reposts, L is the number of new likes, a 1 ~ a 4 are the weighted parameters set in the setting module, generally can be set to [ 1,2,2,1.5]. Those that are higher than the mid-cycle heat threshold are judged as hot spots, and the mid-cycle threshold can generally be set to 0.001 times the highest value of the recent mid-cycle heat.
所述的计算模块将数据读取模块计算得来的热点及其热度数据映射到涌泉可视化模型的特征中。在本实施例中，热点将显示为一个可见的水泡。所有热点被归在几个大的新闻类别下，例如社会、体育、教育、娱乐等，每一个类别分别安排在不同扇形区域，扇形区域的大小由可见该类别的热度和决定，这样，热点多或热度大的扇形区域较大。水泡较大时和水泡一起呈现的有热点关键词，水泡较小时，只有当鼠标悬浮在水泡上时，才会显示对应的关键词。新出现的热点从中央区域涌出，与中央区域的距离由热点涌出的时间长短决定，距离中央区域越远的水泡，表明该水泡所表征的热点在越长的时间内保持了较高的热度。限于显示区域的大小，水泡向外移动的距离越来越小，这样保证了长时间保持较高热度的水泡持续显示在显示区域的外围。The calculation module maps the hot spots and their heat data calculated by the data reading module to the characteristics of the Yongquan visualization model. In this example, the hot spot will appear as a visible blister. All hotspots are grouped under several major news categories, such as society, sports, education, entertainment, etc. Each category is arranged in a different fan-shaped area, and the size of the fan-shaped area is determined by the heat sum of the visible category. Or the fan-shaped area with high heat is larger. When the bubble is large, there are hot keywords displayed together with the bubble. When the bubble is small, the corresponding keyword will be displayed only when the mouse hovers over the bubble. The newly emerging hot spot emerges from the central area, and the distance from the central area is determined by the length of time for the hot spot to emerge. The farther the bubble is from the central area, the longer the hot spot represented by the bubble maintains a higher temperature. heat. Limited to the size of the display area, the distance that the water bubbles move outward is getting smaller and smaller, which ensures that the water bubbles that maintain a relatively high temperature for a long time are continuously displayed on the periphery of the display area.
在本实施例中，中周期即一天内统计热度表示为水泡大小，水泡越大，说明当天的热度较大；当前1小时的热度表示为水泡的透明度，颜色越透明，说明1小时内的热度越低；中周期的热度变化表示为水泡的颜色，颜色越红，表明该热点变热的速度越高。In this example, the statistical heat in the middle period, that is, within a day, is expressed as the size of the blisters. The larger the blisters, the greater the heat of the day; the current 1-hour heat is expressed as the transparency of the blisters. The more transparent the color, the heat within 1 hour The lower the temperature is, the change in temperature in the mesocycle is expressed as the color of the blister, and the redder the color, the higher the speed at which the hot spot becomes hot.
计算模块中使用了水泡的碰撞检测和防碰撞处理，在两个检测到碰撞的水泡中，将半径大的水泡向远离中心的方向移动与半径成比例的一定距离，直至不再检测到碰撞。The calculation module uses the collision detection and anti-collision processing of water bubbles. Among the two detected collisions, the water bubble with a larger radius is moved away from the center by a certain distance proportional to the radius until no more collisions are detected.
所述的调度模块根据设置模块中设定计算参数及交互模块中用户操作单元中用户选择的图像呈现方式和数据查看模式，调用交互模块进行图像的呈现。在本实施例中，当用户选择自动浏览模式时，调度模块将按短周期为刷新间隔来调用交互模块刷新可视化呈现区域的显示结果，当用户选择手动浏览模式或者历史数据查看模式时，调度模块将根据用户的指令来传输用户所请求的数据，并由交互模块来呈现相应的图像。According to the calculation parameters set in the setting module and the image presentation mode and data viewing mode selected by the user in the user operation unit in the interaction module, the scheduling module calls the interaction module to perform image presentation. In this embodiment, when the user selects the automatic browsing mode, the scheduling module will call the interactive module to refresh the display results of the visual presentation area at a short cycle interval; when the user selects the manual browsing mode or the historical data viewing mode, the scheduling module The data requested by the user will be transmitted according to the user's instruction, and the corresponding image will be presented by the interactive module.
所述的交互模块根据计算模块计算出的数据给水泡的相关属性赋值并显示在屏幕上，并对水泡进行移动等动画处理，用户可以通过用户操作模块对动态的可视化图形进行暂停、开始、后退等操作，还可以选择历史时段来回演历史数据。According to the data calculated by the calculation module, the interaction module assigns values to the relevant attributes of the blisters and displays them on the screen, and performs animation processing such as moving the blisters, and the user can pause, start, and return the dynamic visual graphics through the user operation module And other operations, you can also select a historical time period to play back historical data.
本实施例涉及上述系统的面向热点分析的数据变化趋势涌泉可视化显示方法，按照所述数据读取模块对用户输入数据进行语义分类的结果，将显示区域分为多个扇形区域，每一个扇形区域为同一类型待呈现的热点数据的显示区域，当热点所表示该类数据的总体热度大于阈值时，每一个热点用一个图标表达，图标从显示区域中心涌出。This embodiment relates to the hotspot analysis-oriented data change trend spring visualization display method of the above-mentioned system. According to the result of semantic classification of user input data by the data reading module, the display area is divided into multiple fan-shaped areas, and each fan-shaped area The area is the display area for the same type of hotspot data to be presented. When the overall popularity of the data represented by the hotspot is greater than the threshold, each hotspot is represented by an icon, and the icon emerges from the center of the display area.
所述的扇形区域的大小取决于该类数据的长期热度大小，可根据该类数据的总体数量、可显示图标数量和大小进行调整。扇形区域的大小随时间根据数据的分布变化而变化；每一个扇形区域内某一更为细致的语义类型数据超过中周期热度阈值时发展为一个热点，表示为一个图标，该图标可以是但不限于水泡型。The size of the fan-shaped area depends on the long-term popularity of this type of data, and can be adjusted according to the overall quantity of this type of data, the number and size of displayable icons. The size of the fan-shaped area changes over time according to the distribution of data; when a more detailed semantic type data in each fan-shaped area exceeds the mid-cycle heat threshold, it develops into a hot spot, which is represented by an icon, which can be but not Limited to vesicular type.
所述的表示热点的图标的理论坐标由图标所表示的热点的持续时间和热点所在语义类别决定，但图标的最终显示坐标由防止重叠的微调单元决定。图标的其他显示属性包括但不限于大小、背景和前景色彩、外围色彩、透明度、内部图案运动速度和方向等，由热点的多个周期热度以及热点的其他属性决定。The theoretical coordinates of the icon representing the hotspot are determined by the duration of the hotspot represented by the icon and the semantic category of the hotspot, but the final display coordinates of the icon are determined by the fine-tuning unit for preventing overlapping. Other display attributes of the icon include but are not limited to size, background and foreground color, peripheral color, transparency, internal pattern movement speed and direction, etc., which are determined by the multiple cycle heat of the hotspot and other attributes of the hotspot.
所述的图标的涌出方向取决于其所在的扇形区域及防碰撞参数。图标从中心涌出后随时间逐渐向外扩散，速度由快至慢；图标与涌出中心的距离则由图标持续在显示区域中得以显示的时间和防碰撞参数决定。当图标所表示该类数据的总体热度小于阈值时，图标消失。The gushing direction of the icon depends on the fan-shaped area where it is located and the anti-collision parameters. After the icon emerges from the center, it gradually spreads outward over time, at a speed ranging from fast to slow; the distance between the icon and the center is determined by the time the icon continues to be displayed in the display area and the anti-collision parameters. When the overall popularity of the type of data represented by the icon is less than the threshold, the icon disappears.
所述的防碰撞参数是为了避免显示区域中图标拥挤造成的重叠，图标最终位置与计算位置之间的偏移量。在涌泉模型中，防碰撞的实现是将发生拥挤的图标由大到小向远离中心的方向在扇形区域内移动，直至不再检测到碰撞。The anti-collision parameter is an offset between the final position of the icon and the calculated position in order to avoid overlapping caused by crowded icons in the display area. In the Yongquan model, the realization of anti-collision is to move the crowded icons from large to small to the direction away from the center in the fan-shaped area until no collision is detected.
可视化的结果示意图如图2所示，在本实施例中，显示区域为有四个类别分配不同大小的扇形区域，第二类中的1号水泡，从中心涌出，逐渐变大并向外周扩散，说明1号水泡所代表的热点持续一段时间，并且热度呈现不断增强的态势。第三类所在扇形区域中的2号水泡，从中心涌出，逐渐变小并向四周扩散，说明该水泡所代表数据的热度在达到较高值后，不断下降。第一类扇形区域中的3号浅红色水泡在涌出后的第二天消失，说明该水泡并未获得较长期的关注度。第四类中的4号浅蓝色水泡在涌出后变化趋势与1号水泡类似，是当下的关注热点。The schematic diagram of the visualized results is shown in Figure 2. In this embodiment, the display area is a fan-shaped area with four categories assigned with different sizes. The No. 1 blister in the second category gushes out from the center, gradually becomes larger and expands to the periphery. Diffusion, indicating that the hot spot represented by blister No. 1 lasted for a period of time, and the heat showed a trend of increasing. The No. 2 water bubble in the fan-shaped area where the third type is located gushes out from the center, gradually becomes smaller and spreads to the surroundings, indicating that the heat of the data represented by the water bubble keeps decreasing after reaching a high value. No. 3 light red blisters in the first fan-shaped area disappeared on the second day after gushing out, indicating that the blisters did not receive long-term attention. The change trend of No. 4 light blue blister in the fourth category is similar to that of No. 1 blister after gushing out, and it is the focus of attention at present.
本实施例可以呈现热点分析数据集在给定观察时间区间范围内符合筛选条件的热点变化情况，在可视化图形中，数据的其他属性数据体现在涌泉可视化模型中水泡的大小、坐标、透明度等各种属性上。每一个水泡表示了一个当前的热点，该水泡图标的动态变化表示了该热点的发展变化情况。This embodiment can present the hotspot changes in the hotspot analysis data set that meet the screening conditions within a given observation time interval. In the visualization graph, other attribute data of the data are reflected in the size, coordinates, transparency, etc. of the bubbles in the Yongquan visualization model. on various attributes. Each bubble represents a current hot spot, and the dynamic change of the bubble icon indicates the development and change of the hot spot.
本实施例中由于需要实时的按照用户设置的短周期(即数据的最短刷新周期)计算热点及其热度，因此需要根据文本特征数据的计算量的多少部署不同的应用环境。大计算量的特征数据计算可以单独将数据读取模块部署于服务器或者大数据环境。其他模块的应用环境为个人PC、图形工作站或者智能设备等具有显示终端的设备，显示终端设备的分辨度则按用户需要显示热点数量的多少来选择。In this embodiment, since hotspots and their popularity need to be calculated in real time according to the short period set by the user (ie, the shortest data refresh period), different application environments need to be deployed according to the calculation amount of text feature data. For feature data calculation with a large amount of calculation, the data reading module can be deployed separately on the server or in the big data environment. The application environments of other modules are personal PCs, graphics workstations, or smart devices with display terminals. The resolution of the display terminal devices is selected according to the number of hotspots that the user needs to display.
在本实施例中，数据读取模块部署于工作站，处理每天1万条的新闻数据，其他模块部署于个人PC或者智能设备中，可实时显示10～100个或更多的热点，热点数量取决于显示设备的分辨率，在智能设备中，通常选择显示10～20个热点，在显示器分辨率为1280*800的台式计算机上可选择显示20～50个热点，在配备有分辨率大于1680*1050的显示器上可选择显示30～100个热点。用户可根据各自需求决定显示热点数量的多少。热点数量越多，热点显示尺寸越小，此时可选择较小的显示宽松系数，反之，则选择较大的显示宽松系数。In this embodiment, the data reading module is deployed on a workstation to process 10,000 pieces of news data per day, and other modules are deployed on personal PCs or smart devices, which can display 10 to 100 or more hotspots in real time, depending on the number of hotspots. Depending on the resolution of the display device, 10-20 hotspots are usually selected to be displayed in smart devices, and 20-50 hotspots can be selected to be displayed on a desktop computer with a display resolution of 1280*800. 30-100 hotspots can be selected to be displayed on the 1050 monitor. Users can decide the number of displayed hotspots according to their own needs. The larger the number of hotspots, the smaller the display size of the hotspots. At this time, a smaller display relaxation coefficient can be selected, otherwise, a larger display relaxation coefficient can be selected.
上述具体实施可由本领域技术人员在不背离本发明原理和宗旨的前提下以不同的方式对其进行局部调整，本发明的保护范围以权利要求书为准且不由上述具体实施所限，在其范围内的各个实现方案均受本发明之约束。The above specific implementation can be partially adjusted in different ways by those skilled in the art without departing from the principle and purpose of the present invention. The scope of protection of the present invention is subject to the claims and is not limited by the above specific implementation. Each implementation within the scope is bound by the invention.
Claims (10)
Priority Applications (1)
| Application Number | Priority Date | Filing Date | Title |
|---|---|---|---|
| CN201610405588.8A CN106095919B (en) | 2016-06-12 | 2016-06-12 | Data variation trend spring visualization system and method towards analysis of central issue |
Applications Claiming Priority (1)
| Application Number | Priority Date | Filing Date | Title |
|---|---|---|---|
| CN201610405588.8A CN106095919B (en) | 2016-06-12 | 2016-06-12 | Data variation trend spring visualization system and method towards analysis of central issue |
Publications (2)
| Publication Number | Publication Date |
|---|---|
| CN106095919A CN106095919A (en) | 2016-11-09 |
| CN106095919B true CN106095919B (en) | 2019-08-02 |
Family
ID=57229070
Family Applications (1)
| Application Number | Title | Priority Date | Filing Date |
|---|---|---|---|
| CN201610405588.8A Expired - Fee Related CN106095919B (en) | 2016-06-12 | 2016-06-12 | Data variation trend spring visualization system and method towards analysis of central issue |
Country Status (1)
| Country | Link |
|---|---|
| CN (1) | CN106095919B (en) |
Families Citing this family (6)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN107766309B (en) * | 2017-08-29 | 2021-06-25 | 腾讯科技（深圳）有限公司 | Data table generation method and device, storage medium and electronic device |
| CN108763429B (en) * | 2018-05-24 | 2022-03-29 | 成都睿码科技有限责任公司 | Two-dimensional display method for simulating development trend of cell-breeding news events |
| CN112783398B (en) * | 2019-11-08 | 2024-12-03 | 阿里巴巴集团控股有限公司 | Display control and interactive control method, device, system and storage medium |
| CN113378019B (en) * | 2020-03-10 | 2024-06-21 | 奇安信科技集团股份有限公司 | Wireless network hotspot classification visualization method, device and electronic device |
| CN111737556B (en) * | 2020-07-03 | 2021-01-26 | 和宇健康科技股份有限公司 | Big data information heat analysis method and cloud platform device |
| CN113805869B (en) * | 2021-09-17 | 2023-11-21 | 中国人民解放军国防科技大学 | A method for generating visual interfaces |
Citations (4)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN103023714A (en) * | 2012-11-21 | 2013-04-03 | 上海交通大学 | Activeness and cluster structure analyzing system and method based on network topics |
| CN103440237A (en) * | 2013-03-15 | 2013-12-11 | 武汉元宝创意科技有限公司 | Microblog data processing visualization system based on 3D (3-dimensional) model |
| CN104504150A (en) * | 2015-01-09 | 2015-04-08 | 成都布林特信息技术有限公司 | News public opinion monitoring system |
| CN104978407A (en) * | 2015-06-18 | 2015-10-14 | 上海交通大学 | Visualized presentation system and method for high-dimensional data characteristic attribute change trend |
-
2016
- 2016-06-12 CN CN201610405588.8A patent/CN106095919B/en not_active Expired - Fee Related
Patent Citations (4)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN103023714A (en) * | 2012-11-21 | 2013-04-03 | 上海交通大学 | Activeness and cluster structure analyzing system and method based on network topics |
| CN103440237A (en) * | 2013-03-15 | 2013-12-11 | 武汉元宝创意科技有限公司 | Microblog data processing visualization system based on 3D (3-dimensional) model |
| CN104504150A (en) * | 2015-01-09 | 2015-04-08 | 成都布林特信息技术有限公司 | News public opinion monitoring system |
| CN104978407A (en) * | 2015-06-18 | 2015-10-14 | 上海交通大学 | Visualized presentation system and method for high-dimensional data characteristic attribute change trend |
Also Published As
| Publication number | Publication date |
|---|---|
| CN106095919A (en) | 2016-11-09 |
Similar Documents
| Publication | Publication Date | Title |
|---|---|---|
| CN106095919B (en) | Data variation trend spring visualization system and method towards analysis of central issue | |
| CN114174960B (en) | Projection in a virtual environment | |
| Wickham et al. | Graphical inference for infovis | |
| US9070227B2 (en) | Particle based visualizations of abstract information | |
| Burch et al. | On the benefits and drawbacks of radial diagrams | |
| Evangelista Belo et al. | Auit–the adaptive user interfaces toolkit for designing xr applications | |
| Orlosky et al. | Managing mobile text in head mounted displays: studies on visual preference and text placement | |
| KR102809219B1 (en) | Technology for virtually testing out items | |
| US10001837B2 (en) | Technologies for interacting with computing devices using haptic manipulation | |
| US10388074B2 (en) | Generating immersive media visualizations for large data sets | |
| CN102455859B (en) | A kind of frequency spectrum data display packing and device | |
| CN111156855A (en) | A human-computer interaction system for virtual training of electronic warfare equipment | |
| US10275947B2 (en) | Modifying a simulated character by direct manipulation | |
| Fu et al. | Redefining natural user interface | |
| JP2021193555A (en) | Element-based switching of the raycasting method | |
| Arbeláez et al. | Crowdsourcing Augmented Reality Environment (CARE) for aesthetic evaluation of products in conceptual stage | |
| Hu et al. | Temporal continuity of visual attention for future gaze prediction in immersive virtual reality | |
| Caggianese et al. | Situated visualization in augmented reality: Exploring information seeking strategies | |
| TWI616779B (en) | Information display method and information display system | |
| CN108399045B (en) | Information display method and information display system | |
| Sun et al. | User Interface Design and Interactive Experience Based on Virtual Reality | |
| CN116301345A (en) | VR equipment control method based on visual brain-computer interface | |
| CN116308528A (en) | An animation display method, system, storage medium and intelligent terminal | |
| Spano et al. | IceTT: a responsive visualization for task models | |
| Nevalainen | A Comparative Study of Monitoring Data Center Temperature Through Visualizations in Virtual Reality Versus 2D Screen |
Legal Events
| Date | Code | Title | Description |
|---|---|---|---|
| C06 | Publication | ||
| PB01 | Publication | ||
| C10 | Entry into substantive examination | ||
| SE01 | Entry into force of request for substantive examination | ||
| GR01 | Patent grant | ||
| GR01 | Patent grant | ||
| CF01 | Termination of patent right due to non-payment of annual fee | ||
| CF01 | Termination of patent right due to non-payment of annual fee |
Granted publication date: 20190802 |