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Reporters obtained the following quote from the background information supplied by the inventors: "A chart or graph is described in Wikipedia as a type of information graphic or graphic organizer that represents tabular numeric data and/or functions. Charts are often used in an attempt to make it easier to understand large quantities of data and the relationship between different parts of the data. Charts can usually be read more quickly than the raw data that they come from. They are used in a wide variety of fields, and can be created by hand (e.g., on graph paper) or by computers using various charting applications.

"Traditional charts use well established and often poorly implemented ways of representing data. Many tools exist to help the user construct very sophisticated representations of data but that sophistication typically results in less meaningful charts.

"It is known to use charting wizards such as those that are available in Microsoft.RTM. Excel.TM. and various other systems such as those provided by, for example, IBM..RTM. In addition there are multiple Business Intelligence (BI) tools available to users to enable users to analyze data in an attempt to create meaningful feedback. However, as the amount of data increases, so does the complexity of the visual representations created by the analysis of the data. These complex representations can end up swamping parts of the visual representation that are most useful and relevant to an end user.

"One known method of visualizing data is a heatmap. A heatmap identifies the data values of individual data points by allocating a specific color based on the data value. For example, red may indicate that the data value is high, and blue may indicate that the data value is low. The color spectrum in between red and blue may then be used to indicate the intermediate values for relevant data points. The heatmap graphic is particularly useful for showing the position and intensity of certain data values with respect to other data values and within a defined environment, such as a geographical area or temporal period.

"It is known to create heatmaps using an inverse distance weighted (IDW) formula, such as a bell shaped curve. However, these methods are extremely complex and can cause artefacts, which can be particularly problematic. It is also known to use a cubic spline method to create a heatmap, but this method is particularly processor (CPU) intensive.

"Heatmaps produced by the above described methods, such as that shown in FIG. 1, can produce quite garish and intense maps that tend to confuse the eye of the reader. For example, the heatmap of FIG. 1 is produced by rendering circles around a specific data point, where the color and diameter of the circle is based on a variable associated with the data point. Smaller diameter circles are used to represent smaller data values and larger diameter circles are used to represent larger data values. Further, the larger the circle (or data value) the 'hotter' the color used to represent the circle. For example, the largest values may be rendered using large circles colored red, whereas the smallest values may be rendered using small circles colored blue. At points where the circles overlap, the circle associated with the largest data value has priority over the smaller circles and the color for the larger circle is shown in the overlap region.

"One problem associated with this method of rendering the overlapped region is that only the values of data points representing the largest values appear in the overlap regions and an accurate representation of the overlap regions is not provided. For example, two data points that are close to each other that represent a maximum value will be rendered using the same color as three or four (or more) data points that are close to each other that represent the same maximum value. A further problem occurs when data points representing smaller values are positioned next to or close to data points representing larger values as the rendered larger value data points obscure the rendered smaller value data points. This results in loss of information being conveyed to the user because minimal data values may be a very important part of the data analysis.

"Prior known methods typically use spread functions, such as bell shaped curves, to calculate interpolation values for each point on a heatmap. These spread functions tail off over a long distance (graphically), requiring each point to take into account all other data points, even if positioned a large graphical distance away from the data point being calculated. Therefore, high levels of computing are required to calculate all values on the heatmap as all points influence all other points."

In addition to obtaining background information on this patent application, VerticalNews editors also obtained the inventors' summary information for this patent application: "Disclosed embodiments overcome or reduce the problems associated with the known methods. In particular, disclosed embodiments provide systems and methods that enable efficient production of heatmaps and other graphical displays without loss of valuable data.

"According to some embodiments, a method for creating a graphical representation of data in the form of a heatmap is performed at an electronic computing device. The device positions data points on a heatmap for graphical representation and calculates conical distribution values around a first data point based on a first data value associated with the first data point. When a conical distribution value around the first data point is greater than a second data value associated with a second data point, the device adjusts the conical distribution values proximate to the second data point by applying an inverse conical distribution around the second data point. The device renders the heatmap based on the calculated conical distribution values and the adjusted conical distribution values so that the data value of the second data point is visible on the heatmap.

"In some embodiments, the conical distribution values are calculated by applying a frustoconical distribution, an exact conical distribution, or a skewed conical distribution.

"In some embodiments, the inverse conical distribution values are calculated by applying one of an inverse frustoconical distribution, an exact inverse conical distribution, or a skewed inverse conical distribution.

"In some embodiments, the device sums conical distribution values when conical distributions for multiple data points overlap.

"In some embodiments, the device selects a highest conical distribution value of multiple data points when conical distribution values for the multiple data points overlap.

"In some embodiments, the device adjusts conical distribution values at edges of a distribution to provide a smoothing effect.

"In some embodiments, the data is gaming data associated with a gaming environment or retail data associated with a retail environment.

"According to some embodiments, a graphical computing system for generating a heatmap includes one or more processors, memory, and one or more programs stored in the memory for execution by the one or more processors. The one or more programs include a data calculation module configured to position data points on a heatmap for graphical representation and calculate conical distribution values around each respective data point based on a respective data value associated with the respective data point. The one or more programs include a minima detection module configured to determine when a conical distribution value for a first data point is greater than a second data value associated with a second data point distinct from the first data point. The one or more programs include an inverse conical calculation module configured to calculate inverse conical distribution values around each respective detected minima data point, the inverse conical distribution values based on the respective data value of the respective detected minima data point. The one or more programs also include a rendering module configured to render the heatmap based on the calculated conical distribution values and the calculated inverse conical distribution values such that each data value associated with a detected minima data point is visible in the heatmap.

"One of skill in the art also knows that a graphical representation of data may use features other than color to represent different data values. For example, values may be represented by different shades of gray (e.g., small values represented by nearly white, very large values represented by black, and intermediate values represented by intermediate shades of gray) or shading patterns. Although the example embodiments are implemented in colored heatmaps, the disclosure is not limited to the use of colored heatmaps.

"According to some embodiments, a method for creating a graphical representation of data is performed at an electronic device having one or more processors and memory. The device receives a finite set of data points and calculates a respective conical distribution for each respective data point centered on the respective data point and based on a respective data value. Each conical distribution comprises a set of locations and a unique distribution value corresponding to each location. The device determines that a first data value of a first data point is less than a distribution value for a second data point, where the distribution value has a location that corresponds to the first data point. Based on the determination, the device calculates an inverse conical distribution in a region around the first data point and combines the conical distributions and inverse conical distributions to display a data visualization that includes each of the data points.

"In some embodiments, the data visualization is displayed as a heatmap in which colors are assigned to locations based on the distribution values corresponding to each location.

"In some embodiments, the conical distribution is a frustoconical distribution, an exact conical distribution, or a skewed conical distribution.

"In some embodiments, the inverse conical distribution is an inverse frustoconical distribution, an exact inverse conical distribution, or a skewed inverse conical distribution.

"In some embodiments, the device sums distribution values at locations where conical distributions for multiple data points overlap.

"In some embodiments, the device selects a highest distribution value of multiple data points at locations where conical distributions for the multiple data points overlap.

BRIEF DESCRIPTION OF THE DRAWINGS

"Embodiments of the present invention will now be described, by way of example only, with reference to the accompanying drawings.

"FIG. 1 shows an example of a heatmap using a prior known method.

"FIG. 2A shows a system block diagram of a data visualization system according to some embodiments.

"FIG. 2B shows a flow diagram for performing a heatmap generation method according to some embodiments.

"FIG. 3 shows a heatmap generated according to one embodiment.

"FIGS. 4A-4C illustrate using conic distributions to construct a data visualization according to some embodiments.

"FIGS. 5A-5C illustrate how conic distributions can be adjusted when a large data value is near a small data value in accordance with some embodiments.

"FIGS. 6A-6B illustrate using frustoconical distributions to construct a data visualization according to some embodiments.

"FIGS. 7A-7C illustrate how frustoconical distributions can be adjusted when a large data value is near a small data value according to some embodiments

"FIGS. 8A-8B illustrate using skewed conical distributions to construct a data visualization according to some embodiments.

"FIG. 9 shows a system diagram of a gaming environment according to some embodiments.

"Like reference numerals refer to corresponding parts throughout the drawings."

For more information, see this patent application:

Keywords for this news article include: Information Technology,

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