IP Library Granted Patent US 10,497,155
Granted Patent B2
US 10,497,155 · App. 15/703,796 · Granted Dec 3, 2019

Data visualization methods

Inventors: Andrew John Cardno (San Diego, CA); Peter Stewart Ingham (Lower Hutt, NZ); Bart Andrew Lewin (Woodlands Hills, CA); Ashok Kumar Singh (Henderson, NV)
Assignee: New BIS Safe Luxco S.à r.l
G06T11/206G06T11/001G07F17/32G07F17/3232G07F17/3255G07F19/20
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Quick Facts
Patent No.
US 10,497,155
App. No.
15/703,796
Granted
Dec 3, 2019
Kind
B2
Abstract

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. The distribution value has a location that corresponds to the first data point. Based on that determination, the device calculates an inverse conical distribution in a region around the first data point. The device combines the conical distributions and inverse conical distributions to display a data visualization that includes each of the data points.

Claims (46)

1. A method for creating a graphical representation of data in the form of a heatmap data visualization, implemented on an electronic computing device having one or more processors and memory, the method including the steps of:

identifying a finite set of data points in a data set;

positioning data points on a heatmap for graphical representation;

calculating conical distribution values around a data point based on a data value associated with that data point, wherein the conical distribution values correspond to a location in a region centered on the respective data point;

applying the highest distribution value of multiple data points at a location where the calculated conical distribution values for the multiple data points overlap at the location;

determining whether the conical distribution values calculated for a data point location are greater than the data value associated with the data point at that location;

upon a positive determination, calculating inverse conical distribution values around the data point based on the data value;

rendering the heatmap data visualization based on the calculated and the highest conical distribution values; and

displaying the rendered heatmap data visualization.

2. The method of claim 1 further including the steps of rendering the heatmap using the data points based on the conic distribution values and inverse conic distribution values.

3. The method of claim 1 wherein 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 to the data value.

4. The method of claim 3 wherein the conical distribution values are calculated by applying one of a frustoconical distribution, an exact conical distribution or a skewed conical distribution to the data value.

5. The method of claim 1 wherein the conical distribution values are calculated by applying one of a frustoconical distribution, an exact conical distribution or a skewed conical distribution to the data value.

6. The method of claim 1 further including the step of adjusting the conical distribution values at the edges of the distribution to provide a smoothing effect.

7. The method of claim 1 where the data is gaming data associated with a gaming environment or retail data associated with a retail environment.

8. A graphical computing system for generating a heatmap data visualization including:

one or more processors;

memory;

one or more programs stored in the memory for execution by the one or more processors, the one or more programs including instructions for:

identifying by the one or more processors a finite set of data points in a data set;

positioning data points on a heatmap for graphical representation;

calculating by the one or more processors conical distribution values around a data point based on a data value associated with that data point;

calculating by the one or more processors a highest distribution value from multiple data points where the conical distribution values for the multiple data points overlap;

determining by the one or more processors whether the calculated conical distribution values for a data point location are greater than the data value associated with the data point at that location;

upon a positive determination by the one or more processors calculating inverse conical distribution values around the data point based on the data value;

rendering by the one or more processors the heatmap data visualization based on the calculated and the highest conical distribution values; and

displaying by the one or more processors the rendered heatmap data visualization.

9. The system of claim 8 , the one or more programs further including instructions for rendering by the one or more processors the heatmap data visualization using the data points based on the conic distribution values and inverse conic distribution values.

10. The system of claim 8 , the one or more programs further including instructions for calculating by the one or more processors the inverse conical distribution values by applying one of an inverse frustoconical distribution, an exact inverse conical distribution or a skewed inverse conical distribution to the data value.

11. The system of claim 10 , the one or more programs further including instructions for calculating by the one or more processors the conical distribution values by applying one of a frustoconical distribution, an exact conical distribution or a skewed conical distribution to the data value.

12. The system of claim 8 , the one or more programs further including instructions for calculating by the one or more processors the conical distribution values by applying one of a frustoconical distribution, an exact conical distribution or a skewed conical distribution to the data value.

13. The system of claim 8 , the one or more programs further including instructions for adjusting by the one or more processors the conical distribution values at the edges of the distribution to provide a smoothing effect.

14. A non-transitory computer readable storage medium storing one or more programs configured for execution by an electronic computing device, the one or more programs comprising instructions for:

identifying a finite set of data points in a data set;

positioning data points on a heatmap data visualization for graphical representation;

calculating conical distribution values around a data point based on a data value associated with that data point;

calculating a highest conical distribution value from multiple data points where conical distribution values for the multiple data points overlap;

determining whether the calculated conical distribution values for a data point location are greater than the data value associated with the data point at that location;

upon a positive determination, calculating inverse conical distribution values around the data point based on the data value;

rendering the heatmap data visualization based on the calculated and highest conical distribution values; and

displaying the rendered heatmap data visualization.

15. The non-transitory computer readable storage medium of claim 14 , the one or more programs further including instructions for rendering the heatmap using the data points based on the conic distribution values and inverse conic distribution values.

16. The non-transitory computer readable storage medium of claim 14 , the one or more programs further including instructions for calculating the inverse conical distribution values by applying one of an inverse frustoconical distribution, an exact inverse conical distribution or a skewed inverse conical distribution to the data value.

17. The non-transitory computer readable storage medium of claim 16 , the one or more programs further including instructions for calculating the conical distribution values by applying one of a frustoconical distribution, an exact conical distribution or a skewed conical distribution to the data value.

18. The non-transitory computer readable storage medium of claim 14 , the one or more programs further including instructions for calculating the conical distribution values by applying one of a frustoconical distribution, an exact conical distribution or a skewed conical distribution to the data value.

19. The non-transitory computer readable storage medium of claim 14 , the one or more programs further including instructions for adjusting by the one or more processors the conical distribution values at the edges of the distribution to provide a smoothing effect.

Assignments (7)
RELEASE OF SECURITY INTEREST Recorded Jan 6, 2026
From: SUSSER BANK
To: NEW BIS SAFE LUXCO S.A.R.L.
Reel/Frame 073380/0489 →
ASSIGNMENT OF ASSIGNOR'S INTEREST Recorded Aug 14, 2025
From: BIS SAFE LUXCO S.A.R.L
To: QUICK CUSTOM INTELLIGENCE, LLC
Reel/Frame 072460/0001 →
SECURITY INTEREST Recorded Feb 14, 2023
From: NEW BIS SAFE LUXCO S.A.R.L
To: SUSSER BANK
Reel/Frame 062693/0325 →
RELEASE OF SECURITY INTEREST Recorded Feb 14, 2023
From: VIZEXP HOLDINGS, LLC (FORMERLY KNOWN AS WME BI, LLC)
To: NEW BIS SAFE LUXCO S.A.R.L.
Reel/Frame 062690/0177 →
SECURITY INTEREST Recorded Mar 6, 2018
From: NEW BIS SAFE LUXCO
To: WME BI, LLC
Reel/Frame 045126/0053 →
ASSIGNMENT OF ASSIGNOR'S INTEREST Recorded Sep 20, 2017
From: CARDNO, ANDREW JOHN; INGHAM, PETER STEWART; LEWIN, BART ANDREW; SINGH, ASHOK KUMAR
To: BUSINESS INTELLIGENCE SOLUTIONS SAFE B.V.
Reel/Frame 043644/0325 →
ASSIGNMENT OF ASSIGNOR'S INTEREST Recorded Sep 20, 2017
From: BUSINESS INTELLIGENCE SOLUTIONS SAFE B.V.
To: NEW BIS SAFE LUXCO S.À R.L
Reel/Frame 043644/0332 →
Continuity (5)
Continuation 15277987 · Sep 27, 2016
Continuation 14200903 · Mar 7, 2014
Continuation 12866842
Provisional Application 61115037 · Nov 15, 2008
Related Publication 20180068471A1 · Mar 8, 2018