VISUALIZATION OF DYNAMIC, WEIGHTED NETWORKS

• US 20140253556A1
• Filed: 03/11/2013
• Published: 09/11/2014
• Est. Priority Date: 03/11/2013
• Status: Abandoned Application

• Current Assignee: Microsoft Technology Licensing LLC (Microsoft Corporation)
• Original Assignee: Microsoft Corporation
• Inventors: Riche, Nathalie Henry, Lee, Bongshin, Carpendale, Sheelagh
• Application Number:
  US13/792,246
• Publication Number:
  US 20140253556A1
• Time in Patent Office: Days
• US Class Current: 345/440
• CPC Class Codes: G06T 11/206 Drawing of charts or graphs
• CPC Class Codes: H04L 41/22 comprising specially adapted graphical user interfaces [GUI]

Abstract

A method, system, and one or more computer-readable storage media for a visualizing dynamic, weighted network are provided herein. The method includes generating, via a computing device, a table for visualizing a dynamic, weighted network. Each row of the table represents a link within the dynamic, weighted network. Each column of the table represents a time point, and each cell of the table includes a weight of a corresponding link at a corresponding time point. The method also includes manipulating the table to identify a pattern within the dynamic, weighted network in response to input by a user of the computing device.

Claims

1. A method for visualizing a dynamic, weighted network, comprising:

generating, via a computing device, a table for visualizing a dynamic, weighted network, wherein each row of the table comprises a link within the dynamic, weighted network, each column of the table comprises a time point, and each cell of the table comprises a weight of a corresponding link at a corresponding time point; and

manipulating the table to identify a pattern within the dynamic, weighted network in response to input by a user of the computing device.

2. The method of claim 1, wherein manipulating the table comprises analyzing a particular row within the table to visualize an evolution of a corresponding link over a specific period of time.

3. The method of claim 1, wherein manipulating the table comprises aggregating any of the columns and/or any of the rows within the table.

4. The method of claim 3, comprising performing multi-level aggregation by aggregating a plurality of rows to visualize an evolution of a plurality of corresponding links over time.

5. The method of claim 1, wherein manipulating the table comprises reordering any of the columns and/or any of the rows within the table.

6. The method of claim 5, wherein reordering any of the columns and/or any of the rows within the table comprises performing an automatic sorting procedure via the computing device in response to input by the user.

7. The method of claim 5, wherein reordering any of the columns and/or any within the rows of the table comprises manually rearranging any of the columns and/or any of the rows within table in response to input by the user.

8. The method of claim 1, wherein manipulating the table comprises filtering any of the columns and/or any of the rows within the table.

9. The method of claim 8, comprising:

generating a graphical visualization representing a weight of each of a plurality of links within the dynamic, weighted graph at a particular time point by aggregating a plurality of cells corresponding to different rows and a same column within the table; and

tightly coupling the table to the graphical visualization.

10. The method of claim 1, comprising representing each row within the table as a stream graph showing an evolution of a corresponding link over time.

11. A computing system for visualizing a dynamic, weighted network, comprising:

a processor that is adapted to execute stored instructions; and

a system memory, wherein the system memory comprises code configured to;

generate a table for visualizing a dynamic, weighted network, wherein each row of the table comprises a link within the dynamic, weighted network, each column of the table comprises a time point, and each cell of the table comprises a weight of a corresponding link at a corresponding time point; and

manipulate the table to identify a pattern within the dynamic, weighted network in response to input by a user.

12. The system of claim 11, wherein the system memory comprises code configured to manipulate the table by aggregating any of the columns and/or any of the rows within the table.

13. The system of claim 12, wherein the system memory comprises code configured to perform multi-level aggregation of a plurality of columns and a plurality of rows within the table.

14. The system of claim 11, wherein the system memory comprises code configured to manipulate the table by reordering any of the columns and/or any of the rows within the table.

15. The system of claim 11, wherein the system memory comprises code configured to manipulate the table by filtering any of the columns and/or any of the rows within the table.

16. The system of claim 11, wherein the system memory comprises code configured to tightly couple the table to a graphical visualization corresponding to the table.

17. The system of claim 11, wherein the system memory comprises code configured to generate a node-link diagram representing a weight of each of a plurality of links within the dynamic, weighted graph at a particular time point by aggregating a plurality of cells corresponding to different rows and a same column within the table.

18. The system of claim 17, wherein the system memory comprises code configured to tightly couple the table to the node-link diagram

19. One or more computer-readable storage media for storing computer-readable instructions, the computer-readable instructions providing a system for visualizing a dynamic, weighted network when executed by one or more processing devices, the computer-readable instructions comprising code configured to:

generate a table for visualizing the dynamic, weighted network, wherein each row of the table comprises a connection between two nodes within the dynamic, weighted network, each column of the table comprises a time point, and each cell of the table comprises a strength of a corresponding connection at a corresponding time point; and

aggregate, reorder, and filter any number of the columns and any number of the rows within the table to identify a pattern within the dynamic, weighted network.

20. The one or more computer-readable storage media of claim 19, wherein the computer-readable instructions comprise code configured to tightly couple the table to a graphical visualization corresponding to the table.