Computer-implemented system and method for placing cluster groupings into a display

• US 8,639,044 B2
• Filed: 02/04/2013
• Issued: 01/28/2014
• Est. Priority Date: 02/13/2004
• Status: Expired due to Term

• Current Assignee: Nuix North America Inc. (Nuix Ltd.)
• Original Assignee: FTI Consulting Technology LLC (FTI Consulting Incorporated)
• Inventors: Evans, Lynne Marie
• Primary Examiner(s): MARIAM, DANIEL G
• Application Number:
  US13/758,982
• Publication Number:
  US 20130148905A1
• Time in Patent Office: 358 Days
• Field of Search: 382/181, 382/190, 382/209, 382/224, 382/225, 382/305, 345/440, 345/467, 707/707, 707/710, 707/713
• US Class Current: 382/225
• CPC Class Codes: G06F 16/24578 using ranking
• CPC Class Codes: G06F 16/285 Clustering or classification
• CPC Class Codes: G06F 16/287 Visualization; Browsing
• CPC Class Codes: G06F 16/334 Query execution G06F16/335 takes precedence
• CPC Class Codes: G06F 16/35 Clustering; Classification
• CPC Class Codes: G06F 16/355 Class or cluster creation or modification
• CPC Class Codes: G06F 16/358 Browsing; Visualisation therefor
• CPC Class Codes: G06F 16/93 Document management systems
• CPC Class Codes: G06F 16/9535 Search customisation based on user profiles and personalisation
• CPC Class Codes: G06F 18/00 Pattern recognition
• CPC Class Codes: G06F 18/23 Clustering techniques
• CPC Class Codes: G06T 11/20 Drawing from basic elements, e.g. lines or circles
• CPC Class Codes: G06T 11/206 Drawing of charts or graphs
• CPC Class Codes: G06T 11/60 Editing figures and text; Combining figures or text
• CPC Class Codes: G06T 2200/32 involving image mosaicing
• CPC Class Codes: G06V 30/416 Extracting the logical structure, e.g. chapters, sections or page numbers; Identifying elements of the document, e.g. authors
• CPC Class Codes: H05K 999/99 dummy group
• CPC Class Codes: Y10S 707/99935 Query augmenting and refining, e.g. inexact access

Abstract

A system and method for generating groups of cluster spines for display are provided. One or more concepts for each cluster in a set of clusters are generated. Spines are formed from at least a portion of the clusters based on the concepts. At least one spine unique from all other spines is placed. One or more spine groups are generated by positioning at least one unplaced spine in relation to one of the placed unique spines. The spine groups are displayed.

Claims

1. A method for placing cluster groupings into a display, comprising the steps of:

accessing cluster groups comprising one or more thematically-related clusters;

identifying those cluster groups that are sufficiently dissimilar from the other cluster groups as unique and automatically positioning the unique cluster groups around a shape defined centrally within a display; and

placing the remaining non-unique cluster groups in relation to the unique cluster groups positioned in the display,

wherein the steps are performed by a suitably-programmed computer.

2. A method according to claim 1, further comprising:

placing the unique cluster groups at equal distances around the shape.

3. A method according to claim 1, further comprising:

setting a metric for determining the dissimilarity between the cluster groups as a cosine value of at least 0.2.

4. A method according to claim 1, further comprising:

placing the remaining non-unique cluster groups, comprising;

comparing one such remaining non-unique cluster group against the cluster groups positioned in the display;

determining similarities of the remaining non-unique cluster group and each of the positioned cluster groups; and

placing the remaining non-unique cluster group in relation to the positioned cluster group that is most similar to the remaining non-unique cluster group.

5. A method according to claim 4, further comprising:

rotating the remaining non-unique cluster group when the remaining non-unique cluster group overlaps with the most similar positioned cluster group.

6. A method according to claim 5, wherein the remaining non-unique cluster group is rotated in an anticlockwise direction.

7. A method according to claim 4, further comprising:

a rotation module to rotate the remaining non-unique cluster group when the remaining non-unique cluster group overlaps with the most similar positioned cluster group.

8. A method according to claim 5, further comprising:

determining whether the rotated remaining non-unique cluster group exceeds a maximum angle or a minimum angle relative to a target angle determined via placement of the most similar positioned cluster group; and

moving the rotated remaining non-unique cluster group away from the shape when the rotated remaining non-unique cluster group exceeds one of the maximum angle and the minimum angle.

9. A method according to claim 5, wherein the remaining non-unique cluster group is rotated in an anticlockwise direction.

10. A method according to claim 5, further comprising:

a cluster group movement module to determine whether the rotated remaining non-unique cluster group exceeds a maximum angle or a minimum angle relative to a target angle determined via placement of the most similar positioned cluster group and to move the rotated meaning non-unique cluster group away from the shape when the rotated remaining non-unique cluster group exceeds one of the maximum angle and the minimum angle.

11. A method according to claim 1, further comprising:

generating a group concept score vector for each cluster group comprising aggregating theme concepts for that spine group.

12. A method according to claim 1, wherein the cluster groups each comprise at least one spine of the clusters.

13. A method according to claim 1, wherein the shape comprises a circle.

14. A method according to claim 1, wherein the placement module places the unique cluster groups at equal distances around the shape.

15. A method according to claim 1, further comprising:

a unique determination module to set a metric for determining the dissimilarity between the cluster groups as a cosine value of at least 0.2.

16. A method according to claim 1, wherein the placement module further comprises:

a comparison module to compare one such remaining non-unique cluster group against the cluster groups positioned in the display; and

a similarity determination module to determine similarities of the remaining non-unique cluster group and each of the positioned cluster groups, wherein the remaining non-unique cluster group is placed in relation to the positioned cluster group that is most similar to the remaining non-unique cluster group.

17. A method according to claim 1, further comprising:

a scoring module to generate a group concept score vector for each cluster group comprising aggregating theme concepts for that spine group.

18. A method according to claim 1, wherein the cluster groups each comprise at least one spine of the clusters.

19. A method according to claim 1, wherein the shape comprises a circle.

20. A system for placing cluster groupings into a display, comprising:

cluster groups comprising one or more thematically-related clusters; and

a computer processor to execute modules, comprising;

an identification module to identify those cluster groups that are sufficiently dissimilar from the other cluster groups as unique; and

a group placement to position the unique cluster groups around a shape defined centrally within a display and to place the remaining non-unique cluster groups in relation to the unique cluster groups positioned in the display.