Computer-implemented system and method for placing groups of document clusters into a display

• US 9,384,573 B2
• Filed: 01/25/2016
• Issued: 07/05/2016
• 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:
  US15/005,980
• Publication Number:
  US 20160140742A1
• Time in Patent Office: 162 Days
• Field of Search: None
• US Class Current: 1/1
• 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 computer-implemented system and method for placing groups of document clusters into a display is provided. One or more spines of document clusters are placed into a display and at least one of the document clusters for each placed spine is designated as an anchor cluster. At least one of the unplaced spines is compared with each of the placed spines in the display and one of the placed spines most similar to the unplaced spine is identified. The document clusters of the unplaced spine are compared with the anchor cluster of the most similar placed spine and the cluster on the unplaced spine that is most similar to the anchor cluster on the most similar placed spine is identified. The most similar cluster of the unplaced spine is grafted to the anchor cluster of the most similar placed spine.

Claims

1. A computer-implemented system for placing groups of document clusters into a display, comprising:

a placement module to place one or more spines of document clusters into a display, wherein at least one of the document clusters for each placed spine is designated as an anchor cluster;

a spine selection module to compare at least one of the unplaced spines with each of the placed spines in the display and to identify one of the placed spines most similar to the unplaced spine;

a cluster selection module to compare the document clusters of the unplaced spine with the anchor cluster of the most similar placed spine and to identify the cluster most similar to the anchor cluster of the most similar placed spine; and

a grafting module to graft the most similar cluster of the unplaced spine to the anchor cluster of the most similar placed spine.

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

a document concept determination module to form concepts for each document from terms extracted from that document; and

a score assignment module to assign a score to each of the document concepts.

3. A system according to claim 2, further comprising:

a cluster concept determination module to designate at least one cluster concept for each cluster placed on the spines by determining a cumulative score based on the document concept scores of the documents in that cluster; and

a concept ranking module to rank the cluster concepts by the cumulative score.

4. A system according to claim 3, further comprising:

a theme selection module to select as a theme for each cluster one such concept that is located in an initial center of that cluster and is included in a minimum number of documents in that cluster.

5. A system according to claim 3, wherein the top ranked cluster concepts best summarize the documents in that cluster.

6. A system according to claim 3, further comprising:

a spine concept determination module to select at least one concept for each spine by analyzing each cluster concept assigned to the clusters along that spine and by selecting as the spine concepts, the cluster concepts that are not referenced by a single cluster along that spine and are not referenced by more than a predetermined number of clusters along that spine.

7. A system according to claim 6, further comprising:

a score generator to generate a score for each spine concept by aggregating the cumulative cluster concept scores for each of the clusters along that spine.

8. A system according to claim 7, further comprising:

an anchor cluster selection module to select as the anchor cluster for each spine, one of the clusters that include the spine concept for that spine.

9. A system according to claim 1, further comprising:

an angle determination module to determine an angle for positioning the unplaced spine to the anchor cluster of the most similar placed spine; and

the spine placement module to place the unplaced spine in relation to the most similar placed spine along the angle.

10. A system according to claim 1, further comprising:

a cluster theme determination module to assign concepts to each cluster based on instructions received from a user and to select one such concept as a theme for that cluster, wherein the selected concept is located in an initial center of that cluster and is included in a minimum number of documents in that cluster.

11. A computer-implemented method for placing groups of document clusters into a display, comprising the steps of:

placing one or more spines of document clusters into a display, wherein at least one of the document clusters for each placed spine is designated as an anchor cluster;

comparing at least one of the unplaced spines with each of the placed spines in the display and identifying one of the placed spines most similar to the unplaced spine;

comparing the document clusters of the unplaced spine with the anchor cluster of the most similar placed spine and identifying the cluster on the unplaced spine that is most similar to the anchor cluster on the most similar placed spine; and

grafting the most similar cluster of the unplaced spine to the anchor cluster of the most similar placed spine.

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

forming concepts for each document from terms extracted from that document; and

assigning a score to each of the document concepts based on at least one of a frequency, concept weight, structural weight, and corpus weight of that document concept.

13. A method according to claim 12, further comprising:

designating at least one cluster concept for each cluster associated with the spines, comprising;

determining a cumulative score for each cluster concept based on the document concept scores of the documents in that cluster; and

ranking the cluster concepts by the cumulative score.

14. A method according to claim 13, further comprising:

selecting as a theme for each cluster one such concept that is located in an initial center of that cluster and is included in a minimum number of documents in that cluster.

15. A method according to claim 13, wherein the top ranked cluster concepts best summarize the documents in that cluster.

16. A method according to claim 13, further comprising:

selecting at least one concept for each spine, comprising;

analyzing each cluster concept assigned to the clusters along that spine; and

selecting as the spine concepts, the cluster concepts that are not referenced by a single cluster along that spine and are not referenced by more than a predetermined number of clusters along that spine.

17. A method according to claim 16, further comprising:

generating a score for each spine concept by aggregating the cumulative cluster concept scores for each of the clusters along that spine.

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

selecting as the anchor cluster for each spine, one of the clusters that include the spine concept for that spine.

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

determining an angle for positioning the unplaced spine to the anchor cluster of the most similar placed spine; and

placing the unplaced spine in relation to the most similar placed spine along the angle.

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

assigning concepts to each cluster based on instructions received from a user; and

selecting one such concept as a theme for that cluster, wherein the selected concept is located in an initial center of that cluster and is included in a minimum number of documents in that cluster.