System and method for placing candidate spines into a display with the aid of a digital computer

• US 9,858,693 B2
• Filed: 05/16/2016
• Issued: 01/02/2018
• 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): LEROUX, ETIENNE PIERRE
• Application Number:
  US15/156,233
• Publication Number:
  US 20160259845A1
• Time in Patent Office: 596 Days
• 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: Y10S 707/99935 Query augmenting and refining, e.g. inexact access

Abstract

A system and method for placing candidate spines into a display with the aid of a digital computer is provided. Candidate spines each having two or more clusters of documents are generated. Each cluster is associated with one or more concept scores for concepts identified within the documents of that cluster. A concept score vector is generated for each candidate spine by aggregating as spine concept scores, the cluster concept scores of the clusters associated with that candidate spine. The candidate spines are ordered by a number of the clusters associated with each candidate spine. Those candidate spines that are sufficiently dissimilar from the other candidate spines are identified based on the candidate spine concept score vectors. The sufficiently dissimilar candidate spines are placed in a display and at least a portion of the unplaced candidate spines are placed in relation to the placed candidate spines.

Claims

1. A method for placing candidate spines into a display with the aid of a digital computer, comprising:

generating candidate spines each comprising two or more clusters of documents, wherein each cluster is associated with one or more concept scores for concepts identified within the documents of that cluster;

generating a concept score vector for each candidate spine by aggregating as spine concept scores, the cluster concept scores of the clusters associated with that candidate spine;

normalizing each spine concept score in the spine concept score vector by dividing the spine concept score by a length of the spine concept score vector;

ordering the candidate spines by a number of the clusters associated with each candidate spine;

identifying those candidate spines sufficiently dissimilar from the other candidate spines based on the candidate spine concept score vectors;

placing the sufficiently dissimilar candidate spines in a display; and

placing at least a portion of the unplaced candidate spines in relation to the placed candidate spines.

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

discarding those candidate spines having one of concepts referenced by more than 10% of the clusters and that do not have a predetermined number of clusters.

3. A method according to claim 2, wherein the predetermined number of clusters is five or more.

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

identifying the sufficiently dissimilar candidate spines based on a measure of similarity of each candidate spine with each other candidate spine.

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

calculating the similarity of each candidate spine to each previous candidate spine in the ordering; and

selecting the candidate spines with a low similarity to each of the other candidate spines as sufficiently dissimilar.

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

ordering the unplaced candidate spines based on the number of clusters prior to placement in the display.

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

obtaining further clusters of documents; and

assigning one or more of the clusters of documents to at least one of the placed candidate spines.

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

generating the cluster concepts, comprising;

determining a cumulative score for each concept appearing in the documents of each cluster;

ranking the concepts by the cumulative scores;

applying acceptance criteria to the ranked concepts; and

selecting those concepts that satisfy the acceptance criteria as the cluster concepts.

9. A method according to claim 1, wherein the acceptance criteria comprise at least one of inclusion of one such concept in a center of one such cluster, inclusion of the concept in a minimum number of documents in the cluster, and inclusion of the concept in a predetermined percentage of documents in the cluster.