Computer-Implemented System And Method For Forming Document Clusters For Display

Abstract

A computer-implemented system and method for forming document clusters for display is provided. Concepts are identified from a set of documents and a subset of the documents that include those concepts with frequencies of occurrence that occur within a range of concept frequencies are selected from the set. The documents in the subset are assigned to clusters. Each cluster includes a center and a radius, and is placed into a display with the center of that cluster at a fixed distance from the common origin. A portion of the placed clusters are further placed along a common vector.

What is claimed is: 
     
         1 . A computer-implemented system for forming document clusters for display, comprising:
 a set of documents comprising concepts;   a server comprising memory, a central processing unit, an input port to receive the document set, and an output port, wherein the central processing unit is configured to:
 select a subset of the documents from the set that include those concepts with frequencies of occurrence that occur within a range of concept frequencies; 
 assign the documents in the subset to clusters, each cluster comprising a center and a radius; and 
 place each cluster into a display with the center of that cluster at a fixed distance from the common origin, wherein a portion of the placed clusters are further placed along a common vector. 
   
     
     
         2 . A system according to  claim 1 , wherein the central processing unit is further configured to apply tighter ranges of concept frequencies to larger documents than to shorter documents. 
     
     
         3 . A system according to  claim 1 , wherein the central processing unit is further configured to form the clusters by creating an initial cluster and adding additional clusters. 
     
     
         4 . A system according to  claim 1 , wherein the central processing unit is further configured to:
 select a document from the subset and determine a location of the document from the common origin;   determine a location of one of the clusters from the common origin;   calculate a difference between the location of the document and the location of the cluster; and   apply a predetermined threshold to the calculated difference.   
     
     
         5 . A system according to  claim 4 , wherein the central processing unit is further configured to place the selected document in the cluster when the difference is below the predetermined threshold. 
     
     
         6 . A system according to  claim 4 , wherein the central processing unit is further configured to select a further cluster for comparison with the document when the difference is above the predetermined threshold. 
     
     
         7 . A system according to  claim 6 , wherein the central processing unit is further configured to create a new cluster when the difference between the document and each cluster is above the predetermined threshold. 
     
     
         8 . A system according to  claim 1 , wherein the central processing unit is further configured to:
 merge two or more of the clusters into a single cluster;   split one of the clusters into two or more clusters, and   remove outlier clusters.   
     
     
         9 . A system according to  claim 1 , wherein the radius of each cluster reflects a relative number of the documents included in that cluster. 
     
     
         10 . A system according to  claim 1 , wherein each cluster comprises a center of mass and defines a convex volume. 
     
     
         11 . A computer-implemented method for forming document clusters for display, comprising:
 identifying concepts from a set of documents;   selecting a subset of the documents from the set that include those concepts with frequencies of occurrence that occur within a range of concept frequencies;   assigning the documents in the subset to clusters, each cluster comprising a center and a radius; and   placing each cluster into a display with the center of that cluster at a fixed distance from the common origin, wherein a portion of the placed clusters are further placed along a common vector.   
     
     
         12 . A method according to  claim 11 , further comprising:
 applying tighter ranges of concept frequencies to larger documents than to shorter documents.   
     
     
         13 . A method according to  claim 11 , further comprising:
 forming the clusters, comprising:
 creating an initial cluster; and 
 adding additional clusters. 
   
     
     
         14 . A method according to  claim 11 , further comprising:
 selecting a document from the subset and determining a location of the document from the common origin;   determining a location of one of the clusters from the common origin;   calculating a difference between the location of the document and the location of the cluster; and   applying a predetermined threshold to the calculated difference.   
     
     
         15 . A method according to  claim 14 , further comprising:
 when the difference is below the predetermined threshold, placing the selected document in the cluster.   
     
     
         16 . A method according to  claim 14 , further comprising:
 when the difference is above the predetermined threshold, selecting a further cluster for comparison with the document.   
     
     
         17 . A method according to  claim 16 , further comprising:
 when the difference between the document and each cluster is above the predetermined threshold, creating a new cluster.   
     
     
         18 . A method according to  claim 11 , further comprising:
 merging two or more of the clusters into a single cluster;   splitting one of the clusters into two or more clusters, and   removing outlier clusters.   
     
     
         19 . A method according to  claim 11 , wherein the radius of each cluster reflects a relative number of the documents included in that cluster. 
     
     
         20 . A method according to  claim 11 , wherein each cluster comprises a center of mass and defines a convex volume.