Automatic query clustering

Abstract

The present invention relates to a system and methodology for automatic clusterization and display of data items in a local or remote database system. Such clusterization can be based on properties associated with the data items such as a type, location, people, date, time, user-defined, and so forth, wherein an initial property may be employed to form a first level of clusterization and a subsequent property may be automatically determined to form an optimized clusterization from which to find and retrieve desired information. A computerized interface for organizing and retrieving data is provided. The interface includes a property analyzer to determine an item distribution for at least two cluster properties and an organizer that forms new clusters based in part on the item distribution.

1 . A system for automatically clustering query results, comprising: 
 means for retrieving properties of a plurality of items;    means for determining a score for the plurality of items based upon the properties; and    means for automatically clustering data associated with the items based upon the determined score.    
   
   
       2 . A method for automatic query clustering, comprising: 
 associating one or more properties with a plurality of data items;    determining a distribution for the data items based upon the properties; and    automatically clustering the data items based upon the determined distribution.    
   
   
       3 . The method of  claim 2 , the distribution is determined from at least one of the following equations:  
       score= n _items cluster1   *n _items cluster2 * . . .  score=( N _total)!/(( n _items cluster1 )!*( n _items cluster2 )!* . . . )  
   
   
       4 . The method of  claim 2 , further comprising processing N items and M properties.  
   
   
       5 . The method of  claim 4 , further comprising at least one of initializing M hash tables, iterating through N items and, for each item, iterating through M properties.  
   
   
       6 . The method of  claim 5 , further comprising calculating a hash value for each property.  
   
   
       7 . The method of  claim 6 , further comprising calculating a clusterization score for each property using data from an associated hash table.  
   
   
       8 . The method of  claim 2 , further comprising automatically organizing clusters based upon a predetermined threshold.  
   
   
       9 . The method of  claim 8 , further comprising suggesting alternative cluster grouping.  
   
   
       10 . The method of  claim 8 , further comprising organizing clusters based upon user-defined properties.