US2015074147A1PendingUtilityA1

Method and Apparatus for Aligning Multiple Taxonomies

Assignee: MUSGROVE TECHNOLOGY ENTPR LLC MTEPriority: Feb 2, 2007Filed: Apr 2, 2014Published: Mar 12, 2015
Est. expiryFeb 2, 2027(~0.5 yrs left)· nominal 20-yr term from priority
G06F 16/367G06F 16/358G06F 17/30713G06F 17/30734G06F 16/36
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Claims

Abstract

A document taxonomy alignment system and method, relying on document glosses and utilizing a soft ontology expansion. An all-new hierarchical leaf node can be created expressly for the purpose of better aligning the plurality of document taxonomies in question. A small but valuable subset of the nodes created by soft ontology expansion turn out to capture some otherwise unmappable taxonomy nodes, and thereby have the effect of classifying the documents better than would any pre-existing node in any one of those taxonomies.

Claims

exact text as granted — not AI-modified
What is claimed is: 
     
         1 . A method comprising:
 mapping a first set of concept nodes in a first taxonomy to a second set of concept nodes in a second taxonomy by aligning nodes with equivalent categories of documents in the first taxonomy and second taxonomy; and   generating a master taxonomy having a plurality of mapped concept nodes, the first set of concept nodes for organizing a first plurality of documents and the second set of concept nodes for organizing a second plurality of documents, each of the first and second plurality of documents associated with a document gloss, each of the mapped concept nodes containing documents from a concept node from the first taxonomy and a concept node from the second taxonomy that contain equivalent categories of documents.   
     
     
         2 . A computer readable storage medium having computer executable instructions recorded thereon which cause a computer system to carry out a method when executed, the method comprising:
 mapping a first set of concept nodes in a first taxonomy to a second set of concepts in a second taxonomy by aligning nodes with equivalent categories of documents in the first taxonomy and second taxonomy; and   generating a master taxonomy having a plurality of mapped concept nodes, the first set of concept nodes for organizing a first plurality of documents and the second set of concept nodes for organizing a second plurality of documents, each of the first and second plurality of documents associated with a document gloss, each of the mapped concept nodes containing documents from a concept node from the first taxonomy and a concept node from the second taxonomy that contain equivalent categories of documents.   
     
     
         3 . A computer system for mapping a taxonomy to at least one other taxonomy, wherein the computer system comprises a non-transitory computer readable storage medium having computer executable instructions recorded thereon which cause a computer system to carry out a method, the taxonomies including categories of documents, the computer system comprising:
 means for mapping a first set of concept nodes in a first taxonomy to a second set of concepts in a second taxonomy by aligning nodes with equivalent categories of documents in the first taxonomy and second taxonomy; and   generating a master taxonomy having a plurality of mapped concept nodes, the first set of concept nodes for organizing a first plurality of documents and the second set of concept nodes for organizing a second plurality of documents, each of the first and second plurality of documents associated with a document gloss, each of the mapped concept nodes containing documents from a concept node from the first taxonomy and a concept node from the second taxonomy that contain equivalent categories of documents.   
     
     
         4 . The method of  claim 1  further comprising reviewing the first taxonomy and the second taxonomy. 
     
     
         5 . The method of  claim 1  wherein the nodes are categories of the first and second plurality of documents. 
     
     
         6 . The method of  claim 1  wherein the first and second plurality of documents are websites. 
     
     
         7 . The method of  claim 1  wherein document glosses are summaries of the first and second plurality of documents in the taxonomies and differentiate each document from other documents in the taxonomies. 
     
     
         8 . The method of  claim 1 , wherein mapping the first set of concept nodes in the first taxonomy to the second set of concepts in the second taxonomy by aligning nodes with equivalent categories of documents in the first taxonomy and second taxonomy to generate the master taxonomy having the plurality of concept nodes comprises:
 combining all documents of all nodes in each of the first and second taxonomies in a single set;   performing a semantic analysis of the documents and the document glosses;   if two words are frequently paired in the document glosses and in the documents, then the documents are related, wherein the word pairs are the concepts;   checking the node document glosses for the presence of the concepts; and   employing a percentage matching algorithm to connect node documents in one taxonomy to leaf nodes of a different taxonomy.   
     
     
         9 . The non-transitory computer readable storage medium of  claim 2  further comprising reviewing the first taxonomy and the second taxonomy. 
     
     
         10 . The non-transitory computer readable storage medium of  claim 2  wherein the nodes are categories of the first and second plurality of documents. 
     
     
         11 . The non-transitory computer readable storage medium of  claim 2  wherein the first and second plurality of documents are websites. 
     
     
         12 . The non-transitory computer readable storage medium of  claim 2  wherein document glosses are summaries of the first and second plurality of documents in the taxonomies and differentiate each document from other documents in the taxonomies. 
     
     
         13 . The non-transitory computer readable storage medium of  claim 2 , wherein mapping the first set of concept nodes in the first taxonomy to the second set of concepts in the second taxonomy by aligning nodes with equivalent categories of documents in the first taxonomy and second taxonomy to generate the master taxonomy having the plurality of concept nodes comprises:
 combining all documents of all nodes in the first taxonomy and the second taxonomy in a single set;   performing a semantic analysis of the documents and the document glosses;   if two words are frequently paired in the document glosses and in the documents, then the documents are related, wherein the word pairs are the concepts; and   checking the node document glosses for the presence of the concepts; and   employing a percentage matching algorithm to connect node documents in one taxonomy to leaf nodes of a different taxonomy.   
     
     
         14 . The system of  claim 3  further comprising means for reviewing the first taxonomy and the second taxonomy. 
     
     
         15 . The system of  claim 3  wherein the nodes are categories of the first and second plurality of documents. 
     
     
         16 . The system of  claim 3  wherein the first and second plurality of documents are websites. 
     
     
         17 . The system of  claim 3  wherein document glosses are summaries of the first and second plurality of documents in the taxonomies and differentiate e document from other documents in the taxonomies. 
     
     
         18 . The system of  claim 3 , wherein the means for mapping the first set of concept nodes in the first taxonomy to the second set of concept nodes in the second taxonomy by aligning nodes with equivalent categories of documents in the first taxonomy and second taxonomy to generate the master taxonomy having the plurality of concept nodes comprises means for:
 combining all documents of all nodes in the first taxonomy and the second taxonomy in a single set;   performing a semantic analysis of the documents and the document glosses;   if two words are frequently paired in the document glosses and in the documents, then the documents are related, wherein the word pairs are the concepts; and   checking the node document glosses for the presence of the concepts; and   employing a percentage matching algorithm to connect node documents in one taxonomy to leaf nodes of a different taxonomy.

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