Automated classification algorithm comprising at least one input-invariant part

• US 8,417,653 B2
• Filed: 08/24/2011
• Issued: 04/09/2013
• Est. Priority Date: 09/14/2007
• Status: Active Grant

• Current Assignee: Accenture Global Services Limited (Accenture PLC)
• Original Assignee: Accenture Global Services Limited (Accenture PLC)
• Inventors: Probst, Katharina, Ghani, Rayid
• Primary Examiner(s): Holmes, Michael B
• Application Number:
  US13/216,840
• Publication Number:
  US 20110307429A1
• Time in Patent Office: 594 Days
• Field of Search: 706/14
• US Class Current: 706/14
• CPC Class Codes: G06N 20/00 Machine learning
• CPC Class Codes: G06N 7/01 Probabilistic graphical models, e.g. probabilistic networks

Abstract

A classification algorithm is separated into one or more input-invariant parts and one or more input-dependent classification parts. Classifiable electronic data is obtained via a communication network. Using the classification algorithm, classifications of a plurality of data elements in the classifiable data are identified, where the at least one classification part incorporates user input concerning classification of at least one data element of the plurality of data elements.

Claims

1. A method for performing classification on classifiable electronic data, the method comprising:

obtaining the classifiable electronic data via a communication network; and

identifying classifications of a plurality of data elements in the classifiable electronic data using a classification algorithm comprising at least one input-invariant part and at least one classification part, the at least one classification part incorporating user input concerning classification of at least one data element of the plurality of data elements and each data element of the plurality of data elements comprising at least one non-imaged based textual word.

2. The method of claim 1, further comprising obtaining the classifiable electronic data via a public communication network.

3. The method of claim 1, wherein the classifications comprise an attribute classification and a value classification.

4. The method of claim 1, wherein the classification algorithm comprises a modified co-EM algorithm.

5. A non-transitory machine readable medium having stored thereon instructions that, when executed, cause a processor to:

obtain classifiable electronic data via a communication network; and

identify classifications of a plurality of data elements in the classifiable electronic data using a classification algorithm comprising at least one input-invariant part and at least one classification part, the at least one classification part incorporating user input concerning classification of at least one data element of the plurality of data elements and each data element of the plurality data elements comprising at least one non-imaged based textual word.

6. The machine readable medium of claim 5, wherein those instructions that cause the processor to obtain the classifiable electronic data are further operative to cause the processor Obtain the classifiable electronic data via a public communication network.

7. The machine readable medium of claim 5, wherein those instructions that cause the processor to identify the classifications are further operative to cause the processor to identify the classifications according to an attribute classification and a value classification.

8. The machine readable medium of claim 5, wherein those instructions that cause the processor to identify the classifications using the classification algorithm are further operative to cause the processor o identify the classifications according to a modified co-EM algorithm.

9. An apparatus for performing classification on classifiable electronic data, the apparatus comprising:

a processor;

a storage device, operatively connected to the processor and having stored thereon instructions that, when executed, cause the processor to;

obtain classifiable electronic data via a communication network; and

identifying classifications of a plurality of data elements in the classifiable electronic data using a classification algorithm comprising at least one input-invariant part and at least one classification part, the at least one classification part incorporating user input concerning classification of at least one data element of the plurality of data elements and each data element of the plurality of data elements comprising least one non-based textual word.

11. The apparatus of claim 9, wherein those instructions that cause the processor to identify the classifications are further operative to cause the processor to identify the classifications according to an attribute classification and a value classification.

10. The apparatus of claim wherein hose instructions that cause the processor to obtain the classifiable electronic data are further operative to cause the processor to obtain the classifiable electronic data via a public communication network.

12. The apparatus of claim wherein hose instructions that cause the processor to identify the classifications using the classification algorithm are further operative to cause the processor to identify the classifications according to a modified co-EM algorithm.