Neural network based rating system

• US 20070094172A1
• Filed: 07/21/2006
• Published: 04/26/2007
• Est. Priority Date: 07/22/2005
• Status: Abandoned Application

• Current Assignee: Stephen Thaler
• Original Assignee: Stephen Thaler
• Inventors: Thaler, Stephen
• Application Number:
  US11/491,411
• Publication Number:
  US 20070094172A1
• Time in Patent Office: Days
• US Class Current: 706/16
• CPC Class Codes: G06N 3/08 Learning methods
• CPC Class Codes: G06N 3/10 Interfaces, programming languages or software development kits, e.g. for simulating neural networks

Abstract

A neural network-based rating system includes a data set, said data set further comprising at least two records and at least one field associated with said records and a data rating application, which includes means for user input of ratings for at least a first of said records of said data set; at least one artificial neural network; means for automatically dimensioning said artificial neural network as a function of said fields within said data set; means for initiating training of said artificial neural network, said trained artificial neural network operative to generate ratings for at least a second of said records of said data set; means for initiating rating of at least said second record of said data set by said trained artificial neural network; and means for sorting said data set based on said user ratings and said artificial neural network-generated ratings.

Claims

1. A neural network-based rating system, comprising:

a data set, said data set further comprising at least two records and at least one field associated with said records;

a data rating application, further comprising;

means for user input of ratings for at least a first of said records of said data set;

at least one artificial neural network;

means for automatically dimensioning said artificial neural network as a function of said fields within said data set;

means for initiating training of said artificial neural network, said trained artificial neural network operative to generate ratings for at least a second of said records of said data set;

means for initiating rating of at least said second record of said data set by said trained artificial neural network; and

means for sorting said data set based on said user ratings and said artificial neural network-generated ratings.

2. The neural network-based rating system of claim 1, wherein said data set is integrated with said data rating application.

3. The neural network-based rating system of claim 1, further comprising a communication link between said data set and said data rating application and wherein said data set and said data rating application reside on first and second remote computer, respectively.

4. The neural network-based rating system of claim 3, wherein said communication link is selected from the group consisting of the Internet, a wide area network, and a local area network.

5. The neural network-based rating system of claim 1, wherein said system further comprises a graphical user interface.

6. The neural network-based rating system of claim 5, wherein said graphical user interface comprises a spreadsheet-type screen comprising a grid representing said records and said field.

7. The neural network-based rating system of claim 5, wherein said graphical user interface comprises a depiction of an object associated with said records of said data set.

8. The neural network-based rating system of claim 1, wherein said artificial neural network comprises at least one hetero-associative network.

9. The neural network-based rating system of claim 1, wherein said artificial neural network comprises at least one auto-associative network.

10. The neural network-based rating system of claim 1, wherein said means for initiating training of said artificial neural network operates as ratings are entered via said user interface.

11. The neural network-based rating system of claim 1, wherein said means for initiating training of said at least one neural network operates automatically upon user input of ratings for said at least first record.

12. The neural network-based rating system of claim 1, wherein said means for initiating rating of said second portion of said data set by said trained artificial neural network automatically initiates rating once said artificial neural network is trained.

13. The neural network-based rating system of claim 1, wherein said means for sorting said data set by said ratings generated by said artificial neural network automatically initiates sorting once said artificial neural network is trained and finishes rating said second portion of said data set.

14. The neural network-based rating system of claim 1, wherein said user input means is selected from the group consisting of a mouse, a keyboard, and a tablet device.

15. The neural network-based rating system of claim 1, wherein said user input means comprises a sensor.

16. The neural network-based rating system of claim 15, wherein said sensor is a biometric sensor.

17. The neural network-based rating system of claim 1, wherein said user input means comprises a speech recognition system.

18. The neural network-based rating system of claim 1, wherein said user input means comprises a video camera.

19. The neural network-based rating system of claim 18, wherein said user input means further comprises a facial recognition system.

20. The neural network-based rating system of claim 1, wherein said artificial neural network comprises a group membership filter.

21. A neural network based rating process, comprising the steps of:

providing a data set, said data set comprising at least two records and at least one field associated with said records;

inputting ratings for at least one of said records;

providing at least one artificial neural network which is integrated into a single executable file associated with said rating process;

automatically dimensioning said artificial neural network as a function of said fields associated with said data set;

training said dimensioned artificial neural network based on said at least one rating input;

rating at least one unrated record within said data set; and

sorting said records of said data set based on said input ratings and ratings generated by said artificial neural network.

22. The neural network-based rating process of claim 21, wherein said step of inputting ratings further comprises a user indicating a rating by manipulating a data entry device.

23. The neural network-based rating process of claim 21, wherein said step of inputting ratings further comprises sensing a user'"'"'s degree of satisfaction via a sensor.

24. The neural network-based rating process of claim 21, wherein said step of providing at least one artificial neural network further comprises providing an auto-associative artificial neural network.

25. The neural network-based rating process of claim 21, wherein said step of providing at least one artificial neural network further comprises providing a hetero-associative artificial neural network.

26. The neural network-based rating process of claim 21, further comprising the step of displaying said data set to a user and wherein said step of sorting said records further comprises displaying said sorted records to said user.

27. The neural network-based rating process of claim 26, wherein said step of displaying said data set to said user further comprises producing a spreadsheet-type screen comprising a grid representing said records and said field.

28. The neural network-based rating process of claim 26, wherein said step of displaying said data set to said user further comprises producing a depiction of an object associated with said records of said data set.

29. The neural network-based rating process of claim 26, wherein said step of displaying said data set to said user further comprises producing a sensation associated with said records of said data set.