Profile configuration for a data processing apparatus
View Patent ↗Data processing apparatus is disclosed comprising: a sensor module configured to sense a first profile comprised of one or more attributes of an environment of said data processing apparatus; and a classification module configured to assign a prediction factor to each of said one or more attributes of said first profile and to store each said attribute and assigned prediction factor as a stored profile.
1. A method of operating a data processing apparatus, the method comprising:
sensing a first profile comprised of one or more attributes of an environment of said data processing apparatus;
assigning a prediction factor to each of said one or more attributes of said first profile;
storing each said attribute and assigned prediction factor responsive to a new profile capture signal;
automatically determining a value for the correlation between said first profile and one or more stored profiles; and
generating said new profile capture signal for each said correlation value being less than a threshold level.
2. The method of claim 1 , further comprising determining each said correlation value based on a difference between the presence of one or more attributes in said first profile and the presence of one or more attributes in each of said one or more stored profiles.
3. The method of claim 1 , further comprising determining a best match stored profile, said best match stored profile having the highest correlation value with said first profile, and, for said highest correlation value being equal to or exceeding said threshold value and less than the maximum correlation value, updating said best match stored profile.
4. The method of claim 1 , further comprising normalizing each said assigned prediction factor to the number of attributes in said first profile.
5. The method of claim 2 , further comprising determining each said correlation value based on adding and subtracting prediction factors and adding a prediction factor if associated with an attribute of said stored profile for which a corresponding attribute is present in said first profile and subtracting a prediction factor if associated with an attribute of said stored profile for which a corresponding attribute is not present in said first profile.
6. The method of claim 3 , further comprising updating said best match stored profile by adding thereto an attribute of said first profile not present in said best match stored profile.
7. The method of claim 3 , further comprising modifying the prediction factor of each attribute present in both said best match stored profile and said first profile with a learning factor.
8. The method of claim 4 , wherein each said assigned prediction factor is a number N divided by the number of attributes in said first profile.
9. The method of claim 7 , further comprising adding said learning factor to each prediction factor of each attribute present in both said best match stored profile and said first profile.
10. The method of claim 9 , further comprising normalizing prediction factors of said stored best match profile.
11. A non-transitory computer readable storage medium storing instructions thereon, the instructions when executed by a processor cause the processor to:
sense a first profile comprised of one or more attributes of an environment of said data processing apparatus;
assign a prediction factor to each of said one or more attributes of said first profile;
store each said attribute and assigned prediction factor responsive to a new profile capture signal; and
determine automatically a value for the correlation between said first profile and one or more stored profiles and generating said new profile capture signal for each said correlation value being less than a threshold level.
12. The non-transitory computer readable storage medium of claim 11 , wherein the instructions further comprise instructions that cause the processor to:
determine each said correlation value based on a difference between the presence of one or more attributes in said first profile and the presence of one or more attributes in each of said one or more stored profiles; and
determine each said correlation value based on adding and subtracting prediction factors and adding a prediction factor if associated with an attribute of said stored profile for which a corresponding attribute is present in said first profile and subtracting a prediction factor if associated with an attribute of said stored profile for which a corresponding attribute is not present in said first profile.
13. A method of operating data processing apparatus, the method comprising:
sensing a first profile comprised of one or more attributes of an environment of said data processing apparatus;
assigning a prediction factor to each of said one or more attributes of said first profile;
normalizing each said assigned prediction factor to the number of attributes in said first profile; and
storing each said attribute and assigned prediction factor responsive to a new profile capture signal.
14. The method of claim 13 , further comprising determining each said correlation value based on a difference between the presence of one or more attributes in said first profile and the presence of one or more attributes in each of said one or more stored profiles.
15. The method of claim 13 , further comprising:
automatically determining a value for the correlation between said first profile and one or more stored profiles; and
generating said new profile capture signal for each said correlation value being less than a threshold level.
16. The method of claim 13 , wherein each said assigned prediction factor is a number N divided by the number of attributes in said first profile.
17. The method of claim 14 , further comprising determining each said correlation value based on adding and subtracting prediction factors and adding a prediction factor if associated with an attribute of said stored profile for which a corresponding attribute is present in said first profile and subtracting a prediction factor if associated with an attribute of said stored profile for which a corresponding attribute is not present in said first profile.
18. The method of claim 15 , further comprising determining a best match stored profile, said best match stored profile having the highest correlation value with said first profile, and, for said highest correlation value being equal to or exceeding said threshold value and less than the maximum correlation value, updating said best match stored profile.
19. The method of claim 18 , further comprising updating said best match stored profile by adding thereto an attribute of said first profile not present in said best match stored profile.
20. The method of claim 18 , further comprising modifying the prediction factor of each attribute present in both said best match stored profile and said first profile with a learning factor.
21. The method of claim 20 , further comprising adding said learning factor to each prediction factor of each attribute present in both said best match stored profile and said first profile.
22. A non-transitory computer readable storage medium storing instructions thereon, the instructions when executed cause at least one processor to:
sense a first profile comprised of one or more attributes of an environment of said data processing apparatus;
assign a prediction factor to each of said one or more attributes of said first profile;
normalize each said assigned prediction factor to the number of attributes in said first profile; and
store each said attribute and assigned prediction factor responsive to a new profile capture signal.
23. The non-transitory computer readable storage medium of claim 22 , further comprising instructions that cause the at least one processor to determine each said correlation value based on a difference between the presence of one or more attributes in said first profile and the presence of one or more attributes in each of said one or more stored profiles.
24. The non-transitory computer readable storage medium of claim 22 , wherein each said assigned prediction factor is a number N divided by the number of attributes in said first profile.
25. The non-transitory computer readable storage medium of claim 23 , further comprising instructions that cause the at least one processor to determine each said correlation value based on adding and subtracting prediction factors and adding a prediction factor if associated with an attribute of said stored profile for which a corresponding attribute is present in said first profile and subtracting a prediction factor if associated with an attribute of said stored profile for which a corresponding attribute is not present in said first profile.