Personal taste assessment method and system

1. A method for predicting a person's preference for an item, comprising:

receiving, via an electronic device, identifying information about an item of interest; and

by one or more processors:

accessing a user profile for a person, wherein the user profile comprises a preference model representing associations between the person's ratings of items and a plurality of item characteristics;

accessing a database of characteristic values for a plurality of candidate items;

using the identifying information to identify a candidate item that corresponds to the item of interest and retrieve one or more characteristics of the identified candidate item;

processing the retrieved characteristics with the user profile to generate a predicted rating for the item of interest for the person by:

determining whether the retrieved characteristics of the identified candidate item correspond to one or more indicators of preference in the preference model, and

based on whether the retrieved characteristics of the identified candidate item correspond to one or more indicators of preference, generating the predicted rating as a prediction of whether the person is likely to like or dislike the identified candidate item; and

causing the electronic device to output the predicted rating to the person.

2. The method of claim 1 , wherein:

the item of interest and candidate items are each consumable items and

the retrieved characteristics of the identified candidate item comprise traits that are associated with at least one of the following senses: taste, smell and touch.

3. The method of claim 1 , wherein

upon determining that the identified retrieved characteristics of the identified candidate item correspond to one or more indicators of preference in the preference model,

generating the predicted rating comprises:

entering values of the retrieved characteristics of the identified candidate item into the preference model; and

returning a result of the preference model as the prediction.

4. The method of claim 1 , wherein:

receiving the identifying information about the item of interest comprises receiving an image of the item of interest that is captured by a camera of the electronic device; and

using the identifying information to identify a candidate item that corresponds to the item of interest comprises:

processing the image to extract data from a label or code on the item of interest, and

comparing the extracted data to the candidate items in the database to identify a candidate item that corresponds to the item of interest.

5. The method of claim 4 , further comprising, by a user interface of the electronic device, before receiving the identifying information about the item of interest, prompting the person to use the electronic device to capture the image of the item of interest so that the image includes the identifying information.

6. The method of claim 1 , wherein processing the retrieved characteristics with the user profile to generate the predicted rating comprises:

analyzing dependency patterns in one or more preference models in the user profile; and

using the dependency patterns to generate the predicted rating.

7. The method of claim 6 , wherein analyzing the dependency patterns comprises:

analyzing consistent patterns of dependency in the one or more preference models and identifying a representative rating based on the consistent patterns; and

using the representative rating as the predicted rating.

8. The method of claim 6 , wherein analyzing the dependency patterns comprises:

analyzing contrasting or polarizing patterns of dependency in at least one of the preference models;

processing values of characteristics of the identified candidate item in the at least one preference model having contrasting or polarizing patterns of dependency to yield a result; and

using the result as the predicted rating.

9. The method of claim 1 , wherein processing the retrieved characteristics with the user profile to generate the predicted rating comprises:

determining that no preference model in the user profile can be matched with the characteristics of the identified candidate item; and

generating an inconclusive result as the predicted rating.

10. The method of claim 1 , wherein processing the retrieved characteristics with the user profile to generate the predicted rating comprises:

determining that no preference models in the user profile is sufficiently reflective of how the person would have rated the item; and

generating an inconclusive result as the predicted rating.

11. A system for predicting a person's preference for an item, comprising:

one or more processors:

a database of characteristic values for a plurality of candidate items;

a computer-readable memory storing a user profile for a person, wherein the user profile comprises a preference model representing associations between the person's ratings of items and a plurality of item characteristics; and

a computer-readable memory containing programming instructions that, when executed, cause one or more of the processors to:

receive identifying information about an item of interest;

access the database and use the identifying information to identify a candidate item that corresponds to the item of interest and retrieve one or more characteristics of the identified candidate item;

process the retrieved characteristics with the user profile to generate a predicted rating for the item of interest for the person by:

determining whether the retrieved characteristics of the identified candidate item correspond to one or more indicators of preference in the user profile, and

based on whether the retrieved characteristics of the identified candidate item correspond to one or more indicators of preference, generating the predicted rating as a prediction of whether the person is likely to likely to like or dislike the identified candidate item; and

output the predicted rating.

12. The system of claim 11 , wherein the computer-readable memory comprises additional instructions to process the retrieved characteristics with the user profile to generate a predicted rating for the item of interest for the person comprise instructions to:

upon determining that the retrieved characteristics of the identified candidate item correspond to one or more indicators of preference in the user profile

generate the predicted rating by:

entering values of the retrieved characteristics of the identified candidate item into a preference model; and

returning a result of the preference model as the predicted rating.

13. The system of claim 11 , wherein:

the instructions to receive the identifying information about the item of interest comprise instructions to receive an image of the item of interest; and

the instructions to use the identifying information to identify a candidate item that corresponds to the item of interest comprise instructions to:

process the image to extract data from a label or code on the item of interest, and

compare the extracted data to the candidate items in the database to identify a candidate item that corresponds to the item of interest.

14. The system of claim 13 , further comprising:

a camera;

an electronic device user interface; and

additional programming instructions that, when executed, cause one or more of the processors to, before receiving the identifying information about the item of interest, cause the user interface to prompt the person to use the camera to capture the image of the item of interest so that the image includes the identifying information.

15. The system of claim 11 , wherein the instructions to process the retrieved characteristics with the user profile to generate the predicted rating comprise instructions to:

analyze dependency patterns in one or more preference models in the user profile; and

use the dependency patterns to generate the predicted rating.

16. The system of claim 15 , wherein the instructions to analyze the dependency patterns comprise instructions to:

analyze consistent patterns of dependency in the one or more preference models and identify a representative rating based on the consistent patterns; and

use the representative rating as the predicted rating.

17. The system of claim 15 , wherein the instructions to analyze the dependency patterns comprise instructions to:

analyze contrasting or polarizing patterns of dependency in at least one of the preference models;

process values of characteristics of the identified candidate item in the at least one preference model having contrasting or polarizing patterns of dependency to yield a result; and

use the result as the predicted rating.

18. The system of claim 11 , wherein the instructions to process the retrieved characteristics with the user profile to generate the predicted rating comprise instructions to:

determine that no preference model in the user profile can be matched with the characteristics of the identified candidate item; and

generate an inconclusive result as the predicted rating.

19. The system of claim 11 , wherein the instructions to process the retrieved characteristics with the user profile to generate the predicted rating comprise instructions to:

determine that no preference models in the user profile is sufficiently reflective of how the person would have rated the item; and

generate an inconclusive result as the predicted rating.

20. The system of claim 11 , wherein:

the item of interest and candidate items are each consumable items; and

the retrieved characteristics of the identified candidate item comprise traits that are associated with at least one of the following senses: taste, smell and touch.