Appetite improvement system through memory association

1. A method comprising:

analyzing, by one or more computer processors, a plurality of user information sources related to a user;

defining, by the one or more computer processors, a positive user sentiment expressed by the user in the plurality of user information sources;

identifying, by the one or more computer processors, at least one factor that correlates with the positive user sentiment expressed by the user;

ranking, by the one or more computer processors, the at least one factor based on a strength of the correlation;

responsive to determining that the strength of the correlation is above a predefined threshold, storing, by the one or more computer processors, the at least one factor as a positive token;

generating, by the one or more computer processors, a plurality of food profiles, wherein a respective food item in the plurality of food profiles includes a corresponding recipe information, a corresponding nutritional information, and a corresponding food property information;

responsive to mapping the at least one positive token to the plurality of food profiles, identifying, by the one or more computer processors, based on the corresponding recipe information, the corresponding nutritional information, and the corresponding food property information, at least one food item that incorporates the at least one positive token, wherein the at least one positive token is associated with the positive sentiment expressed by the user; and

continuously updating, by the one or more computer processors, a recommendation list including the at least one food item having a preparation information to resemble the at least one positive token to the user.

2. The method of claim 1 , further comprising:

receiving, by the one or more computer processors, at least one image related to the user;

defining, by the one or more computer processors, the positive user sentiment with respect to the at least one image based on machine learning techniques; and

applying, by the one or more computer processors, image analysis on the at least one image to identify the at least one factor that correlates with the positive user sentiment.

3. The method of claim 1 , further comprising:

receiving, by the one or more computer processors, a brain state data related to the user;

defining, by the one or more computer processors, the positive user sentiment with respect to the brain state data based on machine learning techniques; and

applying, by the one or more computer processors, an analysis on the brain state data to identify the at least one factor that correlates with the positive user sentiment.

4. The method of claim 1 , wherein the at least one factor that correlates with the positive user sentiment is selected from the group consisting of:

a theme, a subject, an object, a person, an activity, a setting, an environmental condition, and a time of day.

5. The method of claim 3 , further comprising:

monitoring, by the one or more computer processors, the brain state data while the user eats a particular food item; and

storing, by the one or more computer processors, the brain state data as being associated with the particular food item.

6. The method of claim 1 , wherein analyzing the plurality of user information sources related to the user is selected from the group consisting of:

performing image analysis, performing text analysis, performing natural language processing, performing semantic analysis, performing sentiment analysis, performing rule-based analysis, and performing machine learning-based analysis.

7. The method of claim 1 , further comprising:

responsive to determining that no food item is identified to incorporate the at least one positive token, modifying, by the one or more computer processors, the at least one food item to incorporate the at least one positive token.