Generating and providing content recommendations to a group of users

A method for generating content recommendation sets to match structured preference profiles of a group of users, said method comprising:

• using a computing device to automatically generate for each given user in the group, based on a structured user preference profile of the given user:
• (i) individual content recommendation sets, and (ii) a score for each content recommendation in the individual recommendation sets, the score representing a confidence of the system in each recommendation in relation to the given user;
• using a computing device to combine the individual content recommendation sets into an aggregated recommendation set;
• using a computing device to calculate a relevancy level of items in the aggregated recommendation set in relation to each given user in the group by calculating, within a vector space defined by a defined taxonomy of media specific content genes, a distance between:
• (a) a vector representing a set of salience values of first semantic characteristics within the given content item, which first semantic characteristics are selected from the defined taxonomy of media specific content genes, and (b) a centroid of a vector cluster, each vector in the cluster representing a set of values of second semantic characteristics of rated content items related to the given user, which second semantic characteristics are also selected from the defined taxonomy of media specific content genes;
• and
• using a computing device to automatically select a subset of selected content recommendations, from the aggregated recommendation set, for inclusion in a content recommendation result set for the group, based at least partially on:
• a. a number of the individual content recommendation sets including the selected content recommendations;
• b. the scores of the selected content recommendations in the individual content recommendation sets;
• and
• c. the calculated relevancy levels of the selected content recommendations.

A system for generating content recommendation sets to match structured preference profiles of a group of users;

• said system comprising:
• a first computing device including a Recommendation Engine configured to automatically generate for each given user in the group, based on a structured user preference profile of the given user:
• (i) individual content recommendation sets for the given user, and (ii) a score for each content recommendation in the individual recommendation sets, the score representing a confidence of the system in each recommendation;
• a second computing device including a Recommendation Aggregation Module configured to combine the individual content recommendation sets into an aggregated recommendation set;
• and
• a third computing device including a Recommendation Selection Module configured to automatically select a subset of selected content recommendations;
• from the aggregated recommendation set, for inclusion in a content recommendation result set for the group, based at least partially on:
• a. a number of the individual content recommendation sets including the selected content recommendations;
• b. the scores of the selected content recommendations in the individual content recommendation sets;
• and
• c. a community rating of one or more of the selected content recommendations
• a fourth computing device including a Relevancy Level Calculator configured to calculate a relevancy level of a given item in the aggregated recommendation set, in relation to a given user in the group, by calculating, within a vector space defined by a defined taxonomy of media specific content genes, a distance between:
• (a) a vector representing a set of salience values of first semantic characteristics within the given content item, which first semantic characteristics are selected from the defined taxonomy of media specific content genes, and (b) a centroid of a vector cluster, each vector in the cluster representing a set of values of second semantic characteristics of rated content items related to the given user, which second semantic characteristics are also selected from the defined taxonomy of media specific content genes;
• and wherein said Recommendation Selection Module is configured to factor the calculated relevancy levels when automatically selecting a subset of selected content recommendations.

A system for generating content recommendation sets to match structured preference profiles of a group of users;

• said system comprising:
• a first computing device including a Recommendation Engine configured to automatically generate for each given user in the group, based on a structured user preference profile of the given user:
• (i) individual content recommendation sets for the given user, and (ii) a score for each content recommendation in the individual recommendation sets, the score representing a confidence of the system in each recommendation;
• a second computing device including a Recommendation Aggregation Module configured to combine the individual content recommendation sets into an aggregated recommendation set;
• and
• a third computing device including a Recommendation Selection Module configured to automatically select a subset of selected content recommendations, from the aggregated recommendation set, for inclusion in a content recommendation result set for the group, based at least partially on:
• a. a number of the individual content recommendation sets including the selected content recommendations;
• b. the scores of the selected content recommendations in the individual content recommendation sets;
• and
• c. a calculated similarity level above a defined threshold between one or more of the selected content recommendations and a content item associated with a recommendation history of one or more of the users
• a fourth computing device including a Relevancy Level Calculator configured to calculate a relevancy level of a given item in the aggregated recommendation set, in relation to a given user in the group, by calculating, within a vector space defined by a defined taxonomy of media specific content genes, a distance between:
• (a) a vector representing a set of salience values of first semantic characteristics within the given content item, which first semantic characteristics are selected from the defined taxonomy of media specific content genes, and (b) as centroid of a vector cluster, each vector in the cluster representing a set of values of second semantic characteristics of rated content items related to the given user, which second semantic characteristics are also selected from the defined taxonomy of media specific content genes;
• and wherein said Recommendation Selection Module is configured to factor the calculated relevancy levels when automatically selecting a subset of selected content recommendations.