Real time recommendation engine

A computer program product having computer executable instructions that when executed by at least one computer having at least one processor, wherein the instructions modify a recommender system to execute a method comprising:

• obtaining a group profile relating to the user, wherein the group profile includes a group of user formed in an ad hoc manner;
• identifying by analyzing by a device data in the group profile indicating interests of the users based on a set of conditions set by the user;
• storing the group profile and the identified data in a profile store;
• creating an activity profile for a plurality of activities at a plurality of locations, each activity having a corresponding activity profile;
• creating, by a device, author profiles for at least one author of a review for at least one of the plurality of activities as an author profile, the author profile corresponding to at least one activity profile;
• identifying by the device at least one trigger event between the group profile, at least one activity profile, and at least one author profile corresponding to the at least one activity profile, wherein the trigger event is identified by a recommendation system within the device, the recommendation system includes:
• providing by, an explicit-implicit database, catalog items acquired responsive to preferences exhibited by a population of users,
• clustering by, a model maker and a cluster engine, the catalog items into catalog dusters, and
• recommending, by a recommender engine, the catalog items in the catalog dusters, wherein the catalog items correspond to the trigger event relating to the group profile;
• generating a list of activities associated with the trigger event;
• displaying the list of activities to the user;
• generating, using machine learning techniques, a list of conditions relating to the user, wherein the conditions indicate a current state of the user;
• determining, by the device, that a trigger condition from the list of conditions has occurred to the user by analyzing by the device, at least one electronic profile associated with the user using natural language processing of the at least one electronic profile and the list of activities;
• determining by the device a duration of the trigger condition;
• associating the determined trigger condition with the group profile by converting by the device, data regarding the determined trigger condition into profile data;
• filtering out, by determining activities in the list of activities that activate the trigger condition, the activities from the list of activities, and
• displaying, by the device, an updated list of activities to the user.

A recommendation system configured to provide recommendations to at least one user comprising:

• at least one processor;
• at least one memory component;
• a recommender engine configured to provide a recommendation to the at least one user;
• the recommender engine configured to execute a method of:
• obtaining a group profile for the user, wherein the group profile includes a group of users formed in an ad hoc manner;
• identifying by analyzing by a device data in the group profile indicating interests of the users based on a set of conditions set by the user;
• storing the user profile and the identified data in a profile store;
• creating an activity profile for a plurality of activities at a plurality of locations, each activity having a corresponding activity profile, wherein each activity is an event;
• creating, by a device, author profiles for at least one author of a review for at least one of the plurality of activities as an author profile, the author profile corresponding to at least one activity profile;
• identifying by the device at least one trigger event between the group profile, at least one activity profile, and at least one author profile corresponding to the at least one activity profile, wherein the trigger event is identified by a recommendation system within the device, the recommendation system includes:
• providing by, an explicit-implicit database, catalog items acquired responsive to preferences exhibited by a population of users,
• clustering by, a model maker and a cluster engine, the catalog items into catalog clusters, and
• recommending, by a recommender engine, the catalog items in the catalog clusters, wherein the catalog items correspond to the trigger event relating to the group profile;
• generating a list of activities associated with the trigger event;
• displaying the list of activities to the user;
• generating, using machine learning techniques, a list of conditions relating to the user, wherein the conditions indicate a current state of the user;
• determining by the device that a trigger condition from the list of conditions has occurred to the user by analyzing, by the device, at least one electronic profile associated with the user using natural language processing of the at least one electronic profile and the list of activities;
• determining by the device a duration of the trigger condition;
• associating the determined trigger condition with the group profile by converting, by the device, data regarding the determined trigger condition into profile data;
• filtering out, by determining activities in the list of activities that activate the trigger condition, the activities from the list of activities;
• and
• displaying, by the device, an updated list of activities to the user.