10. A system for generating a model of a user comprising: a logging unit for receiving user activities on a social network server for the user, the user activities relating to at least one of content items and generating a log of the user activities; a model generation engine coupled to the logging unit, the model generation engine receiving the log of the user activities for a content item, joining the user activities for the content item, expanding attributes of the log by at least one of content and the user based on aggregating responses from the user to features of the content items and profile data of the user and associating the features of the content items with the profile data, generating an expanded log based on expanding the attributes of the log, generating the model based on the expanded log, training the model using a user's rejection to a user interest and the user's recent activity that identifies a recent interest for the user and dynamically updating the model based on training the model; and a scoring engine for generating global scores for the content items from heterogeneous data sources that are normalized for the heterogeneous data sources, identifying candidate items for the user based on the global scores for the content items, generating a stream of content comprising selected items based on the candidate items and the model, providing an explanation for why a selected item is included in the stream of content, the explanation including the user interest associated with the selected item, generating a feedback mechanism for display with the explanation, and receiving the user's rejection of the user interest through the feedback mechanism.
10. A system for generating a model of a user comprising: a logging unit for receiving user activities on a social network server for the user, the user activities relating to at least one of content items and generating a log of the user activities; a model generation engine coupled to the logging unit, the model generation engine receiving the log of the user activities for a content item, joining the user activities for the content item, expanding attributes of the log by at least one of content and the user based on aggregating responses from the user to features of the content items and profile data of the user and associating the features of the content items with the profile data, generating an expanded log based on expanding the attributes of the log, generating the model based on the expanded log, training the model using a user's rejection to a user interest and the user's recent activity that identifies a recent interest for the user and dynamically updating the model based on training the model; and a scoring engine for generating global scores for the content items from heterogeneous data sources that are normalized for the heterogeneous data sources, identifying candidate items for the user based on the global scores for the content items, generating a stream of content comprising selected items based on the candidate items and the model, providing an explanation for why a selected item is included in the stream of content, the explanation including the user interest associated with the selected item, generating a feedback mechanism for display with the explanation, and receiving the user's rejection of the user interest through the feedback mechanism. 13. The system of claim 10 , wherein the model generation engine expands the attributes of the log by the user including identifying the content item in the log, retrieving features and weights associated with the content item, identifying characteristics of the user and associating the characteristics of the user with the features and weights associated with the content item.