Abstract: A monitoring component installed in a network navigation interface, such as an Internet browser, is disclosed. The monitoring component monitors activity of a user performed via the network navigation interface among one or more network resources, such as e-commerce sites, blogs, media hosting sites, and social networking sites. The monitoring component further enables the user to selected at least one monitored activity to be shared with contacts known to the user. An activity service is provided that notifies the contacts of the selected activity and generates recommendations for the user based on the activities reported by the monitoring component. In this manner, users may share activities of interest with their contacts, as well obtain recommendations about items of possible interest.

Abstract: A monitoring component installed in a network navigation interface, such as an Internet browser, is disclosed. The monitoring component monitors activity of a user performed via the network navigation interface among one or more network resources, such as e-commerce sites, blogs, media hosting sites, and social networking sites. The monitoring component further enables the user to selected at least one monitored activity to be shared with contacts known to the user. An activity service is provided that notifies the contacts of the selected activity and generates recommendations for the user based on the activities reported by the monitoring component. In this manner, users may share activities of interest with their contacts, as well obtain recommendations about items of possible interest.

Abstract: A monitoring component installed in a network navigation interface, such as an Internet browser, is disclosed. The monitoring component monitors activity of a user performed via the network navigation interface among one or more network resources, such as e-commerce sites, blogs, media hosting sites, and social networking sites. The monitoring component further enables the user to selected at least one monitored activity to be shared with contacts known to the user. An activity service is provided that notifies the contacts of the selected activity and generates recommendations for the user based on the activities reported by the monitoring component. In this manner, users may share activities of interest with their contacts, as well obtain recommendations about items of possible interest.

Abstract: A recommendations system is provided in various embodiments for selecting items to recommend to a user. The system includes a recommendation engine with a plurality of recommenders, and each recommender identifies a different type of reason for recommending items. In one embodiment, each recommender retrieves item preference data and generates candidate recommendations responsive to a subset of that data. The recommenders also score the candidate recommendations. In certain embodiments, a normalization engine normalizes the scores of the candidate recommendations provided by each recommender. A candidate selector selects at least a portion of the candidate recommendations based on the normalized scores to provide as recommendations to the user. The candidate selector also outputs the recommendations with associated reasons for recommending the items.

Abstract: A recommendations system is provided in various embodiments for selecting items to recommend to a user. The system includes a recommendation engine with a plurality of recommenders, and each recommender identifies a different type of reason for recommending items. In one embodiment, each recommender retrieves item preference data and generates candidate recommendations responsive to a subset of that data. The recommenders also score the candidate recommendations. In certain embodiments, a normalization engine normalizes the scores of the candidate recommendations provided by each recommender. A candidate selector selects at least a portion of the candidate recommendations based on the normalized scores to provide as recommendations to the user. The candidate selector also outputs the recommendations with associated reasons for recommending the items.

Abstract: A recommendations system is provided in various embodiments for selecting items to recommend to a user. The system includes a recommendation engine with a plurality of recommenders, and each recommender identifies a different type of reason for recommending items. In one embodiment, each recommender retrieves item preference data and generates candidate recommendations responsive to a subset of that data. The recommenders also score the candidate recommendations. In certain embodiments, a normalization engine normalizes the scores of the candidate recommendations provided by each recommender. A candidate selector selects at least a portion of the candidate recommendations based on the normalized scores to provide as recommendations to the user. The candidate selector also outputs the recommendations with associated reasons for recommending the items.

Abstract: A recommendations system is provided in various embodiments for selecting items to recommend to a user. The system includes a recommendation engine with a plurality of recommenders, and each recommender identifies a different type of reason for recommending items. In one embodiment, each recommender retrieves item preference data and generates candidate recommendations responsive to a subset of that data. The recommenders also score the candidate recommendations. In certain embodiments, a normalization engine normalizes the scores of the candidate recommendations provided by each recommender. A candidate selector selects at least a portion of the candidate recommendations based on the normalized scores to provide as recommendations to the user. The candidate selector also outputs the recommendations with associated reasons for recommending the items.

Abstract: A recommendations system is provided in various embodiments for selecting items to recommend to a user. The system includes a recommendation engine with a plurality of recommenders, and each recommender identifies a different type of reason for recommending items. In one embodiment, each recommender retrieves item preference data and generates candidate recommendations responsive to a subset of that data. The recommenders also score the candidate recommendations. In certain embodiments, a normalization engine normalizes the scores of the candidate recommendations provided by each recommender. A candidate selector selects at least a portion of the candidate recommendations based on the normalized scores to provide as recommendations to the user. The candidate selector also outputs the recommendations with associated reasons for recommending the items.

Abstract: A recommendations system is provided in various embodiments for selecting items to recommend to a user. The system includes a recommendation engine with a plurality of recommenders, and each recommender identifies a different type of reason for recommending items. In one embodiment, each recommender retrieves item preference data and generates candidate recommendations responsive to a subset of that data. The recommenders also score the candidate recommendations. In certain embodiments, a normalization engine normalizes the scores of the candidate recommendations provided by each recommender. A candidate selector selects at least a portion of the candidate recommendations based on the normalized scores to provide as recommendations to the user. The candidate selector also outputs the recommendations with associated reasons for recommending the items.