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  2. Recommender system - Wikipedia

    en.wikipedia.org/wiki/Recommender_system

    When the system is limited to recommending content of the same type as the user is already using, the value from the recommendation system is significantly less than when other content types from other services can be recommended. For example, recommending news articles based on news browsing is useful.

  3. Zen (recommendation system) - Wikipedia

    en.wikipedia.org/wiki/Zen_(recommendation_system)

    For example, if a user begins to read about architecture, content on this subject will appear in their content feed more often. [19] [20] Prediction of user interest by using collaborative filtering [9] The technology that underlies Zen was adapted by Yandex and CERN for use in the Large Hadron Collider.

  4. News aggregator - Wikipedia

    en.wikipedia.org/wiki/News_aggregator

    The user interface of the feed reader Tiny Tiny RSS. In computing, a news aggregator, also termed a feed aggregator, content aggregator, feed reader, news reader, or simply an aggregator, is client software or a web application that aggregates digital content such as online newspapers, blogs, podcasts, and video blogs (vlogs) in one location for easy viewing.

  5. Category:Recommender systems - Wikipedia

    en.wikipedia.org/wiki/Category:Recommender_systems

    Main page; Contents; Current events; Random article; About Wikipedia; Contact us

  6. Collaborative filtering - Wikipedia

    en.wikipedia.org/wiki/Collaborative_filtering

    This image shows an example of predicting of the user's rating using collaborative filtering. At first, people rate different items (like videos, images, games). After that, the system is making predictions about user's rating for an item, which the user has not rated yet. These predictions are built upon the existing ratings of other users ...

  7. Social information processing - Wikipedia

    en.wikipedia.org/wiki/Social_information_processing

    Another challenge in social recommendation is performing cross-domain recommendation, as in traditional recommender systems. [3] The reason is that social media websites in different domains include different information about users, and merging information within different contexts may not lead to useful recommendations.

  8. Item-item collaborative filtering - Wikipedia

    en.wikipedia.org/wiki/Item-item_collaborative...

    As in user-user systems, similarity functions can use normalized ratings (correcting, for instance, for each user's average rating). Second, the system executes a recommendation stage. It uses the most similar items to a user's already-rated items to generate a list of recommendations.

  9. RSS - Wikipedia

    en.wikipedia.org/wiki/RSS

    RSS feed data is presented to users using software called a news aggregator and the passing of content is called web syndication. Users subscribe to feeds either by entering a feed's URI into the reader or by clicking on the browser's feed icon. The RSS reader checks the user's feeds regularly for new information and can automatically download ...