Introduction To Recommenders System. Brief discussion on Analysis, Design And Evolution

      Аннотация: Recommender systems can now be found in many modern applications that expose the user to a huge collection of items. Such systems typically provide the user with a list of recommended items they might prefer, or predict how much they might prefer each item. These systems help users to decide on appropriate items, and ease the task of finding preferred items in the collection.For example, the DVD rental provider Netflix displays predicted ratings for every displayed movie in order to help the user decide which movie to rent. The online book retailer Amazon provides average user ratings for displayed books, and a list of other books that are bought by users who buy a specific book. Microsoft provides many free download for users, such as bug fixes, products and so forth. When a user downloads some software, the system presents a list of additional items that are downloaded together. All these systems are typically categorized as recommender systems, even though they provide diverse services.

Ключевые слова: Web Usage Mining, Information Retrieval, recommender systems, Click-through Phase, Basket Placement Phase, Basket-to-purchase Phase, Background Theory, Content Based Approach, Collaborative Filtering, Hybrid Approach, CBCF