منابع مشابه
Trust-aware Recommender Systems Chapter 1 Trust-aware Recommender Systems Trust-aware Recommender Systems 1.1 Recommender Systems Trust-aware Recommender Systems
Recommender systems are an effective solution to the information overload problem, specially in the online world where we are constantly faced with inordinately many choices. These systems try to find the items such as books or movies that match best with users’ preferences. Based on the different approaches to finding the items of interests to users, we can classify the recommender systems int...
متن کاملRecommender Systems
The ongoing rapid expansion of the Internet greatly increases the necessity of effective recommender systems for filtering the abundant information. Extensive research for recommender systems is conducted by a broad range of communities including social and computer scientists, physicists, and interdisciplinary researchers. Despite substantial theoretical and practical achievements, unification...
متن کاملRecommender Systems
Recommender systems assist and augment this natural social process. In a typical recommender system people provide recommendations as inputs, which the system then aggregates and directs to appropriate recipients. In some cases the primary transformation is in the aggregation; in others the system’s value lies in its ability to make good matches between the recommenders and those seeking recomm...
متن کاملRecommender Systems
Recommender systems have become an important part users’ everyday interactions with Web based applications, particularly those driving e-commerce. Businesses have come to realize the potential of these personalized and adaptive systems in order to increase sales and to retain customers. Likewise, Web users have come to rely on such systems to help them in more efficiently finding items of inter...
متن کاملRecommender Systems
The goal of a Recommender System is to generate meaningful recommendations to a collection of users for items or products that might interest them. Suggestions for books on Amazon, or movies on Netflix, are real world examples of the operation of industry-strength recommender systems. The design of such recommendation engines depends on the domain and the particular characteristics of the data ...
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ژورنال
عنوان ژورنال: Physics Reports
سال: 2012
ISSN: 0370-1573
DOI: 10.1016/j.physrep.2012.02.006