Recommender system


Topic | v1 | created by janarez |
Description

A recommender system, or a recommendation system (sometimes replacing 'system' with a synonym such as platform or engine), is a subclass of information filtering system that seeks to predict the "rating" or "preference" a user would give to an item. They are primarily used in commercial applications. Recommender systems are utilized in a variety of areas and are most commonly recognized as playlist generators for video and music services, product recommenders for online stores, or content recommenders for social media platforms and open web content recommenders. These systems can operate using a single input, like music, or multiple inputs within and across platforms like news, books, and search queries. There are also popular recommender systems for specific topics like restaurants and online dating. Recommender systems have also been developed to explore research articles and experts, collaborators, and financial services.


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Resources

treated in Recommendation Systems

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Welcome to Recommendation Systems! We've designed this course to expand your knowledge of recommendat...

cons given in The Ethical and Privacy Issues of Recommendation Engines on Media Platforms

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Why we should pay more attention to the models that recommend content. Recommendation engines on m...

relates to Deep Neural Networks for YouTube Recommendations

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YouTube represents one of the largest scale and most sophisticated industrial recommendation systems...

cons given in Recommender systems and their ethical challenges

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This article presents the first, systematic analysis of the ethical challenges posed by recommender s...