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YouTube has faced criticism over aspects of its operations, [1] its recommendation algorithms perpetuating videos that promote conspiracy theories and falsehoods, [2] hosting videos ostensibly targeting children but containing violent or sexually suggestive content involving popular characters, [3] videos of minors attracting pedophilic ...
For years YouTube's video-recommending algorithm has stood accused of fuelling a grab bag of societal ills by feeding users an AI-amplified diet of hate speech, political extremism and/or ...
A recommender system (RecSys), or a recommendation system (sometimes replacing system with terms such as platform, engine, or algorithm), is a subclass of information filtering system that provides suggestions for items that are most pertinent to a particular user.
As the numbers of users and items grow, traditional CF algorithms will suffer serious scalability problems [citation needed]. For example, with tens of millions of customers () and millions of items (), a CF algorithm with the complexity of is already too large. As well, many systems need to react immediately to online requirements and make ...
The cold start problem is a well known and well researched problem for recommender systems.Recommender systems form a specific type of information filtering (IF) technique that attempts to present information items (e-commerce, films, music, books, news, images, web pages) that are likely of interest to the user.
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Slope One is a family of algorithms used for collaborative filtering, introduced in a 2005 paper by Daniel Lemire and Anna Maclachlan. [1] Arguably, it is the simplest form of non-trivial item-based collaborative filtering based on ratings. Their simplicity makes it especially easy to implement them efficiently while their accuracy is often on ...