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Introduction Bridge-Based Ranking is an alternative way to score and rank content by adjusting for user polarization. The most successful implementation of Bridge-Based Ranking, X’s Community Notes, explains that the algorithm favors notes that are rated highly by users across a “diversity of perspectives”. But as I show in this article, ratings from users with diverse perspectives are not necessary for a note to rank highly. It is somewhat more accurate to say that the note must be highly rated regardless of diversity of perspective. ....
Service recommendation is key to improving users’ online experience. The development of the Internet has accelerated the creation of many services, and whether users can obtain good experiences among the massive number of services mainly depends on the quality of service recommendation. It is commonly believed that deep learning has excellent nonlinear fitting ability in capturing the complex interactions between users and items. The advantage in learning intricacy relationships enables deep learning to become an important technology for present service recommendation. Recently, it is noticed that linear models can perform almost as well as the state-of-the-art deep learning models, suggesting that capturing linear relationships between users and items is also very important for recommender systems. Therefore, numerous deep learning systems combined with linear models have been proposed. However, existing models are incapable of considering the size of the embedding. When the embeddi ....