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METHOD AND SERVER FOR TRAINING A MACHINE LEARNING ALGORITHM (MLA) FOR CONTENT RECOMMENDATION GENERATION
METHOD AND SERVER FOR TRAINING A MACHINE LEARNING ALGORITHM (MLA) FOR CONTENT RECOMMENDATION GENERATION
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机译:用于训练内容推荐生成的机器学习算法的方法和服务器
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摘要
A method of training machine learning algorithm for selecting recommended content for a user of an electronic device is provided. The method is executable by a recommendation server accessible by the electronic device via a communication network, the recommendation server executing the machine learning algorithm, once trained. The method comprises: acquiring an indication of a plurality of user-item interactions, each user-item interaction being associated with a user and a digital item; based on the plurality of user-item interactions, generating a matrix of user-item relevance scores; factorizing the matrix of user-item relevance scores into a user matrix and an item matrix, said factorizing including: initializing the item matrix using item vectors, the item vectors having been generated such that digital items with similar content have similar item vectors, initializing the user matrix with user-vectors; iteratively optimizing of the user matrix and the item matrix; and storing the optimized item matrix.
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