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基於協同訓練的分布式深度協同過濾模型

Research on Distributed Deep Collaborative Filtering Model Based on Co-Training

  • 摘要: 為解決數據分布式存儲下實現較高精度和安全性的個性化推薦,提出了一種全新的分布式半監督推薦系統框架。嘗試將半監督學習方法中的協同訓練(Co-training)與基於深度學習的深度協同過濾模型結合為Co-NCF模型💆‍♂️,並使用基於consensus算法的分布式梯度下降法來訓練Co-NCF模型👩‍❤️‍💋‍👩,以此構建了Co-NCF模型的分布式版本🧓🏿。該模型在MovieLens數據集上的測試中👊🏻,表現顯著強於現有的分布式NCF模型。

     

    Abstract: In order to realize the personalized recommendation with high accuracy and security, a new framework of distributed semi-supervised recommendation system was proposed. Co-NCF model was established through the combination of the co-training of semi supervised learning method with deep collaborative filtering model based on deep learning. Consensus-based distributed gradient decent algorithm was employed to train the Co-NCF model, so as to build the distributed version of Co-NCF model. In the test of MovieLens dataset, the performance of this model was significantly better than that of the existing distributed NCF model.

     

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