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Researcher profile

Miao Zhao

6 papers in the PaperMetrix corpus

Publications

Papers by this author

  1. Knowledge Graph Convolutional Networks for Recommender Systems

    2019

    To alleviate sparsity and cold start problem of collaborative filtering based recommender systems, researchers and engineers usually collect attributes of users and items, and design delicate algorithms to exploit these additional information. In general, the …

  2. Knowledge-aware Graph Neural Networks with Label Smoothness Regularization for Recommender Systems

    2019 · arXiv (Cornell University)

    Knowledge graphs capture structured information and relations between a set of entities or items. As such knowledge graphs represent an attractive source of information that could help improve recommender systems. However, existing approaches in this …

  3. Poformer: A simple pooling transformer for speaker verification

    2021 · arXiv (Cornell University)

    Most recent speaker verification systems are based on extracting speaker embeddings using a deep neural network. The pooling layer in the network aims to aggregate frame-level features extracted by the backbone. In this paper, we …

  4. RippleNet

    2018

    To address the sparsity and cold start problem of collaborative filtering, researchers usually make use of side information, such as social networks or item attributes, to improve recommendation performance. This paper considers the knowledge graph …

  5. Multi-Task Feature Learning for Knowledge Graph Enhanced Recommendation

    2019

    Collaborative filtering often suffers from sparsity and cold start problems in real recommendation scenarios, therefore, researchers and engineers usually use side information to address the issues and improve the performance of recommender systems. In this …

  6. Exploring High-Order User Preference on the Knowledge Graph for Recommender Systems

    2019 · ACM Transactions on Information Systems

    To address the sparsity and cold-start problem of collaborative filtering, researchers usually make use of side information, such as social networks or item attributes, to improve the performance of recommendation. In this article, we consider …